diff --git a/automated_detection_testing/detection_service.py b/automated_detection_testing/detection_service.py index f8261d03a4..bb025e0042 100644 --- a/automated_detection_testing/detection_service.py +++ b/automated_detection_testing/detection_service.py @@ -87,7 +87,7 @@ def main(args): try: module = __import__('generate') - results = module.main(REPO_PATH = 'security_content' , OUTPUT_PATH = 'security_content/package', VERBOSE = 'True' ) + results = module.main(REPO_PATH = 'security_content' , OUTPUT_PATH = 'security_content/dist/escu', PRODUCT = 'ESCU', VERBOSE = 'True' ) except Exception as e: print('Error: ' + str(e)) diff --git a/automated_detection_testing/requirements.txt b/automated_detection_testing/requirements.txt index 20a9903175..cabdcc0db2 100644 --- a/automated_detection_testing/requirements.txt +++ b/automated_detection_testing/requirements.txt @@ -5,6 +5,13 @@ aspy.yaml==1.3.0 atomicwrites==1.4.0 attackcti==0.3.4.3 attrs==20.3.0 +azure-common==1.1.25 +azure-core==1.8.2 +azure-identity==1.4.1 +azure-mgmt-compute==17.0.0 +azure-mgmt-core==1.2.1 +azure-mgmt-network==16.0.0 +azure-mgmt-resource==15.0.0 bcrypt==3.2.0 boto3==1.17.30 botocore==1.20.30 @@ -14,7 +21,6 @@ cfgv==2.0.1 chardet==4.0.0 configparser==5.0.2 contextlib2==0.6.0.post1 -cryptography==3.4.4 Deprecated==1.2.12 dnspython==2.1.0 docutils==0.16 diff --git a/bin/generate.py b/bin/generate.py index 06f56e3867..aed5cc18f5 100644 --- a/bin/generate.py +++ b/bin/generate.py @@ -126,7 +126,7 @@ def generate_savedsearches_conf(detections, response_tasks, baselines, deploymen detection['product'] = detection['tags']['product'] if (OUTPUT_PATH) == 'dist/saaws': detection['disabled'] = 'false' - + for baseline in baselines: @@ -340,41 +340,6 @@ def get_deployments(object, deployments): matched_deployments = [] for deployment in deployments: - if 'analytic_story' in deployment['tags']: - if type(deployment['tags']['analytic_story']) is str: - if 'analytic_story' in object['tags']: - if deployment['tags']['analytic_story'] == object['tags']['analytic_story'] or deployment['tags']['analytic_story']=='all': - matched_deployments.append(deployment) - - else: - for story in deployment['tags']['analytic_story']: - if story == object['tags']['analytic_story']: - matched_deployments.append(deployment) - continue - - # Remove this check since deployment files are numbered and detections for Splunk Security Analytics for AWS will only get risk configs. - - # if 'product' in deployment['tags']: - # if type(deployment['tags']['product']) is str: - # if 'product' in object['tags']: - # if deployment['tags']['product'] == object['tags']['product'] or deployment['tags']['product']=='Splunk Security Analytics for AWS': - # matched_deployments.append(deployment) - # else: - # for story in deployment['tags']['product']: - # if story == object['tags']['product']: - # matched_deployments.append(deployment) - # continue - - - if 'detection_name' in deployment['tags']: - if type(deployment['tags']['detection_name']) is str: - if deployment['tags']['detection_name'] == object['name']: - matched_deployments.append(deployment) - else: - for detection in deployment['tags']['detection_name']: - if detection == object['name']: - matched_deployments.append(deployment) - continue for tag in object['tags'].keys(): if tag in deployment['tags'].keys(): @@ -391,21 +356,21 @@ def get_deployments(object, deployments): for tag_value_deployment in tag_array_deployment: if tag_value == tag_value_deployment: + # print("tag value: {}, matched deployment tag: {} on deployment: {}".format(tag_value,tag_value_deployment, deployment)) matched_deployments.append(deployment) continue + # grab default for all stories if deployment not set if len(matched_deployments) == 0: - default_deployment = {} - default_deployment['scheduling'] = {} - default_deployment['scheduling']['cron_schedule'] = '0 * * * *' - default_deployment['scheduling']['earliest_time'] = '-70m@m' - default_deployment['scheduling']['latest_time'] = '-10m@m' - default_deployment['scheduling']['schedule_window'] = 'auto' - last_deployment = default_deployment + for deployment in deployments: + if 'analytic_story' in deployment['tags']: + if deployment['tags']['analytic_story'] == 'all': + last_deployment = deployment else: last_deployment = matched_deployments[-1] last_deployment = replace_vars_in_deployment(last_deployment, object) + # print(last_deployment) return last_deployment @@ -625,7 +590,7 @@ def main(REPO_PATH, OUTPUT_PATH, PRODUCT, VERBOSE): detections = load_objects("detections/*/*.yml", VERBOSE, REPO_PATH) detections.extend(load_objects("detections/*/*/*.yml", VERBOSE, REPO_PATH)) - if PRODUCT == "SAAWS": + if PRODUCT == "SAAWS": detections = [object for object in detections if 'Splunk Security Analytics for AWS' in object['tags']['product']] stories = [object for object in stories if 'Splunk Security Analytics for AWS' in object['tags']['product']] baselines = [object for object in baselines if 'Splunk Security Analytics for AWS' in object['tags']['product']] diff --git a/deployments/10_enterprise_security_deployment_configuration.yml b/deployments/10_enterprise_security_deployment_configuration.yml index e61026ba57..6a9681fd71 100644 --- a/deployments/10_enterprise_security_deployment_configuration.yml +++ b/deployments/10_enterprise_security_deployment_configuration.yml @@ -18,4 +18,4 @@ alert_action: - dest - src tags: - analytics_story: all + analytic_story: all diff --git a/deployments/14_credential_dumping_story.yml b/deployments/14_credential_dumping_story.yml index 5fa4d76e28..86fbc9d80f 100644 --- a/deployments/14_credential_dumping_story.yml +++ b/deployments/14_credential_dumping_story.yml @@ -9,4 +9,4 @@ scheduling: latest_time: -10m@m schedule_window: auto tags: - analytics_story: Credential Dumping + analytic_story: Credential Dumping diff --git a/deployments/16_splunk_security_analytics_for_aws.yml b/deployments/16_splunk_security_analytics_for_aws.yml index 0956e70bd7..b3a7974301 100644 --- a/deployments/16_splunk_security_analytics_for_aws.yml +++ b/deployments/16_splunk_security_analytics_for_aws.yml @@ -11,4 +11,5 @@ scheduling: latest_time: -10m@m schedule_window: auto tags: - product: Splunk Security Analytics for AWS + product: + - Splunk Security Analytics for AWS diff --git a/detections/cloud/aws_excessive_security_scanning.yml b/detections/cloud/aws_excessive_security_scanning.yml new file mode 100644 index 0000000000..be06ec9df0 --- /dev/null +++ b/detections/cloud/aws_excessive_security_scanning.yml @@ -0,0 +1,53 @@ +name: AWS Excessive Security Scanning +id: 1fdd164a-def8-4762-83a9-9ffe24e74d5a +version: 1 +date: '2021-04-13' +author: Patrick Bareiss, Splunk +type: batch +datamodel: [] +description: This search looks for CloudTrail events and analyse the amount of eventNames + which starts with Describe by a single user. This indicates that this user scans + the configuration of your AWS cloud environment. +search: '`cloudtrail` eventName=Describe* OR eventName=List* OR eventName=Get* | + stats dc(eventName) as dc_events min(_time) as firstTime max(_time) as lastTime + values(eventName) as eventName values(src) as src values(userAgent) as userAgent + by user userIdentity.arn | where dc_events > 50 | `security_content_ctime(firstTime)` + | `security_content_ctime(lastTime)`|`aws_excessive_security_scanning_filter`' +how_to_implement: You must install splunk AWS add on and Splunk App for AWS. This + search works with cloudtrail logs. +known_false_positives: While this search has no known false positives. +references: +- https://github.com/aquasecurity/cloudsploit +tags: + analytic_story: + - AWS User Monitoring + asset_type: AWS Account + cis20: + - CIS 13 + kill_chain_phases: + - Actions on Objectives + mitre_attack_id: + - T1526 + nist: + - PR.DS + - PR.AC + - DE.CM + product: + - Splunk Security Analytics for AWS + - Splunk Enterprise + - Splunk Enterprise Security + - Splunk Cloud + required_fields: + - _time + - eventName + - src + - userAgent + - user + - userIdentity.arn + risk_object: src + risk_object_type: system + risk_score: 20 + security_domain: network + automated_detection_testing: passed + dataset: + - https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1526/aws_security_scanner/aws_security_scanner.json diff --git a/detections/endpoint/malicious_powershell_executed_as_a_service.yml b/detections/endpoint/malicious_powershell_executed_as_a_service.yml new file mode 100644 index 0000000000..87849d074d --- /dev/null +++ b/detections/endpoint/malicious_powershell_executed_as_a_service.yml @@ -0,0 +1,49 @@ +name: Malicious Powershell Executed As A Service +id: 8e204dfd-cae0-4ea8-a61d-e972a1ff2ff8 +version: 1 +date: '2021-04-07' +author: Ryan Becwar +type: batch +datamodel: +- Endpoint +description: This detection is to identify the abuse the Windows SC.exe to execute + malicious commands or payloads via PowerShell. +search: ' `wineventlog_system` EventCode=7045 | eval l_Service_File_Name=lower(Service_File_Name) + | regex l_Service_File_Name="powershell[.\s]|powershell_ise[.\s]|pwsh[.\s]|psexec[.\s]" + | regex l_Service_File_Name="-nop[rofile]*|-w[indowstyle]*\s+hid[den]*|-noe[xit]*|-enc[odedcommand]*" + | stats count min(_time) as firstTime max(_time) as lastTime by EventCode Service_File_Name + Service_Name Service_Start_Type Service_Type Service_Account user | `security_content_ctime(firstTime)` + | `security_content_ctime(lastTime)` | `malicious_powershell_executed_as_a_service_filter`' +how_to_implement: To successfully implement this search, you need to be ingesting + Windows System logs with the Service name, Service File Name Service Start type, + and Service Type from your endpoints. +known_false_positives: Creating a hidden powershell service is rare and could key + off of those instances. +references: +- https://www.fireeye.com/content/dam/fireeye-www/blog/pdfs/dosfuscation-report.pdf +- http://az4n6.blogspot.com/2017/ +- https://www.danielbohannon.com/blog-1/2017/3/12/powershell-execution-argument-obfuscation-how-it-can-make-detection-easier +tags: + analytic_story: + - Malicious Powershell + dataset: + - https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1569.002/atomic_red_team/windows-system.log + kill_chain_phases: + - Privilege Escalation + mitre_attack_id: + - T1569.002 + product: + - Splunk Enterprise + - Splunk Enterprise Security + - Splunk Cloud + required_fields: + - EventCode + - Service_File_Name + - Service_Type + - _time + - Service_Name + - Service_Start_Type + - Service_Account + - user + security_domain: endpoint + automated_detection_testing: passed diff --git a/dist/escu/default/analytic_stories.conf b/dist/escu/default/analytic_stories.conf index 35242428a9..8eac00156b 100644 --- a/dist/escu/default/analytic_stories.conf +++ b/dist/escu/default/analytic_stories.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security_content -# On Date: 2021-03-29T18:33:55 UTC +# On Date: 2021-04-14T19:13:35 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -16,7 +16,7 @@ version = 1 reference = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] detection_searches = ["ESCU - aws detect attach to role policy - Rule", "ESCU - aws detect permanent key creation - Rule", "ESCU - aws detect role creation - Rule", "ESCU - aws detect sts assume role abuse - Rule", "ESCU - aws detect sts get session token abuse - Rule"] mappings = {"kill_chain_phases": ["Lateral Movement"], "mitre_attack": ["T1078", "T1550"]} -investigative_searches = ["ESCU - Get Notable History - Response Task", "ESCU - AWS Investigate User Activities By AccessKeyId - Response Task"] +investigative_searches = ["ESCU - AWS Investigate User Activities By AccessKeyId - Response Task", "ESCU - Get Notable History - Response Task"] support_searches = ["ESCU - Previously Seen AWS Cross Account Activity"] data_models = [] providing_technologies = none @@ -24,6 +24,7 @@ description = Track when a user assumes an IAM role in another AWS account to ob narrative = Amazon Web Services (AWS) admins manage access to AWS resources and services across the enterprise using AWS's Identity and Access Management (IAM) functionality. IAM provides the ability to create and manage AWS users, groups, and roles-each with their own unique set of privileges and defined access to specific resources (such as EC2 instances, the AWS Management Console, API, or the command-line interface). Unlike conventional (human) users, IAM roles are assumable by anyone in the organization. They provide users with dynamically created temporary security credentials that expire within a set time period.\ Herein lies the rub. In between the time between when the temporary credentials are issued and when they expire is a period of opportunity, where a user could leverage the temporary credentials to wreak havoc-spin up or remove instances, create new users, elevate privileges, and other malicious activities-throughout the environment.\ This Analytic Story includes searches that will help you monitor your AWS CloudTrail logs for evidence of suspicious cross-account activity. For example, while accessing multiple AWS accounts and roles may be perfectly valid behavior, it may be suspicious when an account requests privileges of an account it has not accessed in the past. After identifying suspicious activities, you can use the provided investigative searches to help you probe more deeply. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [AWS Cryptomining] category = Cloud Security @@ -34,8 +35,8 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078.004", "T1535"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get Notable History - Response Task", "ESCU - Investigate AWS activities via region name - Response Task", "ESCU - Get EC2 Launch Details - Response Task", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Get EC2 Instance Details by instanceId - Response Task"] -support_searches = ["ESCU - Previously Seen EC2 AMIs", "ESCU - Previously Seen EC2 Launches By User", "ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK", "ESCU - Previously Seen AWS Regions", "ESCU - Previously Seen EC2 Instance Types"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Investigate AWS activities via region name - Response Task", "ESCU - Get EC2 Launch Details - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get EC2 Instance Details by instanceId - Response Task"] +support_searches = ["ESCU - Previously Seen EC2 Instance Types", "ESCU - Previously Seen EC2 AMIs", "ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK", "ESCU - Previously Seen EC2 Launches By User", "ESCU - Previously Seen AWS Regions"] data_models = [] providing_technologies = none description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. @@ -43,6 +44,7 @@ narrative = Cryptomining is an intentionally difficult, resource-intensive busin Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS). It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ When malicious miners appropriate a cloud instance, often spinning up hundreds of new instances, the costs can become astronomical for the account holder. So, it is critically important to monitor your systems for suspicious activities that could indicate that your network has been infiltrated. \ This Analytic Story is focused on detecting suspicious new instances in your EC2 environment to help prevent such a disaster. It contains detection searches that will detect when a previously unused instance type or AMI is used. It also contains support searches to build lookup files to ensure proper execution of the detection searches. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [AWS IAM Privilege Escalation] category = Cloud Security @@ -60,6 +62,7 @@ providing_technologies = none description = This analytic story contains detections that query your AWS Cloudtrail for activities related to privilege escalation. narrative = Amazon Web Services provides a neat feature called Identity and Access Management (IAM) that enables organizations to manage various AWS services and resources in a secure way. All IAM users have roles, groups and policies associated with them which governs and sets permissions to allow a user to access specific restrictions.\ However, if these IAM policies are misconfigured and have specific combinations of weak permissions; it can allow attackers to escalate their privileges and further compromise the organization. Rhino Security Labs have published comprehensive blogs detailing various AWS Escalation methods. By using this as an inspiration, Splunk’s research team wants to highlight how these attack vectors look in AWS Cloudtrail logs and provide you with detection queries to uncover these potentially malicious events via this Analytic Story. \ +product = ['Splunk Security Analytics for AWS', 'Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [AWS Network ACL Activity] category = Cloud Security @@ -70,12 +73,13 @@ version = 2 reference = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] detection_searches = ["ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1562.007"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC"]} -investigative_searches = ["ESCU - Get DNS Server History for a host - Response Task", "ESCU - AWS Network Interface details via resourceId - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Process Responsible For The DNS Traffic - Response Task", "ESCU - Get Process Info - Response Task", "ESCU - Get DNS traffic ratio - Response Task", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Get Process Information For Port Activity - Response Task", "ESCU - AWS Network ACL Details from ID - Response Task", "ESCU - Get All AWS Activity From IP Address - Response Task"] -support_searches = ["ESCU - Baseline of Network ACL Activity by ARN", "ESCU - Baseline of blocked outbound traffic from AWS"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Get Process Info - Response Task", "ESCU - AWS Network Interface details via resourceId - Response Task", "ESCU - Get DNS Server History for a host - Response Task", "ESCU - Get Process Information For Port Activity - Response Task", "ESCU - Get All AWS Activity From IP Address - Response Task", "ESCU - Get DNS traffic ratio - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Process Responsible For The DNS Traffic - Response Task", "ESCU - AWS Network ACL Details from ID - Response Task"] +support_searches = ["ESCU - Baseline of blocked outbound traffic from AWS", "ESCU - Baseline of Network ACL Activity by ARN"] data_models = [] providing_technologies = none description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and operational/risk auditing of your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Management Console, AWS Command Line Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable to attacks. This analytic story contains detection searches that leverage CloudTrail logs from AWS to check for bad configurations and malicious activity in your AWS network access controls. +product = ['Splunk Security Analytics for AWS', 'Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [AWS Security Hub Alerts] category = Cloud Security @@ -86,12 +90,13 @@ version = 1 reference = ["https://aws.amazon.com/security-hub/features/"] detection_searches = ["ESCU - Detect Spike in AWS Security Hub Alerts for EC2 Instance - Rule", "ESCU - Detect Spike in AWS Security Hub Alerts for User - Rule"] mappings = {"cis20": ["CIS 13"], "nist": ["DE.AE", "DE.DP"]} -investigative_searches = ["ESCU - Get EC2 Launch Details - Response Task", "ESCU - Get EC2 Instance Details by instanceId - Response Task", "ESCU - AWS Investigate User Activities By ARN - Response Task"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Get EC2 Instance Details by instanceId - Response Task", "ESCU - Get EC2 Launch Details - Response Task"] support_searches = [] data_models = [] providing_technologies = none description = This story is focused around detecting Security Hub alerts generated from AWS narrative = AWS Security Hub collects and consolidates findings from AWS security services enabled in your environment, such as intrusion detection findings from Amazon GuardDuty, vulnerability scans from Amazon Inspector, S3 bucket policy findings from Amazon Macie, publicly accessible and cross-account resources from IAM Access Analyzer, and resources lacking WAF coverage from AWS Firewall Manager. +product = ['Splunk Security Analytics for AWS', 'Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [AWS Suspicious Provisioning Activities] category = Cloud Security @@ -102,13 +107,14 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule"] mappings = {"cis20": ["CIS 1"], "mitre_attack": ["T1535"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get All AWS Activity From Country - Response Task", "ESCU - Get All AWS Activity From Region - Response Task", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Get All AWS Activity From City - Response Task", "ESCU - Get All AWS Activity From IP Address - Response Task", "ESCU - AWS Investigate Security Hub alerts by dest - Response Task"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Get All AWS Activity From City - Response Task", "ESCU - AWS Investigate Security Hub alerts by dest - Response Task", "ESCU - Get All AWS Activity From IP Address - Response Task", "ESCU - Get All AWS Activity From Country - Response Task", "ESCU - Get All AWS Activity From Region - Response Task"] support_searches = ["ESCU - Previously Seen AWS Provisioning Activity Sources"] data_models = [] providing_technologies = none description = Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. narrative = Because most enterprise AWS activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where it is impossible to add specific IPs to an allow list because they vary. \ This Analytic Story was designed to provide you with flexibility in the precision you employ in specifying legitimate geographic regions. It can be as specific as an IP address or a city, or as broad as a region (think state) or an entire country. By determining how precise you want your geographical locations to be and monitoring for new locations that haven't previously accessed your environment, you can detect adversaries as they begin to probe your environment. Since there are legitimate reasons for activities from unfamiliar locations, this is not a standalone indicator. Nevertheless, location can be a relevant piece of information that you may wish to investigate further. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [AWS User Monitoring] category = Cloud Security @@ -117,10 +123,10 @@ modification_date = 2018-03-12 id = 2e8948a5-5239-406b-b56b-6c50f1269af3 version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] -detection_searches = ["ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect new API calls from user roles - Rule"] -mappings = {"cis20": ["CIS 1", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078.004"], "nist": ["DE.CM", "DE.DP", "ID.AM", "PR.AC"]} +detection_searches = ["ESCU - AWS Excessive Security Scanning - Rule", "ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect new API calls from user roles - Rule"] +mappings = {"cis20": ["CIS 1", "CIS 13", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078.004", "T1526"], "nist": ["DE.CM", "DE.DP", "ID.AM", "PR.AC", "PR.DS"]} investigative_searches = ["ESCU - Investigate AWS User Activities by user field - Response Task", "ESCU - Get Notable History - Response Task"] -support_searches = ["ESCU - Baseline of API Calls per User ARN", "ESCU - Previously seen API call per user roles in CloudTrail", "ESCU - Create a list of approved AWS service accounts", "ESCU - Baseline of Security Group Activity by ARN"] +support_searches = ["ESCU - Baseline of API Calls per User ARN", "ESCU - Create a list of approved AWS service accounts", "ESCU - Baseline of Security Group Activity by ARN", "ESCU - Previously seen API call per user roles in CloudTrail"] data_models = [] providing_technologies = none description = Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. @@ -128,6 +134,7 @@ narrative = It seems obvious that it is critical to monitor and control the user In addition to compromising the security of your data, when bad actors leverage your compute resources, it can incur monumental costs, since you will be billed for any new EC2 instances and increased bandwidth usage. \ Fortunately, you can leverage Amazon Web Services (AWS) CloudTrail--a tool that helps you enable governance, compliance, and risk auditing of your AWS account--to give you increased visibility into your user and resource activity by recording AWS Management Console actions and API calls. You can identify which users and accounts called AWS, the source IP address from which the calls were made, and when the calls occurred.\ The detection searches in this Analytic Story are designed to help you uncover AWS API activities from users not listed in the identity table, as well as similar activities from disabled accounts. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Apache Struts Vulnerability] category = Vulnerability @@ -138,7 +145,7 @@ version = 1 reference = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] detection_searches = ["ESCU - Suspicious Java Classes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule"] mappings = {"cis20": ["CIS 12", "CIS 18", "CIS 3", "CIS 4", "CIS 7"], "kill_chain_phases": ["Actions on Objectives", "Delivery", "Exploitation"], "mitre_attack": ["T1082"], "nist": ["DE.AE", "DE.CM", "ID.RA", "PR.IP", "PR.MA", "PR.PT", "RS.MI"]} -investigative_searches = ["ESCU - Investigate Suspicious Strings in HTTP Header - Response Task", "ESCU - Investigate Web POSTs From src - Response Task", "ESCU - Get Notable History - Response Task"] +investigative_searches = ["ESCU - Investigate Web POSTs From src - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Investigate Suspicious Strings in HTTP Header - Response Task"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -157,6 +164,7 @@ hen it is suspected there is an attack targeting a web server, it is helpful to In the event that a suspicious file is found, we can review more information about it to help determine if it is, in fact, malicious. Identifying the file type, any processes that have the file open, what processes created and/or modified the file, and the number of systems that may have this file can help to determine if the file is malicious. Also, determining the file hash and checking it against reputation sources, such as VirusTotal, can sometimes quickly help determine whether it is malicious in nature.\ Often, a simple inspection of a suspect process name and path can tell you if the system has been compromised. For example, if `svchost.exe` is found running from a location other than `C:\Windows\System32`, it is likely something malicious designed to hide in plain sight when simply reviewing process names. Similarly, if the process itself seems legitimate, but the parent process is running from the temporary browser cache, there may be activity initiated via a compromised website the user visited.\ It can also be very helpful to examine various behaviors of the process of interest or the parent of the process that is of interest. For example, if it turns out that the process of interest is malicious, it would be good to see if the parent to that process spawned other processes that might also be worth further scrutiny. If a process is suspect, reviewing the network connections made around the time of the event and/or if the process spawned any child processes could be helpful in determining whether it is malicious or executing a malicious script. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Asset Tracking] category = Best Practices @@ -167,12 +175,30 @@ version = 1 reference = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] detection_searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule"] mappings = {"cis20": ["CIS 1"], "kill_chain_phases": ["Actions on Objectives", "Delivery", "Reconnaissance"], "nist": ["ID.AM", "PR.DS"]} -investigative_searches = ["ESCU - Get Notable History - Response Task", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address - Response Task"] +investigative_searches = ["ESCU - Get First Occurrence and Last Occurrence of a MAC Address - Response Task", "ESCU - Get Notable History - Response Task"] support_searches = ["ESCU - Count of assets by category"] data_models = ["Network_Sessions"] providing_technologies = none description = Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further. narrative = This Analytic Story is designed to help you develop a better understanding of what authorized and unauthorized devices are part of your enterprise. This story can help you better categorize and classify assets, providing critical business context and awareness of their assets during an incident. Information derived from this Analytic Story can be used to better inform and support other analytic stories. For successful detection, you will need to leverage the Assets and Identity Framework from Enterprise Security to populate your known assets. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] + +[BITS Jobs] +category = Adversary Tactics +creation_date = 2021-03-26 +modification_date = 2021-03-26 +id = dbc7edce-8e4c-11eb-9f31-acde48001122 +version = 1 +reference = ["https://attack.mitre.org/techniques/T1197/", "https://docs.microsoft.com/en-us/windows/win32/bits/bitsadmin-tool"] +detection_searches = ["ESCU - BITS Job Persistence - Rule", "ESCU - BITSAdmin Download File - Rule", "ESCU - PowerShell Start-BitsTransfer - Rule"] +mappings = {"kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1105", "T1197"]} +investigative_searches = [] +support_searches = [] +data_models = ["Endpoint"] +providing_technologies = none +description = Adversaries may abuse BITS jobs to persistently execute or clean up after malicious payloads. +narrative = Windows Background Intelligent Transfer Service (BITS) is a low-bandwidth, asynchronous file transfer mechanism exposed through Component Object Model (COM). BITS is commonly used by updaters, messengers, and other applications preferred to operate in the background (using available idle bandwidth) without interrupting other networked applications. File transfer tasks are implemented as BITS jobs, which contain a queue of one or more file operations. The interface to create and manage BITS jobs is accessible through PowerShell and the BITSAdmin tool. Adversaries may abuse BITS to download, execute, and even clean up after running malicious code. BITS tasks are self-contained in the BITS job database, without new files or registry modifications, and often permitted by host firewalls. BITS enabled execution may also enable persistence by creating long-standing jobs (the default maximum lifetime is 90 days and extendable) or invoking an arbitrary program when a job completes or errors (including after system reboots). +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Baron Samedit CVE-2021-3156] category = Adversary Tactics @@ -189,6 +215,7 @@ data_models = [] providing_technologies = none description = Uncover activity consistent with CVE-2021-3156. Discovered by the Qualys Research Team, this vulnerability has been found to affect sudo across multiple Linux distributions (Ubuntu 20.04 and prior, Debian 10 and prior, Fedora 33 and prior). As this vulnerability was committed to code in July 2011, there will be many distributions affected. Successful exploitation of this vulnerability allows any unprivileged user to gain root privileges on the vulnerable host. narrative = A non-privledged user is able to execute the sudoedit command to trigger a buffer overflow. After the successful buffer overflow, they are then able to gain root privileges on the affected host. The conditions needed to be run are a trailing "\" along with shell and edit flags. Monitoring the /var/log directory on Linux hosts using the Splunk Universal Forwarder will allow you to pick up this behavior when using the provided detection. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Brand Monitoring] category = Abuse @@ -199,7 +226,7 @@ version = 1 reference = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] detection_searches = ["ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule"] mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives", "Delivery"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Emails From Specific Sender - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Email Info - Response Task", "ESCU - Get Process Responsible For The DNS Traffic - Response Task"] +investigative_searches = ["ESCU - Get Notable History - Response Task", "ESCU - Get Emails From Specific Sender - Response Task", "ESCU - Get Email Info - Response Task", "ESCU - Get Process Responsible For The DNS Traffic - Response Task"] support_searches = ["ESCU - DNSTwist Domain Names"] data_models = ["Email", "Network_Resolution", "Web"] providing_technologies = none @@ -207,6 +234,7 @@ description = Detect and investigate activity that may indicate that an adversar narrative = While you can educate your users and customers about the risks and threats posed by typosquatting, phishing, and corporate espionage, human error is a persistent fact of life. Of course, your adversaries are all too aware of this reality and will happily leverage it for nefarious purposes whenever possible3phishing with lookalike addresses, embedding faux command-and-control domains in malware, and hosting malicious content on domains that closely mimic your corporate servers. This is where brand monitoring comes in.\ You can use our adaptation of `DNSTwist`, together with the support searches in this Analytic Story, to generate permutations of specified brands and external domains. Splunk can monitor email, DNS requests, and web traffic for these permutations and provide you with early warnings and situational awareness--powerful elements of an effective defense.\ Notable events will include IP addresses, URLs, and user data. Drilling down can provide you with even more actionable intelligence, including likely geographic information, contextual searches to help you scope the problem, and investigative searches. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Clop Ransomware] category = Malware @@ -223,6 +251,7 @@ data_models = ["Endpoint"] providing_technologies = none description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the Clop ransomware, including looking for file writes associated with Clope, encrypting network shares, deleting and resizing shadow volume storage, registry key modification, deleting of security logs, and more. narrative = Clop ransomware campaigns targeting healthcare and other vertical sectors, involve the use of ransomware payloads along with exfiltration of data per HHS bulletin. Malicious actors demand payment for ransome of data and threaten deletion and exposure of exfiltrated data. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Cloud Cryptomining] category = Cloud Security @@ -233,8 +262,8 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High Number Of Cloud Instances Launched - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created In Previously Unused Region - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078.004", "T1535"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get Notable History - Response Task", "ESCU - AWS Investigate Security Hub alerts by dest - Response Task", "ESCU - Investigate AWS activities via region name - Response Task", "ESCU - Get EC2 Launch Details - Response Task", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Get EC2 Instance Details by instanceId - Response Task"] -support_searches = ["ESCU - Previously Seen Cloud Compute Creations By User - Initial", "ESCU - Previously Seen Cloud Compute Images - Update", "ESCU - Previously Seen Cloud Regions - Initial", "ESCU - Previously Seen Cloud Regions - Update", "ESCU - Baseline Of Cloud Instances Launched", "ESCU - Baseline Of Cloud Instances Destroyed", "ESCU - Previously Seen Cloud Compute Instance Types - Initial", "ESCU - Previously Seen Cloud Compute Instance Types - Update", "ESCU - Previously Seen Cloud Compute Images - Initial", "ESCU - Previously Seen Cloud Compute Creations By User - Update"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Investigate AWS activities via region name - Response Task", "ESCU - Get EC2 Launch Details - Response Task", "ESCU - AWS Investigate Security Hub alerts by dest - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get EC2 Instance Details by instanceId - Response Task"] +support_searches = ["ESCU - Previously Seen Cloud Regions - Update", "ESCU - Previously Seen Cloud Compute Instance Types - Initial", "ESCU - Baseline Of Cloud Instances Launched", "ESCU - Previously Seen Cloud Compute Images - Update", "ESCU - Previously Seen Cloud Compute Instance Types - Update", "ESCU - Baseline Of Cloud Instances Destroyed", "ESCU - Previously Seen Cloud Regions - Initial", "ESCU - Previously Seen Cloud Compute Creations By User - Update", "ESCU - Previously Seen Cloud Compute Creations By User - Initial", "ESCU - Previously Seen Cloud Compute Images - Initial"] data_models = ["Change"] providing_technologies = none description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. @@ -242,6 +271,7 @@ narrative = Cryptomining is an intentionally difficult, resource-intensive busin Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Azure. It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ When malicious miners appropriate a cloud instance, often spinning up hundreds of new instances, the costs can become astronomical for the account holder. So it is critically important to monitor your systems for suspicious activities that could indicate that your network has been infiltrated. \ This Analytic Story is focused on detecting suspicious new instances in your cloud environment to help prevent cryptominers from gaining a foothold. It contains detection searches that will detect when a previously unused instance type or AMI is used. It also contains support searches to build lookup files to ensure proper execution of the detection searches. +product = ['Splunk Security Analytics for AWS', 'Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Cloud Federated Credential Abuse] category = Cloud Security @@ -258,6 +288,7 @@ data_models = ["Endpoint"] providing_technologies = none description = This analytical story addresses events that indicate abuse of cloud federated credentials. These credentials are usually extracted from endpoint desktop or servers specially those servers that provide federation services such as Windows Active Directory Federation Services. Identity Federation relies on objects such as Oauth2 tokens, cookies or SAML assertions in order to provide seamless access between cloud and perimeter environments. If these objects are either hijacked or forged then attackers will be able to pivot into victim's cloud environements. narrative = This story is composed of detection searches based on endpoint that addresses the use of Mimikatz, Escalation of Privileges and Abnormal processes that may indicate the extraction of Federated directory objects such as passwords, Oauth2 tokens, certificates and keys. Cloud environment (AWS, Azure) related events are also addressed in specific cloud environment detection searches. +product = ['Splunk Security Analytics for AWS', 'Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Cobalt Strike] category = Adversary Tactics @@ -283,6 +314,7 @@ With that, new detections were generated focused on these spawnto processes spaw - Does the spawnto_ value make network connections?\ - Is it normal for spawnto_ value to load jscript, vbscript, Amsi.dll, and clr.dll?\ While investigating a detection related to this Analytic Story, keep in mind the parent process, process path, and any file modifications that may occur. Tuning may need to occur to remove any false positives. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [ColdRoot MacOS RAT] category = Malware @@ -293,7 +325,7 @@ version = 1 reference = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] detection_searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule"] mappings = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Command and Control", "Installation"], "nist": ["DE.CM", "DE.DP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Network Traffic From src ip - Response Task", "ESCU - Get Notable History - Response Task"] +investigative_searches = ["ESCU - Get Notable History - Response Task", "ESCU - Investigate Network Traffic From src ip - Response Task"] support_searches = [] data_models = [] providing_technologies = none @@ -301,6 +333,7 @@ description = Leverage searches that allow you to detect and investigate unusual narrative = Conventional wisdom holds that Apple's MacOS operating system is significantly less vulnerable to attack than Windows machines. While that point is debatable, it is true that attacks against MacOS systems are much less common. However, this fact does not mean that Macs are impervious to breaches. To the contrary, research has shown that that Mac malware is increasing at an alarming rate. According to AV-test, in 2018, there were 86,865 new MacOS malware variants, up from 27,338 the year before—a 31% increase. In contrast, the independent research firm found that new Windows malware had increased from 65.17M to 76.86M during that same period, less than half the rate of growth. The bottom line is that while the numbers look a lot smaller than Windows, it's definitely time to take Mac security more seriously.\ This Analytic Story addresses the ColdRoot remote access trojan (RAT), which was uploaded to Github in 2016, but was still escaping detection by the first quarter of 2018, when a new, more feature-rich variant was discovered masquerading as an Apple audio driver. Among other capabilities, the Pascal-based ColdRoot can heist passwords from users' keychains and remotely control infected machines without detection. In the initial report of his findings, Patrick Wardle, Chief Research Officer for Digita Security, explained that the new ColdRoot RAT could start and kill processes on the breached system, spawn new remote-desktop sessions, take screen captures and assemble them into a live stream of the victim's desktop, and more.\ Searches in this Analytic Story leverage the capabilities of OSquery to address ColdRoot detection from several different angles, such as looking for the existence of associated files and processes, and monitoring for signs of an installed keylogger. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Collection and Staging] category = Adversary Tactics @@ -311,7 +344,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] detection_searches = ["ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule"] mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1036", "T1114.001", "T1114.002"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Notable History - Response Task"] +investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Parent Process Info - Response Task"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -319,6 +352,7 @@ description = Monitor for and investigate activities--such as suspicious writes narrative = A common adversary goal is to identify and exfiltrate data of value from a target organization. This data may include email conversations and addresses, confidential company information, links to network design/infrastructure, important dates, and so on.\ Attacks are composed of three activities: identification, collection, and staging data for exfiltration. Identification typically involves scanning systems and observing user activity. Collection can involve the transfer of large amounts of data from various repositories. Staging/preparation includes moving data to a central location and compressing (and optionally encoding and/or encrypting) it. All of these activities provide opportunities for defenders to identify their presence. \ Use the searches to detect and monitor suspicious behavior related to these activities. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Command and Control] category = Adversary Tactics @@ -329,13 +363,14 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 1", "CIS 11", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1048", "T1048.003", "T1071.001", "T1071.004", "T1095", "T1189"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get DNS Server History for a host - Response Task", "ESCU - AWS Network Interface details via resourceId - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Process Responsible For The DNS Traffic - Response Task", "ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get DNS traffic ratio - Response Task", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Get Process Information For Port Activity - Response Task", "ESCU - AWS Network ACL Details from ID - Response Task", "ESCU - Get All AWS Activity From IP Address - Response Task"] -support_searches = ["ESCU - Baseline of blocked outbound traffic from AWS", "ESCU - Baseline of DNS Query Length - MLTK"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Get Process Info - Response Task", "ESCU - AWS Network Interface details via resourceId - Response Task", "ESCU - Get DNS Server History for a host - Response Task", "ESCU - Get Process Information For Port Activity - Response Task", "ESCU - Get All AWS Activity From IP Address - Response Task", "ESCU - Get DNS traffic ratio - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Process Responsible For The DNS Traffic - Response Task", "ESCU - AWS Network ACL Details from ID - Response Task", "ESCU - Get Parent Process Info - Response Task"] +support_searches = ["ESCU - Baseline of DNS Query Length - MLTK", "ESCU - Baseline of blocked outbound traffic from AWS"] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. narrative = Threat actors typically architect and implement an infrastructure to use in various ways during the course of their attack campaigns. In some cases, they leverage this infrastructure for scanning and performing reconnaissance activities. In others, they may use this infrastructure to launch actual attacks. One of the most important functions of this infrastructure is to establish servers that will communicate with implants on compromised endpoints. These servers establish a command and control channel that is used to proxy data between the compromised endpoint and the attacker. These channels relay commands from the attacker to the compromised endpoint and the output of those commands back to the attacker.\ Because this communication is so critical for an adversary, they often use techniques designed to hide the true nature of the communications. There are many different techniques used to establish and communicate over these channels. This Analytic Story provides searches that look for a variety of the techniques used for these channels, as well as indications that these channels are active, by examining logs associated with border control devices and network-access control lists. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Common Phishing Frameworks] category = Adversary Tactics @@ -353,6 +388,7 @@ providing_technologies = none description = Detect DNS and web requests to fake websites generated by the EvilGinx2 toolkit. These websites are designed to fool unwitting users who have clicked on a malicious link in a phishing email. narrative = As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Because phishing is a technique that relies on human psychology, you will never be able to eliminate this vulnerability 100%. But you can use automated detection to significantly reduce the risks.\ This Analytic Story focuses on detecting signs of MiTM attacks enabled by [EvilGinx2](https://github.com/kgretzky/evilginx2), a toolkit that sets up a transparent proxy between the targeted site and the user. In this way, the attacker is able to intercept credentials and two-factor identification tokens. It employs a proxy template to allow a registered domain to impersonate targeted sites, such as Linkedin, Amazon, Okta, Github, Twitter, Instagram, Reddit, Office 365, and others. It can even register SSL certificates and camouflage them via a URL shortener, making them difficult to detect. Searches in this story look for signs of MiTM attacks enabled by EvilGinx2. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Container Implantation Monitoring and Investigation] category = Cloud Security @@ -369,6 +405,7 @@ data_models = [] providing_technologies = none description = Use the searches in this story to monitor your Kubernetes registry repositories for upload, and deployment of potentially vulnerable, backdoor, or implanted containers. These searches provide information on source users, destination path, container names and repository names. The searches provide context to address Mitre T1525 which refers to container implantation upload to a company's repository either in Amazon Elastic Container Registry, Google Container Registry and Azure Container Registry. narrative = Container Registrys provide a way for organizations to keep customized images of their development and infrastructure environment in private. However if these repositories are misconfigured or priviledge users credentials are compromise, attackers can potentially upload implanted containers which can be deployed across the organization. These searches allow operator to monitor who, when and what was uploaded to container registry. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Credential Dumping] category = Adversary Tactics @@ -379,7 +416,7 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] detection_searches = ["ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Creation of lsass Dump with Taskmgr - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Dump LSASS via procdump - Rule", "ESCU - Dump LSASS via procdump Rename - Rule", "ESCU - Ntdsutil Export NTDS - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1003.001", "T1003.002", "T1003.003", "T1059.001"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Investigate Pass the Ticket Attempts - Response Task", "ESCU - Investigate Previous Unseen User - Response Task", "ESCU - Investigate Pass the Hash Attempts - Response Task", "ESCU - Investigate Failed Logins for Multiple Destinations - Response Task"] +investigative_searches = ["ESCU - Investigate Pass the Hash Attempts - Response Task", "ESCU - Investigate Previous Unseen User - Response Task", "ESCU - Investigate Failed Logins for Multiple Destinations - Response Task", "ESCU - Investigate Pass the Ticket Attempts - Response Task"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -387,6 +424,7 @@ description = Uncover activity consistent with credential dumping, a technique w narrative = Credential dumping—gathering credentials from a target system, often hashed or encrypted—is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking it offline, on their own systems. The threat actors target a variety of sources to extract them, including the Security Accounts Manager (SAM), Local Security Authority (LSA), NTDS from Domain Controllers, or the Group Policy Preference (GPP) files.\ Once attackers obtain valid credentials, they use them to move throughout a target network with ease, discovering new systems and identifying assets of interest. Credentials obtained in this manner typically include those of privileged users, which may provide access to more sensitive information and system operations.\ The detection searches in this Analytic Story monitor access to the Local Security Authority Subsystem Service (LSASS) process, the usage of shadowcopies for credential dumping and some other techniques for credential dumping. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [DHS Report TA18-074A] category = Malware @@ -397,8 +435,8 @@ version = 2 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] detection_searches = ["ESCU - Create local admin accounts using net exe - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Scheduled Task Deleted Or Created via CMD - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 2", "CIS 3", "CIS 5", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1021.002", "T1053.005", "T1059.001", "T1059.003", "T1071.002", "T1112", "T1136.001", "T1204.002", "T1543.003", "T1547.001", "T1562.004"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.AT", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process File Activity - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Process Information For Port Activity - Response Task"] -support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Previously seen command line arguments"] +investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Process Information For Port Activity - Response Task", "ESCU - Get Process File Activity - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Parent Process Info - Response Task"] +support_searches = ["ESCU - Previously seen command line arguments", "ESCU - Baseline of SMB Traffic - MLTK"] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. @@ -406,6 +444,7 @@ narrative = The frequency of nation-state cyber attacks has increased significan There is a wide range of motivations for these state-sponsored hacks, including stealing valuable corporate, military, or diplomatic dataѿall of which could confer advantages in various arenas. They may also target critical infrastructure. \ One joint Technical Alert (TA) issued by the Department of Homeland and the FBI in mid-March of 2018 attributed some cyber activity targeting utility infrastructure to operatives sponsored by the Russian government. The hackers executed spearfishing attacks, installed malware, employed watering-hole domains, and more. While they caused no physical damage, the attacks provoked fears that a nation-state could turn off water, redirect power, or compromise a nuclear power plant.\ Suspicious activities--spikes in SMB traffic, processes that launch netsh (to modify the network configuration), suspicious registry modifications, and many more--may all be events you may wish to investigate further. While the use of these technique may be an indication that a nation-state actor is attempting to compromise your environment, it is important to note that these techniques are often employed by other groups, as well. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [DNS Amplification Attacks] category = Abuse @@ -423,6 +462,7 @@ providing_technologies = none description = DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to `ANY` queries. This Analytic Story can help you detect attackers who may be abusing your company's DNS infrastructure to launch amplification attacks, causing Denial of Service to other victims. narrative = The Domain Name System (DNS) is the protocol used to map domain names to IP addresses. It has been proven to work very well for its intended function. However if DNS is misconfigured, servers can be abused by attackers to levy amplification or redirection attacks against victims. Because DNS responses to `ANY` queries are so much larger than the queries themselves--and can be made with a UDP packet, which does not require a handshake--attackers can spoof the source address of the packet and cause much more data to be sent to the victim than if they sent the traffic themselves. The `ANY` requests are will be larger than normal DNS server requests, due to the fact that the server provides significant details, such as MX records and associated IP addresses. A large volume of this traffic can result in a DOS on the victim's machine. This misconfiguration leads to two possible victims, the first being the DNS servers participating in an attack and the other being the hosts that are the targets of the DOS attack.\ The search in this story can help you to detect if attackers are abusing your company's DNS infrastructure to launch DNS amplification attacks causing Denial of Service to other victims. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [DNS Hijacking] category = Adversary Tactics @@ -433,7 +473,7 @@ version = 1 reference = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - DNS record changed - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1048.003", "T1071.004", "T1189"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get DNS Server History for a host - Response Task", "ESCU - DNS Hijack Enrichment - Response Task"] +investigative_searches = ["ESCU - DNS Hijack Enrichment - Response Task", "ESCU - Get DNS Server History for a host - Response Task"] support_searches = ["ESCU - Discover DNS records"] data_models = ["Network_Resolution"] providing_technologies = none @@ -447,6 +487,7 @@ On January 22, 2019, the US Department of Homeland Security 2019's Cybersecurity 1. CISA will begin regular delivery of newly added certificates to Certificate Transparency (CT) logs for agency domains via the Cyber Hygiene service. Upon receipt, agencies must immediately begin monitoring CT log data for certificates issued that they did not request. If an agency confirms that a certificate was unauthorized, it must report the certificate to the issuing certificate authority and to CISA. Of course, it makes sense to put equivalent actions in place within your environment, as well. \ In DNS hijacking, the attacker assumes control over an account or makes use of a DNS service exploit to make changes to DNS records. Once they gain access, attackers can substitute their own MX records, name-server records, and addresses, redirecting emails and traffic through their infrastructure, where they can read, copy, or modify information seen. They can also generate valid encryption certificates to help them avoid browser-certificate checks. In one notable attack on the Internet service provider, GoDaddy, the hackers altered Sender Policy Framework (SPF) records a relatively minor change that did not inflict excessive damage but allowed for more effective spam campaigns.\ The searches in this Analytic Story help you detect and investigate activities that may indicate that DNS hijacking has taken place within your environment. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Data Exfiltration] category = Adversary Tactics @@ -463,6 +504,7 @@ data_models = [] providing_technologies = none description = The stealing of data by an adversary. narrative = Exfiltration comes in many flavors. Adversaries can collect data over encrypted or non-encrypted channels. They can utilise Command and Control channels that are already in place to exfiltrate data. They can use both standard data transfer protocols such as FTP, SCP, etc to exfiltrate data. Or they can use non-standard protocols such as DNS, ICMP, etc with specially crafted fields to try and circumvent security technologies in place. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Data Protection] category = Abuse @@ -473,12 +515,13 @@ version = 1 reference = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] detection_searches = ["ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1048.003", "T1189"], "nist": ["DE.AE", "DE.CM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable History - Response Task", "ESCU - Get DNS Server History for a host - Response Task", "ESCU - Get Process Responsible For The DNS Traffic - Response Task", "ESCU - Get Process Info - Response Task", "ESCU - Get DNS traffic ratio - Response Task"] +investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get DNS Server History for a host - Response Task", "ESCU - Get DNS traffic ratio - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Process Responsible For The DNS Traffic - Response Task"] support_searches = [] data_models = ["Change_Analysis", "Network_Resolution"] providing_technologies = none description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. narrative = Attackers can leverage a variety of resources to compromise or exfiltrate enterprise data. Common exfiltration techniques include remote-access channels via low-risk, high-payoff active-collections operations and close-access operations using insiders and removable media. While this Analytic Story is not a comprehensive listing of all the methods by which attackers can exfiltrate data, it provides a useful starting point. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Deobfuscate-Decode Files or Information] category = Adversary Tactics @@ -495,6 +538,7 @@ data_models = ["Endpoint"] providing_technologies = none description = Adversaries may use Obfuscated Files or Information to hide artifacts of an intrusion from analysis. narrative = An example of obfuscated files is `Certutil.exe` usage to encode a portable executable to a certificate file, which is base64 encoded, to hide the originating file. There are many utilities cross-platform to encode using XOR, using compressed .cab files to hide contents and scripting languages that may perform similar native Windows tasks. Triaging an event related will require the capability to review related process events and file modifications. Using a tool such as CyberChef will assist with identifying the encoding that was used, and potentially assist with decoding the contents. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Detect Zerologon Attack] category = Adversary Tactics @@ -511,6 +555,7 @@ data_models = [] providing_technologies = none description = Uncover activity related to the execution of Zerologon CVE-2020-11472, a technique wherein attackers target a Microsoft Windows Domain Controller to reset its computer account password. The result from this attack is attackers can now provide themselves high privileges and take over Domain Controller. The included searches in this Analytic Story are designed to identify attempts to reset Domain Controller Computer Account via exploit code remotely or via the use of tool Mimikatz as payload carrier. narrative = This attack is a privilege escalation technique, where attacker targets a Netlogon secure channel connection to a domain controller, using Netlogon Remote Protocol (MS-NRPC). This vulnerability exposes vulnerable Windows Domain Controllers to be targeted via unaunthenticated RPC calls which eventually reset Domain Contoller computer account ($) providing the attacker the opportunity to exfil domain controller credential secrets and assign themselve high privileges that can lead to domain controller and potentially complete network takeover. The detection searches in this Analytic Story use Windows Event viewer events and Sysmon events to detect attack execution, these searches monitor access to the Local Security Authority Subsystem Service (LSASS) process which is an indicator of the use of Mimikatz tool which has bee updated to carry this attack payload. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Disabling Security Tools] category = Adversary Tactics @@ -521,12 +566,30 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] detection_searches = ["ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Unload Sysmon Filter Driver - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1112", "T1543.003", "T1553.004", "T1562.001", "T1562.004"], "nist": ["DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Notable History - Response Task"] -support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Previously seen command line arguments"] +investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Parent Process Info - Response Task"] +support_searches = ["ESCU - Previously seen command line arguments", "ESCU - Baseline of SMB Traffic - MLTK"] data_models = ["Endpoint"] providing_technologies = none description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. narrative = Attackers employ a variety of tactics in order to avoid detection and operate without barriers. This often involves modifying the configuration of security tools to get around them or explicitly disabling them to prevent them from running. This Analytic Story includes searches that look for activity consistent with attackers attempting to disable various security mechanisms. Such activity may involve monitoring for suspicious registry activity, as this is where much of the configuration for Windows and various other programs reside, or explicitly attempting to shut down security-related services. Other times, attackers attempt various tricks to prevent specific programs from running, such as adding the certificates with which the security tools are signed to a block list (which would prevent them from running). +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] + +[Domain Trust Discovery] +category = Adversary Tactics +creation_date = 2021-03-25 +modification_date = 2021-03-25 +id = e6f30f14-8daf-11eb-a017-acde48001122 +version = 1 +reference = ["https://attack.mitre.org/techniques/T1482/"] +detection_searches = ["ESCU - DSQuery Domain Discovery - Rule", "ESCU - NLTest Domain Trust Discovery - Rule", "ESCU - Windows AdFind Exe - Rule"] +mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1018", "T1482"], "nist": ["DE.CM", "PR.PT"]} +investigative_searches = [] +support_searches = [] +data_models = ["Endpoint"] +providing_technologies = none +description = Adversaries may attempt to gather information on domain trust relationships that may be used to identify lateral movement opportunities in Windows multi-domain/forest environments. +narrative = Domain trusts provide a mechanism for a domain to allow access to resources based on the authentication procedures of another domain. Domain trusts allow the users of the trusted domain to access resources in the trusting domain. The information discovered may help the adversary conduct SID-History Injection, Pass the Ticket, and Kerberoasting. Domain trusts can be enumerated using the DSEnumerateDomainTrusts() Win32 API call, .NET methods, and LDAP. The Windows utility Nltest is known to be used by adversaries to enumerate domain trusts. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Dynamic DNS] category = Malware @@ -537,12 +600,13 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1071.001", "T1189"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable History - Response Task", "ESCU - Get DNS traffic ratio - Response Task", "ESCU - Get DNS Server History for a host - Response Task", "ESCU - Get Process Responsible For The DNS Traffic - Response Task"] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic - Response Task", "ESCU - Get DNS traffic ratio - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get DNS Server History for a host - Response Task"] support_searches = [] data_models = ["Network_Resolution", "Web"] providing_technologies = none description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and deny lists. narrative = Dynamic DNS services (DDNS) are legitimate low-cost or free services that allow users to rapidly update domain resolutions to IP infrastructure. While their usage can be benign, malicious actors can abuse DDNS to host harmful payloads or interactive-command-and-control infrastructure. These attackers will manually update or automate domain resolution changes by routing dynamic domains to IP addresses that circumvent firewall blocks and deny lists and frustrate a network defender's analytic and investigative processes. These searches will look for DNS queries made from within your infrastructure to suspicious dynamic domains and then investigate more deeply, when appropriate. While this list of top-level dynamic domains is not exhaustive, it can be dynamically updated as new suspicious dynamic domains are identified. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Emotet Malware DHS Report TA18-201A ] category = Malware @@ -553,7 +617,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 2", "CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Exploitation", "Installation"], "mitre_attack": ["T1021.002", "T1059.003", "T1072", "T1547.001", "T1566.001"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get History Of Email Sources - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Process Information For Port Activity - Response Task"] +investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Process Information For Port Activity - Response Task", "ESCU - Get History Of Email Sources - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Parent Process Info - Response Task"] support_searches = ["ESCU - Baseline of SMB Traffic - MLTK"] data_models = ["Email", "Endpoint", "Network_Traffic"] providing_technologies = none @@ -561,6 +625,7 @@ description = Detect rarely used executables, specific registry paths that may c narrative = The trojan downloader known as Emotet first surfaced in 2014, when it was discovered targeting the banking industry to steal credentials. However, according to a joint technical alert (TA) issued by three government agencies (https://www.us-cert.gov/ncas/alerts/TA18-201A), Emotet has evolved far beyond those beginnings to become what a ThreatPost article called a threat-delivery service(see https://threatpost.com/emotet-malware-evolves-beyond-banking-to-threat-delivery-service/134342/). For example, in early 2018, Emotet was found to be using its loader function to spread the Quakbot and Ransomware variants. \ According to the TA, the the malware continues to be among the most costly and destructive malware affecting the private and public sectors. Researchers have linked it to the threat group Mealybug, which has also been on the security communitys radar since 2014.\ The searches in this Analytic Story will help you find executables that are rarely used in your environment, specific registry paths that malware often uses to ensure survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that Emotet or other malware has compromised your environment. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [F5 TMUI RCE CVE-2020-5902] category = Adversary Tactics @@ -577,6 +642,7 @@ data_models = [] providing_technologies = none description = Uncover activity consistent with CVE-2020-5902. Discovered by Positive Technologies researchers, this vulnerability affects F5 BIG-IP, BIG-IQ. and Traffix SDC devices (vulnerable versions in F5 support link below). This vulnerability allows unauthenticated users, along with authenticated users, who have access to the configuration utility to execute system commands, create/delete files, disable services, and/or execute Java code. This vulnerability can result in full system compromise. narrative = A client is able to perform a remote code execution on an exposed and vulnerable system. The detection search in this Analytic Story uses syslog to detect the malicious behavior. Syslog is going to be the best detection method, as any systems using SSL to protect their management console will make detection via wire data difficult. The searches included used Splunk Connect For Syslog (https://splunkbase.splunk.com/app/4740/), and used a custom destination port to help define the data as F5 data (covered in https://splunk-connect-for-syslog.readthedocs.io/en/master/sources/F5/) +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [GCP Cross Account Activity] category = Cloud Security @@ -595,6 +661,7 @@ description = Track when a user assumes an IAM role in another GCP account to ob narrative = Google Cloud Platform (GCP) admins manage access to GCP resources and services across the enterprise using GCP Identity and Access Management (IAM) functionality. IAM provides the ability to create and manage GCP users, groups, and roles-each with their own unique set of privileges and defined access to specific resources (such as Compute instances, the GCP Management Console, API, or the command-line interface). Unlike conventional (human) users, IAM roles are potentially assumable by anyone in the organization. They provide users with dynamically created temporary security credentials that expire within a set time period.\ In between the time between when the temporary credentials are issued and when they expire is a period of opportunity, where a user could leverage the temporary credentials to wreak havoc-spin up or remove instances, create new users, elevate privileges, and other malicious activities-throughout the environment.\ This Analytic Story includes searches that will help you monitor your GCP Audit logs logs for evidence of suspicious cross-account activity. For example, while accessing multiple GCP accounts and roles may be perfectly valid behavior, it may be suspicious when an account requests privileges of an account it has not accessed in the past. After identifying suspicious activities, you can use the provided investigative searches to help you probe more deeply. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [HAFNIUM Group] category = Adversary Tactics @@ -613,6 +680,7 @@ description = HAFNIUM group was identified by Microsoft as exploiting 4 Microsof narrative = On Tuesday, March 2, 2021, Microsoft released a set of security patches for its mail server, Microsoft Exchange. These patches respond to a group of vulnerabilities known to impact Exchange 2013, 2016, and 2019. It is important to note that an Exchange 2010 security update has also been issued, though the CVEs do not reference that version as being vulnerable.\ While the CVEs do not shed much light on the specifics of the vulnerabilities or exploits, the first vulnerability (CVE-2021-26855) has a remote network attack vector that allows the attacker, a group Microsoft named HAFNIUM, to authenticate as the Exchange server. Three additional vulnerabilities (CVE-2021-26857, CVE-2021-26858, and CVE-2021-27065) were also identified as part of this activity. When chained together along with CVE-2021-26855 for initial access, the attacker would have complete control over the Exchange server. This includes the ability to run code as SYSTEM and write to any path on the server.\ The following Splunk detections assist with identifying the HAFNIUM groups tradecraft and methodology. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Hidden Cobra Malware] category = Malware @@ -623,8 +691,8 @@ version = 2 reference = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] detection_searches = ["ESCU - Create or delete windows shares using net exe - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious File Write - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1021.001", "T1021.002", "T1048.003", "T1059.001", "T1059.003", "T1070.005", "T1071.002", "T1071.004"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get History Of Email Sources - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get DNS Server History for a host - Response Task", "ESCU - Get Process Responsible For The DNS Traffic - Response Task", "ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get DNS traffic ratio - Response Task", "ESCU - Get Process Information For Port Activity - Response Task", "ESCU - Get Outbound Emails to Hidden Cobra Threat Actors - Response Task", "ESCU - Investigate Successful Remote Desktop Authentications - Response Task"] -support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Baseline of DNS Query Length - MLTK", "ESCU - Previously seen command line arguments"] +investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get DNS Server History for a host - Response Task", "ESCU - Get Process Information For Port Activity - Response Task", "ESCU - Get History Of Email Sources - Response Task", "ESCU - Get DNS traffic ratio - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Process Responsible For The DNS Traffic - Response Task", "ESCU - Investigate Successful Remote Desktop Authentications - Response Task", "ESCU - Get Outbound Emails to Hidden Cobra Threat Actors - Response Task", "ESCU - Get Parent Process Info - Response Task"] +support_searches = ["ESCU - Baseline of DNS Query Length - MLTK", "ESCU - Previously seen command line arguments", "ESCU - Baseline of SMB Traffic - MLTK"] data_models = ["Endpoint", "Network_Resolution", "Network_Traffic"] providing_technologies = none description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. @@ -632,6 +700,7 @@ narrative = North Korea's government-sponsored "cyber army" has been slowly buil These state-sponsored actors are thought to be responsible for everything from a hack on a South Korean nuclear plant to an attack on Sony in anticipation of its release of the movie "The Interview" at the end of 2014. They're also notorious for cyberespionage. In recent years, the group seems to be focused on financial crimes, such as cryptojacking.\ In June of 2018, The Department of Homeland Security, together with the FBI and other U.S. government partners, issued Technical Alert (TA-18-149A) to advise the public about two variants of North Korean malware. One variant, dubbed "Joanap," is a multi-stage peer-to-peer botnet that allows North Korean state actors to exfiltrate data, download and execute secondary payloads, and initialize proxy communications. The other variant, "Brambul," is a Windows32 SMB worm that is dropped into a victim network. When executed, the malware attempts to spread laterally within a victim's local subnet, connecting via the SMB protocol and initiating brute-force password attacks. It reports details to the Hidden Cobra actors via email, so they can use the information for secondary remote operations.\ Among other searches in this Analytic Story is a detection search that looks for the creation or deletion of hidden shares, such as, "adnim$," which the Hidden Cobra malware creates on the target system. Another looks for the creation of three malicious files associated with the malware. You can also use a search in this story to investigate activity that indicates that malware is sending email back to the attackers. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Host Redirection] category = Abuse @@ -648,6 +717,7 @@ data_models = ["Network_Resolution"] providing_technologies = none description = Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. narrative = Attackers will often attempt to manipulate client communications for nefarious purposes. In some cases, an attacker may endeavor to modify a local host file to redirect communications with resources (such as antivirus or system-update services) to prevent clients from receiving patches or updates. In other cases, an attacker might use this tactic to have the client connect to a site that looks like the intended site, but instead installs malware or collects information from the victim. Additionally, an attacker may redirect a victim in order to execute a MITM attack and observe communications. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Ingress Tool Transfer] category = Adversary Tactics @@ -656,14 +726,15 @@ modification_date = 2021-03-24 id = b3782036-8cbd-11eb-9d8e-acde48001122 version = 1 reference = ["https://attack.mitre.org/techniques/T1105/"] -detection_searches = ["ESCU - CertUtil Download With URLCache and Split Arguments - Rule", "ESCU - CertUtil Download With VerifyCtl and Split Arguments - Rule", "ESCU - Suspicious Curl Network Connection - Rule"] -mappings = {"kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1105"]} +detection_searches = ["ESCU - Any Powershell DownloadFile - Rule", "ESCU - Any Powershell DownloadString - Rule", "ESCU - BITSAdmin Download File - Rule", "ESCU - CertUtil Download With URLCache and Split Arguments - Rule", "ESCU - CertUtil Download With VerifyCtl and Split Arguments - Rule", "ESCU - Suspicious Curl Network Connection - Rule"] +mappings = {"kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1059.001", "T1105", "T1197"]} investigative_searches = [] support_searches = [] data_models = ["Endpoint"] providing_technologies = none description = Adversaries may transfer tools or other files from an external system into a compromised environment. Files may be copied from an external adversary controlled system through the command and control channel to bring tools into the victim network or through alternate protocols with another tool such as FTP. narrative = Ingress tool transfer is a Technique under tactic Command and Control. Behaviors will include the use of living off the land binaries to download implants or binaries over alternate communication ports. It is imperative to baseline applications on endpoints to understand what generates network activity, to where, and what is its native behavior. These utilities, when abused, will write files to disk in world writeable paths.\ During triage, review the reputation of the remote public destination IP or domain. Capture any files written to disk and perform analysis. Review other parrallel processes for additional behaviors. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [JBoss Vulnerability] category = Vulnerability @@ -694,6 +765,7 @@ If you suspect an attack targeting a web server, it is helpful to look at some o If a suspicious file is found, we can review more information about it to help determine if it is, in fact, malicious. Identifying the file type, any processes that opened the file, the processes that may have created and/or modified the file, and how many other systems potentially have this file can you determine whether the file is malicious. Also, determining the file hash and checking it against reputation sources, such as VirusTotal, can sometimes help you quickly determine if it is malicious in nature.\ Often, a simple inspection of a suspect process name and path can tell you if the system has been compromised. For example, if svchost.exe is found running from a location other than `C:\Windows\System32`, it is likely something malicious designed to hide in plain sight when simply reviewing process names. \ It can also be helpful to examine various behaviors of and the parent of the process of interest. For example, if it turns out the process of interest is malicious, it would be good to see whether the parent process spawned other processes that might also warrant further scrutiny. If a process is suspect, a review of the network connections made around the time of the event and noting whether the process has spawned any child processes could be helpful in determining whether it is malicious or executing a malicious script. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Kubernetes Scanning Activity] category = Cloud Security @@ -704,12 +776,13 @@ version = 1 reference = ["https://github.com/splunk/cloud-datamodel-security-research"] detection_searches = ["ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes cluster pod scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Kubernetes Azure pod scan fingerprint - Rule", "ESCU - Kubernetes Azure scan fingerprint - Rule"] mappings = {"kill_chain_phases": ["Reconnaissance"], "mitre_attack": ["T1526"]} -investigative_searches = ["ESCU - Get Notable History - Response Task", "ESCU - Amazon EKS Kubernetes activity by src ip - Response Task", "ESCU - GCP Kubernetes activity by src ip - Response Task"] +investigative_searches = ["ESCU - GCP Kubernetes activity by src ip - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Amazon EKS Kubernetes activity by src ip - Response Task"] support_searches = [] data_models = [] providing_technologies = none description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. narrative = Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitve information and management priviledges of production workloads, microservices and applications. These searches allow operator to detect suspicious unauthenticated requests from the internet to kubernetes cluster. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Kubernetes Sensitive Object Access Activity] category = Cloud Security @@ -726,6 +799,7 @@ data_models = [] providing_technologies = none description = This story addresses detection and response of accounts acccesing Kubernetes cluster sensitive objects such as configmaps or secrets providing information on items such as user user, group. object, namespace and authorization reason. narrative = Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitive objects within its architecture, specifically configmaps and secrets, if accessed by an attacker can lead to further compromise. These searches allow operator to detect suspicious requests against Kubernetes sensitive objects. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Kubernetes Sensitive Role Activity] category = Cloud Security @@ -742,6 +816,7 @@ data_models = [] providing_technologies = none description = This story addresses detection and response around Sensitive Role usage within a Kubernetes clusters against cluster resources and namespaces. narrative = Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitive roles within its architecture, specifically configmaps and secrets, if accessed by an attacker can lead to further compromise. These searches allow operator to detect suspicious requests against Kubernetes role activities +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Lateral Movement] category = Adversary Tactics @@ -752,7 +827,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] detection_searches = ["ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Kerberoasting spn request with RC4 encryption - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Schtasks scheduling job on remote system - Rule"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1021.001", "T1053.005", "T1550.002", "T1558.003"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get History Of Email Sources - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Process Information For Port Activity - Response Task", "ESCU - Investigate Successful Remote Desktop Authentications - Response Task"] +investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Process Information For Port Activity - Response Task", "ESCU - Get History Of Email Sources - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Investigate Successful Remote Desktop Authentications - Response Task", "ESCU - Get Parent Process Info - Response Task"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -762,6 +837,7 @@ Indications of lateral movement can include the abuse of system utilities (such An adversary can use lateral movement for multiple purposes, including remote execution of tools, pivoting to additional systems, obtaining access to specific information or files, access to additional credentials, exfiltrating data, or delivering a secondary effect. Adversaries may use legitimate credentials alongside inherent network and operating-system functionality to remotely connect to other systems and remain under the radar of network defenders.\ If there is evidence of lateral movement, it is imperative for analysts to collect evidence of the associated offending hosts. For example, an attacker might leverage host A to gain access to host B. From there, the attacker may try to move laterally to host C. In this example, the analyst should gather as much information as possible from all three hosts. \ It is also important to collect authentication logs for each host, to ensure that the offending accounts are well-documented. Analysts should account for all processes to ensure that the attackers did not install unauthorized software. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Malicious PowerShell] category = Adversary Tactics @@ -772,7 +848,7 @@ version = 4 reference = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["ESCU - Any Powershell DownloadFile - Rule", "ESCU - Any Powershell DownloadString - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Exploitation", "Installation"], "mitre_attack": ["T1027", "T1059.001"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get History Of Email Sources - Response Task", "ESCU - Get Notable History - Response Task"] +investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get History Of Email Sources - Response Task", "ESCU - Get Parent Process Info - Response Task"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -787,6 +863,7 @@ Gathering data on the system of interest can sometimes help you quickly determin Often, a simple inspection of the process name and path can tell you if the system has been compromised. For example, if `svchost.exe` is found running from a location other than `C:\Windows\System32`, it is likely something malicious designed to hide in plain sight when cursorily reviewing process names. Similarly, if the process itself seems legitimate, but the parent process is running from the temporary browser cache, that could be indicative of activity initiated via a compromised website a user visited.\ It can also be very helpful to examine various behaviors of the process of interest or the parent of the process of interest. For example, if it turns out the process of interest is malicious, it would be good to see if the parent to that process spawned other processes that might be worth further scrutiny. If a process is suspect, a review of the network connections made in and around the time of the event and/or whether the process spawned any child processes could be helpful, as well.\ In the event a system is suspected of having been compromised via a malicious website, we suggest reviewing the browsing activity from that system around the time of the event. If categories are given for the URLs visited, that can help you zero in on possible malicious sites. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Monitor Backup Solution] category = Best Practices @@ -798,11 +875,12 @@ reference = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-u detection_searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule"] mappings = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} investigative_searches = ["ESCU - Get Notable History - Response Task", "ESCU - All backup logs for host - Response Task"] -support_searches = ["ESCU - Monitor Unsuccessful Backups", "ESCU - Monitor Successful Backups"] +support_searches = ["ESCU - Monitor Successful Backups", "ESCU - Monitor Unsuccessful Backups"] data_models = [] providing_technologies = none description = Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. narrative = Having backups is a standard best practice that helps ensure continuity of business operations. Having mature backup processes can also help you reduce the risks of many security-related incidents and streamline your response processes. The detection searches in this Analytic Story will help you identify systems that have backup failures, as well as systems that have not been backed up for an extended period of time. The story will also return the notable event history and all of the backup logs for an endpoint. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Monitor for Unauthorized Software] category = Best Practices @@ -813,13 +891,14 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["ESCU - Prohibited Software On Endpoint - Rule"] mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "nist": ["ID.AM", "PR.DS"]} -investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Notable History - Response Task"] +investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Parent Process Info - Response Task"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none description = Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. narrative = It is critical to identify unauthorized software and processes running on enterprise endpoints and determine whether they are likely to be malicious. This Analytic Story requires the user to populate the Interesting Processes table within Enterprise Security with prohibited processes. An included support search will augment this data, adding information on processes thought to be malicious. This search requires data from endpoint detection-and-response solutions, endpoint data sources (such as Sysmon), or Windows Event Logs--assuming that the Active Directory administrator has enabled process tracking within the System Event Audit Logs.\ It is important to investigate any software identified as suspicious, in order to understand how it was installed or executed. Analyzing authentication logs or any historic notable events might elicit additional investigative leads of interest. For best results, schedule the search to run every two weeks. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Monitor for Updates] category = Best Practices @@ -838,6 +917,7 @@ description = Monitor your enterprise to ensure that your endpoints are being pa narrative = It is a common best practice to ensure that endpoints are being patched and updated in a timely manner, in order to reduce the risk of compromise via a publicly disclosed vulnerability. Timely application of updates/patches is important to eliminate known vulnerabilities that may be exploited by various threat actors.\ Searches in this analytic story are designed to help analysts monitor endpoints for system patches and/or updates. This helps analysts identify any systems that are not successfully updated in a timely matter.\ Microsoft releases updates for Windows systems on a monthly cadence. They should be installed as soon as possible after following internal testing and validation procedures. Patches and updates for other systems or applications are typically released as needed. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [NOBELIUM Group] category = Adversary Tactics @@ -849,11 +929,12 @@ reference = ["https://www.microsoft.com/security/blog/2021/03/04/goldmax-goldfin detection_searches = ["ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect Rundll32 Inline HTA Execution - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Scheduled Task Deleted Or Created via CMD - Rule", "ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Sunburst Correlation DLL and Network Event - Rule", "ESCU - Supernova Webshell - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Windows AdFind Exe - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 18", "CIS 2", "CIS 3", "CIS 4", "CIS 5", "CIS 6", "CIS 7", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Exfiltration", "Exploitation", "Installation"], "mitre_attack": ["T1018", "T1027", "T1053.005", "T1059.003", "T1071.001", "T1071.002", "T1203", "T1218.005", "T1505.003", "T1543.003", "T1569.002"], "nist": ["DE.AE", "DE.CM", "ID.AM", "ID.RA", "PR.AC", "PR.AT", "PR.DS", "PR.IP", "PR.PT"]} investigative_searches = [] -support_searches = ["ESCU - Previously Seen Running Windows Services - Initial", "ESCU - Previously Seen Running Windows Services - Update"] +support_searches = ["ESCU - Previously Seen Running Windows Services - Update", "ESCU - Previously Seen Running Windows Services - Initial"] data_models = ["Endpoint", "Network_Traffic", "Web"] providing_technologies = none description = Sunburst is a trojanized updates to SolarWinds Orion IT monitoring and management software. It was discovered by FireEye in December 2020. The actors behind this campaign gained access to numerous public and private organizations around the world. narrative = This Analytic Story supports you to detect Tactics, Techniques and Procedures (TTPs) of the NOBELIUM Group. The threat actor behind sunburst compromised the SolarWinds.Orion.Core.BusinessLayer.dll, is a SolarWinds digitally-signed component of the Orion software framework that contains a backdoor that communicates via HTTP to third party servers. The detections in this Analytic Story are focusing on the dll loading events, file create events and network events to detect This malware. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Netsh Abuse] category = Abuse @@ -864,13 +945,14 @@ version = 1 reference = ["https://docs.microsoft.com/en-us/previous-versions/tn-archive/bb490939(v=technet.10)", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] detection_searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1562.004"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Notable History - Response Task"] -support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Previously seen command line arguments"] +investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Parent Process Info - Response Task"] +support_searches = ["ESCU - Previously seen command line arguments", "ESCU - Baseline of SMB Traffic - MLTK"] data_models = ["Endpoint"] providing_technologies = none description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. narrative = It is a common practice for attackers of all types to leverage native Windows tools and functionality to execute commands for malicious reasons. One such tool on Windows OS is `netsh.exe`,a command-line scripting utility that allows you to--either locally or remotely--display or modify the network configuration of a computer that is currently running. `Netsh.exe` can be used to discover and disable local firewall settings. It can also be used to set up a remote connection to a host from an infected system.\ To get started, run the detection search to identify parent processes of `netsh.exe`. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Office 365 Detections] category = Cloud Security @@ -887,6 +969,7 @@ data_models = [] providing_technologies = none description = This story is focused around detecting Office 365 Attacks. narrative = More and more companies are using Microsofts Office 365 cloud offering. Therefore, we see more and more attacks against Office 365. This story provides various detections for Office 365 attacks. +product = ['Splunk Security Analytics for AWS', 'Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Orangeworm Attack Group] category = Malware @@ -897,8 +980,8 @@ version = 2 reference = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 2", "CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1059.001", "T1059.003", "T1543.003", "T1569.002"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.AT", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get History Of Email Sources - Response Task", "ESCU - Get Notable History - Response Task"] -support_searches = ["ESCU - Previously Seen Running Windows Services - Initial", "ESCU - Previously Seen Running Windows Services - Update", "ESCU - Previously seen command line arguments"] +investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get History Of Email Sources - Response Task", "ESCU - Get Parent Process Info - Response Task"] +support_searches = ["ESCU - Previously seen command line arguments", "ESCU - Previously Seen Running Windows Services - Update", "ESCU - Previously Seen Running Windows Services - Initial"] data_models = ["Endpoint"] providing_technologies = none description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. @@ -906,6 +989,7 @@ narrative = In May of 2018, the attack group Orangeworm was implicated for insta Awareness of the Orangeworm group first surfaced in January, 2015. It has conducted targeted attacks against related industries, as well, such as pharmaceuticals and healthcare IT solution providers.\ Healthcare may be a promising target, because it is notoriously behind in technology, often using older operating systems and neglecting to patch computers. Even so, the group was able to evade detection for a full three years. Sources say that the malware spread quickly within the target networks, infecting computers used to control medical devices, such as MRI and X-ray machines.\ This Analytic Story is designed to help you detect and investigate suspicious activities that may be indicative of an Orangeworm attack. One detection search looks for command-line arguments. Another monitors for uses of sc.exe, a non-essential Windows file that can manipulate Windows services. One of the investigative searches helps you get more information on web hosts that you suspect have been compromised. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Phishing Payloads] category = Adversary Tactics @@ -929,6 +1013,7 @@ Following is a typical series of events, according to an [article by Trend Micro 1. The .lnk file executes a PowerShell script\ 1. Powershell executes a reverse shell, rendering the exploit successful As a side note, adversaries are likely to use a tool like Empire to craft and obfuscate payloads and their post-injection activities, such as [exfiltration, lateral movement, and persistence](https://github.com/EmpireProject/Empire).\ This Analytic Story focuses on detecting signs that a malicious payload has been injected into your environment. For example, one search detects outlook.exe writing a .zip file. Another looks for suspicious .lnk files launching processes. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns] category = Adversary Tactics @@ -939,8 +1024,8 @@ version = 1 reference = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] detection_searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1059.001", "T1059.003", "T1547.001"], "nist": ["DE.AE", "DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get History Of Email Sources - Response Task", "ESCU - Get Notable History - Response Task"] -support_searches = ["ESCU - Baseline of Command Line Length - MLTK", "ESCU - Previously seen command line arguments"] +investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get History Of Email Sources - Response Task", "ESCU - Get Parent Process Info - Response Task"] +support_searches = ["ESCU - Previously seen command line arguments", "ESCU - Baseline of Command Line Length - MLTK"] data_models = ["Endpoint"] providing_technologies = none description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. @@ -972,6 +1057,7 @@ If behavioral searches included in this story yield positive hits, iDefense reco 1. 889a9b52566448231f112a5ce9b5dfaf\ 1. b8ec65dab97cdef3cd256cc4753f0c54\ 1. 04d83cd3813698de28cfbba326d7647c +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Prohibited Traffic Allowed or Protocol Mismatch] category = Best Practices @@ -982,12 +1068,13 @@ version = 1 reference = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1048", "T1048.003", "T1071.001", "T1189"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable History - Response Task", "ESCU - Get DNS Server History for a host - Response Task", "ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Process Information For Port Activity - Response Task"] +investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Process Information For Port Activity - Response Task", "ESCU - Get DNS Server History for a host - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Parent Process Info - Response Task"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. narrative = A traditional security best practice is to control the ports, protocols, and services allowed within your environment. By limiting the services and protocols to those explicitly approved by policy, administrators can minimize the attack surface. The combined effect allows both network defenders and security controls to focus and not be mired in superfluous traffic or data types. Looking for deviations to policy can identify attacker activity that abuses services and protocols to run on alternate or non-standard ports in the attempt to avoid detection or frustrate forensic analysts. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Ransomware] category = Malware @@ -998,12 +1085,13 @@ version = 1 reference = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] detection_searches = ["ESCU - BCDEdit Failure Recovery Modification - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Suspicious Scheduled Task from Public Directory - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - TOR Traffic - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - WBAdmin Delete System Backups - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 3", "CIS 5", "CIS 6", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Exploitation", "Privilege Escalation"], "mitre_attack": ["T1021.002", "T1036.003", "T1047", "T1048", "T1053.005", "T1070", "T1070.001", "T1071.001", "T1485", "T1490", "T1547.001"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get History Of Email Sources - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Sysmon WMI Activity for Host - Response Task", "ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Process Information For Port Activity - Response Task", "ESCU - Get Backup Logs For Endpoint - Response Task"] -support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Baseline of Command Line Length - MLTK"] +investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Process Information For Port Activity - Response Task", "ESCU - Get Sysmon WMI Activity for Host - Response Task", "ESCU - Get Backup Logs For Endpoint - Response Task", "ESCU - Get History Of Email Sources - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Parent Process Info - Response Task"] +support_searches = ["ESCU - Baseline of Command Line Length - MLTK", "ESCU - Baseline of SMB Traffic - MLTK"] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. narrative = Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise. Attackers can deploy ransomware to enterprises through spearphishing campaigns and driveby downloads, as well as through traditional remote service-based exploitation. In the case of the WannaCry campaign, there was self-propagating wormable functionality that was used to maximize infection. Fortunately, organizations can apply several techniques--such as those in this Analytic Story--to detect and or mitigate the effects of ransomware. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Ransomware Cloud] category = Malware @@ -1020,6 +1108,7 @@ data_models = [] providing_technologies = none description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware. These searches include cloud related objects that may be targeted by malicious actors via cloud providers own encryption features. narrative = Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise.Cloud ransomware can be deployed by obtaining high privilege credentials from targeted users or resources. +product = ['Splunk Security Analytics for AWS', 'Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Router and Infrastructure Security] category = Best Practices @@ -1037,6 +1126,7 @@ providing_technologies = none description = Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. narrative = Networking devices, such as routers and switches, are often overlooked as resources that attackers will leverage to subvert an enterprise. Advanced threats actors have shown a proclivity to target these critical assets as a means to siphon and redirect network traffic, flash backdoored operating systems, and implement cryptographic weakened algorithms to more easily decrypt network traffic.\ This Analytic Story helps you gain a better understanding of how your network devices are interacting with your hosts. By compromising your network devices, attackers can obtain direct access to the company's internal infrastructure— effectively increasing the attack surface and accessing private services/data. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Ryuk Ransomware] category = Malware @@ -1053,6 +1143,7 @@ data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the Ryuk ransomware, including looking for file writes associated with Ryuk, Stopping Security Access Manager, DisableAntiSpyware registry key modification, suspicious psexec use, and more. narrative = Cybersecurity Infrastructure Security Agency (CISA) released Alert (AA20-302A) on October 28th called “Ransomware Activity Targeting the Healthcare and Public Health Sector.” This alert details TTPs associated with ongoing and possible imminent attacks against the Healthcare sector, and is a joint advisory in coordination with other U.S. Government agencies. The objective of these malicious campaigns is to infiltrate targets in named sectors and to drop ransomware payloads, which will likely cause disruption of service and increase risk of actual harm to the health and safety of patients at hospitals, even with the aggravant of an ongoing COVID-19 pandemic. This document specifically refers to several crimeware exploitation frameworks, emphasizing the use of Ryuk ransomware as payload. The Ryuk ransomware payload is not new. It has been well documented and identified in multiple variants. Payloads need a carrier, and for Ryuk it has often been exploitation frameworks such as Cobalt Strike, or popular crimeware frameworks such as Emotet or Trickbot. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [SQL Injection] category = Adversary Tactics @@ -1070,6 +1161,7 @@ providing_technologies = none description = Use the searches in this Analytic Story to help you detect structured query language (SQL) injection attempts characterized by long URLs that contain malicious parameters. narrative = It is very common for attackers to inject SQL parameters into vulnerable web applications, which then interpret the malicious SQL statements.\ This Analytic Story contains a search designed to identify attempts by attackers to leverage this technique to compromise a host and gain a foothold in the target environment. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [SamSam Ransomware] category = Malware @@ -1080,7 +1172,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] detection_searches = ["ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Spike in File Writes - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 16", "CIS 18", "CIS 2", "CIS 3", "CIS 4", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Installation", "Reconnaissance"], "mitre_attack": ["T1021.001", "T1021.002", "T1082", "T1204.002", "T1485", "T1486", "T1490"], "nist": ["DE.AE", "DE.CM", "ID.AM", "ID.RA", "PR.AC", "PR.DS", "PR.IP", "PR.MA", "PR.PT"]} -investigative_searches = ["ESCU - Get History Of Email Sources - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Process Information For Port Activity - Response Task", "ESCU - Get Backup Logs For Endpoint - Response Task", "ESCU - Investigate Successful Remote Desktop Authentications - Response Task"] +investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Process Information For Port Activity - Response Task", "ESCU - Get Backup Logs For Endpoint - Response Task", "ESCU - Get History Of Email Sources - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Investigate Successful Remote Desktop Authentications - Response Task", "ESCU - Get Parent Process Info - Response Task"] support_searches = [] data_models = ["Endpoint", "Network_Traffic", "Web"] providing_technologies = none @@ -1091,6 +1183,7 @@ SamSam attacks are different beasts. They have become progressively more targete In a typical attack on one large healthcare organization in 2018, the company ended up paying a ransom of four Bitcoins, then worth $56,707. Reports showed that access to the company's files was restored within two hours of paying the sum.\ According to Sophos, SamSam previously leveraged RDP to gain access to targeted networks via brute force. SamSam is not spread automatically, like other malware. It requires skill because it forces the attacker to adapt their tactics to the individual environment. Next, the actors escalate their privileges to admin level. They scan the networks for worthy targets, using conventional tools, such as PsExec or PaExec, to deploy/execute, quickly encrypting files.\ This Analytic Story includes searches designed to help detect and investigate signs of the SamSam ransomware, such as the creation of fileswrites to system32, writes with tell-tale extensions, batch files written to system32, and evidence of brute-force attacks via RDP. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Silver Sparrow] category = Adversary Tactics @@ -1107,6 +1200,7 @@ data_models = ["Endpoint"] providing_technologies = none description = Silver Sparrow, identified by Red Canary Intelligence, is a new forward looking MacOS (Intel and M1) malicious software downloader utilizing JavaScript for execution and a launchAgent to establish persistence. narrative = Silver Sparrow works is a dropper and uses typical persistence mechanisms on a Mac. It is cross platform, covering both Intel and Apple M1 architecture. To this date, no implant has been downloaded for malicious purposes. During installation of the update.pkg or updater.pkg file, the malicious software utilizes JavaScript to generate files and scripts on disk for persistence.These files later download a implant from an S3 bucket every hour. This analytic assists with identifying different types of macOS malware families establishing LaunchAgent persistence. Per SentinelOne source, it is predicted that Silver Sparrow is likely selling itself as a mechanism to 3rd party “affiliates” or pay-per-install (PPI) partners, typically seen as commodity adware/malware. Additional indicators and behaviors may be found within the references. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Spectre And Meltdown Vulnerabilities] category = Vulnerability @@ -1123,6 +1217,7 @@ data_models = ["Vulnerabilities"] providing_technologies = none description = Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. narrative = Meltdown and Spectre exploit critical vulnerabilities in modern CPUs that allow unintended access to data in memory. This Analytic Story will help you identify the systems can be patched for these vulnerabilities, as well as those that still need to be patched. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Splunk Enterprise Vulnerability] category = Vulnerability @@ -1148,6 +1243,7 @@ narrative = This Analytic Story is associated with CVE-2016-4859, an open-redire 1. Splunk Enterprise 5.0.x, prior to 5.0.16\ 1. Splunk Light, prior to 6.4.3CVE-2016-4859 allows attackers to redirect users to arbitrary web sites and conduct phishing attacks via unspecified vectors. (Credit: Noriaki Iwasaki, Cyber Defense Institute, Inc.).\ It is important to ensure that your Splunk deployment is being kept up to date and is properly configured. This detection search allows analysts to monitor internal logs to ensure users are properly authenticated and cannot be redirected to any malicious third-party websites. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Splunk Enterprise Vulnerability CVE-2018-11409] category = Vulnerability @@ -1158,7 +1254,7 @@ version = 1 reference = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] detection_searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule"] mappings = {"cis20": ["CIS 18", "CIS 3", "CIS 4"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM", "ID.RA", "PR.AC", "PR.IP", "PR.PT", "RS.MI"]} -investigative_searches = ["ESCU - Investigate Network Traffic From src ip - Response Task", "ESCU - Get Notable History - Response Task"] +investigative_searches = ["ESCU - Get Notable History - Response Task", "ESCU - Investigate Network Traffic From src ip - Response Task"] support_searches = [] data_models = [] providing_technologies = none @@ -1167,6 +1263,7 @@ narrative = Although there have been no reports of it being exploited, Splunk En Splunk Enterprise exposes partial information about the host operating system, hardware, and Splunk license. Splunk Enterprise before 6.6.0 exposes this information without authentication. Splunk Enterprise 6.6.0 and later exposes this information only to authenticated Splunk users. Based on the information exposure, Splunk characterizes this issue as a low severity impact.\ Read more in Splunk's official response: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings.\ A detection search within this Analytic Story looks for vulnerabilities described in CVE-2018-11409: Information Exposure (https://nvd.nist.gov/vuln/detail/CVE-2018-11409). If it turns up activities that may be specific, you can use the included investigative searches to return information regarding web activity and network traffic by src_ip. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Suspicious AWS EC2 Activities] category = Cloud Security @@ -1177,12 +1274,13 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078.004", "T1535"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get Notable History - Response Task", "ESCU - AWS Investigate Security Hub alerts by dest - Response Task", "ESCU - Investigate AWS activities via region name - Response Task", "ESCU - Get EC2 Launch Details - Response Task", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Get EC2 Instance Details by instanceId - Response Task"] -support_searches = ["ESCU - Baseline of Excessive AWS Instances Terminated by User - MLTK", "ESCU - Previously Seen AWS Regions", "ESCU - Previously Seen EC2 Launches By User", "ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Investigate AWS activities via region name - Response Task", "ESCU - Get EC2 Launch Details - Response Task", "ESCU - AWS Investigate Security Hub alerts by dest - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get EC2 Instance Details by instanceId - Response Task"] +support_searches = ["ESCU - Baseline of Excessive AWS Instances Terminated by User - MLTK", "ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK", "ESCU - Previously Seen EC2 Launches By User", "ESCU - Previously Seen AWS Regions"] data_models = [] providing_technologies = none description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and risk auditing within your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Console, AWS command-line interface, and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your AWS EC2 instances and helps you respond and investigate those activities. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Suspicious AWS Login Activities] category = Cloud Security @@ -1194,11 +1292,12 @@ reference = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integr detection_searches = ["ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect new user AWS Console Login - Rule"] mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078.004", "T1535"], "nist": ["DE.AE", "DE.DP"]} investigative_searches = ["ESCU - AWS Investigate User Activities By ARN - Response Task"] -support_searches = ["ESCU - Update previously seen users in CloudTrail", "ESCU - Previously seen users in CloudTrail"] +support_searches = ["ESCU - Previously seen users in CloudTrail", "ESCU - Update previously seen users in CloudTrail"] data_models = ["Authentication"] providing_technologies = none description = Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. narrative = It is important to monitor and control who has access to your AWS infrastructure. Detecting suspicious logins to your AWS infrastructure will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any EC2 instances created by the attacker. +product = ['Splunk Security Analytics for AWS', 'Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Suspicious AWS S3 Activities] category = Cloud Security @@ -1209,14 +1308,15 @@ version = 2 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] detection_searches = ["ESCU - Detect New Open S3 Buckets over AWS CLI - Rule", "ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule"] mappings = {"cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1530"], "nist": ["DE.CM", "DE.DP", "PR.AC", "PR.DS"]} -investigative_searches = ["ESCU - Get Notable History - Response Task", "ESCU - Investigate AWS activities via region name - Response Task", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - AWS S3 Bucket details via bucketName - Response Task", "ESCU - Get All AWS Activity From IP Address - Response Task"] -support_searches = ["ESCU - Previously seen S3 bucket access by remote IP", "ESCU - Baseline of S3 Bucket deletion activity by ARN"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Investigate AWS activities via region name - Response Task", "ESCU - Get All AWS Activity From IP Address - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - AWS S3 Bucket details via bucketName - Response Task"] +support_searches = ["ESCU - Baseline of S3 Bucket deletion activity by ARN", "ESCU - Previously seen S3 bucket access by remote IP"] data_models = [] providing_technologies = none description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. narrative = As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\ Amazon's "shared responsibility" model dictates that the company has responsibility for the environment outside of the VM and the customer is responsible for the security inside of the S3 container. As such, it's important to stay vigilant for activities that may belie suspicious behavior inside of your environment.\ Among things to look out for are S3 access from unfamiliar locations and by unfamiliar users. Some of the searches in this Analytic Story help you detect suspicious behavior and others help you investigate more deeply, when the situation warrants. +product = ['Splunk Security Analytics for AWS', 'Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Suspicious AWS Traffic] category = Cloud Security @@ -1227,7 +1327,7 @@ version = 1 reference = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] detection_searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "nist": ["DE.AE", "DE.CM", "PR.AC"]} -investigative_searches = ["ESCU - Get DNS Server History for a host - Response Task", "ESCU - AWS Network Interface details via resourceId - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Process Responsible For The DNS Traffic - Response Task", "ESCU - Get Process Info - Response Task", "ESCU - Get DNS traffic ratio - Response Task", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Get Process Information For Port Activity - Response Task", "ESCU - AWS Network ACL Details from ID - Response Task", "ESCU - Get All AWS Activity From IP Address - Response Task"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Get Process Info - Response Task", "ESCU - AWS Network Interface details via resourceId - Response Task", "ESCU - Get DNS Server History for a host - Response Task", "ESCU - Get Process Information For Port Activity - Response Task", "ESCU - Get All AWS Activity From IP Address - Response Task", "ESCU - Get DNS traffic ratio - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Process Responsible For The DNS Traffic - Response Task", "ESCU - AWS Network ACL Details from ID - Response Task"] support_searches = ["ESCU - Baseline of blocked outbound traffic from AWS"] data_models = [] providing_technologies = none @@ -1236,6 +1336,7 @@ narrative = A virtual private cloud (VPC) is an on-demand managed cloud-computin Amazon's VPC service enables you to launch EC2 instances and leverage other Amazon resources. The traffic that flows in and out of this VPC can be controlled via network access-control rules and security groups. Amazon also has a feature called VPC Flow Logs that enables you to log IP traffic going to and from the network interfaces in your VPC. This data is stored using Amazon CloudWatch Logs.\ Attackers may abuse the AWS infrastructure with insecure VPCs so they can co-opt AWS resources for command-and-control nodes, data exfiltration, and more. Once an EC2 instance is compromised, an attacker may initiate outbound network connections for malicious reasons. Monitoring these network traffic behaviors is crucial for understanding the type of traffic flowing in and out of your network and to alert you to suspicious activities.\ The searches in this Analytic Story will monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Suspicious Cloud Authentication Activities] category = Cloud Security @@ -1247,12 +1348,13 @@ reference = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cr detection_searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - Detect AWS Console Login by New User - Rule", "ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule"] mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1535"], "nist": ["DE.AE", "DE.DP", "PR.AC", "PR.DS"]} investigative_searches = ["ESCU - Investigate AWS User Activities by user field - Response Task", "ESCU - Get Notable History - Response Task"] -support_searches = ["ESCU - Previously Seen AWS Cross Account Activity - Initial", "ESCU - Previously Seen AWS Cross Account Activity - Update", "ESCU - Previously Seen Users in CloudTrail - Initial", "ESCU - Previously Seen Users In CloudTrail - Update"] +support_searches = ["ESCU - Previously Seen Users In CloudTrail - Update", "ESCU - Previously Seen Users in CloudTrail - Initial", "ESCU - Previously Seen AWS Cross Account Activity - Initial", "ESCU - Previously Seen AWS Cross Account Activity - Update"] data_models = ["Authentication"] providing_technologies = none description = Monitor your cloud authentication events. Searches within this Analytic Story leverage the recent cloud updates to the Authentication data model to help you stay aware of and investigate suspicious login activity. narrative = It is important to monitor and control who has access to your cloud infrastructure. Detecting suspicious logins will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any compute activity whether legitimate or otherwise.\ This Analytic Story has data model versions of cloud searches leveraging Authentication data, including those looking for suspicious login activity, and cross-account activity for AWS. +product = ['Splunk Security Analytics for AWS', 'Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Suspicious Cloud Instance Activities] category = Cloud Security @@ -1263,12 +1365,13 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High Number Of Cloud Instances Destroyed - Rule", "ESCU - Abnormally High Number Of Cloud Instances Launched - Rule", "ESCU - Cloud Instance Modified By Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078.004"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get All AWS Activity From IP Address - Response Task", "ESCU - AWS Investigate User Activities By ARN - Response Task"] -support_searches = ["ESCU - Previously Seen Cloud Instance Modifications By User - Initial", "ESCU - Baseline Of Cloud Instances Launched", "ESCU - Previously Seen Cloud Instance Modifications By User - Update", "ESCU - Baseline Of Cloud Instances Destroyed"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Get All AWS Activity From IP Address - Response Task"] +support_searches = ["ESCU - Baseline Of Cloud Instances Destroyed", "ESCU - Baseline Of Cloud Instances Launched", "ESCU - Previously Seen Cloud Instance Modifications By User - Initial", "ESCU - Previously Seen Cloud Instance Modifications By User - Update"] data_models = ["Change"] providing_technologies = none description = Monitor your cloud infrastructure provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your cloud environment. narrative = Monitoring your cloud infrastructure logs allows you enable governance, compliance, and risk auditing. It is crucial for a company to monitor events and actions taken in the their cloud environments to ensure that your instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your cloud compute instances and helps you respond and investigate those activities. +product = ['Splunk Security Analytics for AWS', 'Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Suspicious Cloud Provisioning Activities] category = Cloud Security @@ -1280,12 +1383,13 @@ reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.p detection_searches = ["ESCU - Cloud Provisioning Activity From Previously Unseen City - Rule", "ESCU - Cloud Provisioning Activity From Previously Unseen Country - Rule", "ESCU - Cloud Provisioning Activity From Previously Unseen IP Address - Rule", "ESCU - Cloud Provisioning Activity From Previously Unseen Region - Rule"] mappings = {"cis20": ["CIS 1"], "mitre_attack": ["T1078"], "nist": ["ID.AM"]} investigative_searches = ["ESCU - Get Notable History - Response Task"] -support_searches = ["ESCU - Previously Seen Cloud Provisioning Activity Sources - Initial", "ESCU - Previously Seen Cloud Provisioning Activity Sources - Update"] +support_searches = ["ESCU - Previously Seen Cloud Provisioning Activity Sources - Update", "ESCU - Previously Seen Cloud Provisioning Activity Sources - Initial"] data_models = ["Change"] providing_technologies = none description = Monitor your cloud infrastructure provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your cloud environment. narrative = Because most enterprise cloud infrastructure activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where it is impossible to add specific IPs to an allow list because they vary.\ This Analytic Story was designed to provide you with flexibility in the precision you employ in specifying legitimate geographic regions. It can be as specific as an IP address or a city, or as broad as a region (think state) or an entire country. By determining how precise you want your geographical locations to be and monitoring for new locations that haven't previously accessed your environment, you can detect adversaries as they begin to probe your environment. Since there are legitimate reasons for activities from unfamiliar locations, this is not a standalone indicator. Nevertheless, location can be a relevant piece of information that you may wish to investigate further. +product = ['Splunk Security Analytics for AWS', 'Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Suspicious Cloud User Activities] category = Cloud Security @@ -1297,12 +1401,13 @@ reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.p detection_searches = ["ESCU - Abnormally High Number Of Cloud Infrastructure API Calls - Rule", "ESCU - Abnormally High Number Of Cloud Security Group API Calls - Rule", "ESCU - Cloud API Calls From Previously Unseen User Roles - Rule"] mappings = {"cis20": ["CIS 1", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078", "T1078.004"], "nist": ["DE.CM", "DE.DP", "ID.AM", "PR.AC"]} investigative_searches = ["ESCU - AWS Investigate User Activities By ARN - Response Task"] -support_searches = ["ESCU - Baseline Of Cloud Infrastructure API Calls Per User", "ESCU - Previously Seen Cloud API Calls Per User Role - Initial", "ESCU - Previously Seen Cloud API Calls Per User Role - Update", "ESCU - Baseline Of Cloud Security Group API Calls Per User"] +support_searches = ["ESCU - Baseline Of Cloud Security Group API Calls Per User", "ESCU - Previously Seen Cloud API Calls Per User Role - Update", "ESCU - Previously Seen Cloud API Calls Per User Role - Initial", "ESCU - Baseline Of Cloud Infrastructure API Calls Per User"] data_models = ["Change"] providing_technologies = none description = Detect and investigate suspicious activities by users and roles in your cloud environments. narrative = It seems obvious that it is critical to monitor and control the users who have access to your cloud infrastructure. Nevertheless, it's all too common for enterprises to lose track of ad-hoc accounts, leaving their servers vulnerable to attack. In fact, this was the very oversight that led to Tesla's cryptojacking attack in February, 2018.\ In addition to compromising the security of your data, when bad actors leverage your compute resources, it can incur monumental costs, since you will be billed for any new instances and increased bandwidth usage. +product = ['Splunk Security Analytics for AWS', 'Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Suspicious Command-Line Executions] category = Adversary Tactics @@ -1313,12 +1418,13 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Exploitation"], "mitre_attack": ["T1036.003", "T1059.001", "T1059.003"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Notable History - Response Task"] -support_searches = ["ESCU - Baseline of Command Line Length - MLTK", "ESCU - Previously seen command line arguments"] +investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Parent Process Info - Response Task"] +support_searches = ["ESCU - Previously seen command line arguments", "ESCU - Baseline of Command Line Length - MLTK"] data_models = ["Endpoint"] providing_technologies = none description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. narrative = The ability to execute arbitrary commands via the Windows CLI is a primary goal for the adversary. With access to the shell, an attacker can easily run scripts and interact with the target system. Often, attackers may only have limited access to the shell or may obtain access in unusual ways. In addition, malware may execute and interact with the CLI in ways that would be considered unusual and inconsistent with typical user activity. This provides defenders with opportunities to identify suspicious use and investigate, as appropriate. This Analytic Story contains various searches to help identify this suspicious activity, as well as others to aid you in deeper investigation. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Suspicious DNS Traffic] category = Adversary Tactics @@ -1329,12 +1435,13 @@ version = 1 reference = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1048.003", "T1071.004", "T1189"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable History - Response Task", "ESCU - Get DNS Server History for a host - Response Task", "ESCU - Get Process Responsible For The DNS Traffic - Response Task", "ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get DNS traffic ratio - Response Task"] +investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get DNS Server History for a host - Response Task", "ESCU - Get DNS traffic ratio - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Process Responsible For The DNS Traffic - Response Task", "ESCU - Get Parent Process Info - Response Task"] support_searches = ["ESCU - Baseline of DNS Query Length - MLTK"] data_models = ["Network_Resolution"] providing_technologies = none description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. narrative = Although DNS is one of the fundamental underlying protocols that make the Internet work, it is often ignored (perhaps because of its complexity and effectiveness). However, attackers have discovered ways to abuse the protocol to meet their objectives. One potential abuse involves manipulating DNS to hijack traffic and redirect it to an IP address under the attacker's control. This could inadvertently send users intending to visit google.com, for example, to an unrelated malicious website. Another technique involves using the DNS protocol for command-and-control activities with the attacker's malicious code or to covertly exfiltrate data. The searches within this Analytic Story look for these types of abuses. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Suspicious Emails] category = Adversary Tactics @@ -1345,7 +1452,7 @@ version = 1 reference = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] detection_searches = ["ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 3", "CIS 7"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1566", "T1566.001"], "nist": ["DE.AE", "PR.IP"]} -investigative_searches = ["ESCU - Get Emails From Specific Sender - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Email Info - Response Task"] +investigative_searches = ["ESCU - Get Notable History - Response Task", "ESCU - Get Emails From Specific Sender - Response Task", "ESCU - Get Email Info - Response Task"] support_searches = ["ESCU - DNSTwist Domain Names"] data_models = ["Email", "UEBA"] providing_technologies = none @@ -1355,6 +1462,7 @@ Once a phishing message has been detected, the next steps are to answer the foll 1. Which users have received this or a similar message in the past?\ 1. When did the targeted campaign begin?\ 1. Have any users interacted with the content of the messages (by downloading an attachment or clicking on a malicious URL)?This Analytic Story provides detection searches to identify suspicious emails, as well as contextual and investigative searches to help answer some of these questions. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Suspicious GCP Storage Activities] category = Cloud Security @@ -1371,6 +1479,7 @@ data_models = [] providing_technologies = none description = Use the searches in this Analytic Story to monitor your GCP Storage buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open storage buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. narrative = Similar to other cloud providers, GCP operates on a shared responsibility model. This means the end user, you, are responsible for setting appropriate access control lists and permissions on your GCP resources.\ This Analytics Story concentrates on detecting things like open storage buckets (both read and write) along with storage bucket access from unfamiliar users and IP addresses. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Suspicious MSHTA Activity] category = Adversary Tactics @@ -1381,8 +1490,8 @@ version = 2 reference = ["https://redcanary.com/blog/introducing-atomictestharnesses/", "https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/techniques/T1218/005/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5"] detection_searches = ["ESCU - Detect MSHTA Url in Command Line - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect Rundll32 Inline HTA Execution - Rule", "ESCU - Detect mshta inline hta execution - Rule", "ESCU - Detect mshta renamed - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Suspicious mshta child process - Rule", "ESCU - Suspicious mshta spawn - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1059.003", "T1218.005", "T1547.001"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Notable History - Response Task"] -support_searches = ["ESCU - Baseline of Command Line Length - MLTK", "ESCU - Previously seen command line arguments"] +investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Parent Process Info - Response Task"] +support_searches = ["ESCU - Previously seen command line arguments", "ESCU - Baseline of Command Line Length - MLTK"] data_models = ["Endpoint"] providing_technologies = none description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. @@ -1399,6 +1508,7 @@ The objective of this step is meant to identify suspicious behavioral indicators 1. Network connections. Any network connections? Review the reputation of the remote IP or domain.\ Retrieval of script code\ The objective of this step is to confirm the executed script code is benign or malicious. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Suspicious Okta Activity] category = Adversary Tactics @@ -1409,7 +1519,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] detection_searches = ["ESCU - Multiple Okta Users With Invalid Credentials From The Same IP - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078.001"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate User Activities In Okta - Response Task", "ESCU - Investigate Okta Activity by app - Response Task", "ESCU - Investigate Okta Activity by IP Address - Response Task"] +investigative_searches = ["ESCU - Investigate User Activities In Okta - Response Task", "ESCU - Investigate Okta Activity by IP Address - Response Task", "ESCU - Investigate Okta Activity by app - Response Task"] support_searches = [] data_models = [] providing_technologies = none @@ -1417,6 +1527,7 @@ description = Monitor your Okta environment for suspicious activities. Due to th narrative = Okta is the leading single sign on (SSO) provider, allowing users to authenticate once to Okta, and from there access a variety of web-based applications. These applications are assigned to users and allow administrators to centrally manage which users are allowed to access which applications. It also provides centralized logging to help understand how the applications are used and by whom. \ While SSO is a major convenience for users, it also provides attackers with an opportunity. If the attacker can gain access to Okta, they can access a variety of applications. As such monitoring the environment is important. \ With people moving quickly to adopt web-based applications and ways to manage them, many are still struggling to understand how best to monitor these environments. This analytic story provides searches to help monitor this environment, and identify events and activity that warrant further investigation such as credential stuffing or password spraying attacks, and users logging in from multiple locations when travel is disallowed. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Suspicious Regsvr32 Activity] category = Adversary Tactics @@ -1433,6 +1544,7 @@ data_models = ["Endpoint"] providing_technologies = none description = Monitor and detect techniques used by attackers who leverage the regsvr32.exe process to execute malicious code. narrative = One common adversary tactic is to bypass application control solutions via the regsvr32.exe process. This particular bypass was popularized with "SquiblyDoo" using the "scrobj.dll" dll to load .sct scriptlets. This technique is still widely used by adversaries to bypass detection and prevention controls. The file extension of the DLL is irrelevant (it may load a .txt file extension for example). The searches in this story help you detect and investigate suspicious activity that may indicate that an adversary is leveraging regsvr32.exe to execute malicious code. Validate execution Determine if regsvr32.exe executed. Validate the OriginalFileName of regsvr32.exe and further PE metadata. If executed outside of c:\windows\system32 or c:\windows\syswow64, it should be highly suspect. Determine if script code was executed with regsvr32. Situational Awareness - The objective of this step is meant to identify suspicious behavioral indicators related to executed of Script code by regsvr32.exe. Parent process. Is the parent process a known LOLBin? Is the parent process an Office Application? Module loads. Is regsvr32 loading any suspicious .DLLs? Unsigned or signed from non-standard paths. Network connections. Any network connections? Review the reputation of the remote IP or domain. Retrieval of Script Code - confirm the executed script code is benign or malicious. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Suspicious Rundll32 Activity] category = Adversary Tactics @@ -1449,6 +1561,7 @@ data_models = ["Endpoint"] providing_technologies = none description = Monitor and detect techniques used by attackers who leverage rundll32.exe to execute arbitrary malicious code. narrative = One common adversary tactic is to bypass application control solutions via the rundll32.exe process. Natively, rundll32.exe will load DLLs and is a great example of a Living off the Land Binary. Rundll32.exe may load malicious DLLs by ordinals, function names or directly. The queries in this story focus on loading default DLLs, syssetup.dll, ieadvpack.dll, advpack.dll and setupapi.dll from disk that may be abused by adversaries. Additionally, two analytics developed to assist with identifying DLLRegisterServer, Start and StartW functions being called. The searches in this story help you detect and investigate suspicious activity that may indicate that an adversary is leveraging rundll32.exe to execute malicious code. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Suspicious WMI Use] category = Adversary Tactics @@ -1459,7 +1572,7 @@ version = 2 reference = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] detection_searches = ["ESCU - Process Execution via WMI - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - WMI Temporary Event Subscription - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1546.003"], "nist": ["PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Sysmon WMI Activity for Host - Response Task", "ESCU - Get Notable History - Response Task"] +investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Sysmon WMI Activity for Host - Response Task", "ESCU - Get Parent Process Info - Response Task"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1467,6 +1580,7 @@ description = Attackers are increasingly abusing Windows Management Instrumentat narrative = WMI is a Microsoft infrastructure for management data and operations on Windows operating systems. It includes of a set of utilities that can be leveraged to manage both local and remote Windows systems. Attackers are increasingly turning to WMI abuse in their efforts to conduct nefarious tasks, such as reconnaissance, detection of antivirus and virtual machines, code execution, lateral movement, persistence, and data exfiltration. \ The detection searches included in this Analytic Story are used to look for suspicious use of WMI commands that attackers may leverage to interact with remote systems. The searches specifically look for the use of WMI to run processes on remote systems.\ In the event that unauthorized WMI execution occurs, it will be important for analysts and investigators to determine the context of the event. These details may provide insights related to how WMI was used and to what end. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Suspicious Windows Registry Activities] category = Adversary Tactics @@ -1477,7 +1591,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1546.001", "T1546.011", "T1546.012", "T1547.001", "T1547.010", "T1548.002", "T1564.001"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Notable History - Response Task"] +investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Parent Process Info - Response Task"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1485,6 +1599,7 @@ description = Monitor and detect registry changes initiated from remote location narrative = Attackers are developing increasingly sophisticated techniques for hijacking target servers, while evading detection. One such technique that has become progressively more common is registry modification.\ The registry is a key component of the Windows operating system. It has a hierarchical database called "registry" that contains settings, options, and values for executables. Once the threat actor gains access to a machine, they can use reg.exe to modify their account to obtain administrator-level privileges, maintain persistence, and move laterally within the environment.\ The searches in this story are designed to help you detect behaviors associated with manipulation of the Windows registry. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Suspicious Zoom Child Processes] category = Adversary Tactics @@ -1496,12 +1611,13 @@ reference = ["https://blog.rapid7.com/2020/04/02/dispelling-zoom-bugbears-what-y detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - First Time Seen Child Process of Zoom - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1059.003", "T1068"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} investigative_searches = ["ESCU - Get Process File Activity - Response Task"] -support_searches = ["ESCU - Previously Seen Zoom Child Processes - Initial", "ESCU - Previously Seen Zoom Child Processes - Update"] +support_searches = ["ESCU - Previously Seen Zoom Child Processes - Update", "ESCU - Previously Seen Zoom Child Processes - Initial"] data_models = ["Endpoint"] providing_technologies = none description = Attackers are using Zoom as an vector to increase privileges on a sytems. This story detects new child processes of zoom and provides investigative actions for this detection. narrative = Zoom is a leader in modern enterprise video communications and its usage has increased dramatically with a large amount of the population under stay-at-home orders due to the COVID-19 pandemic. With increased usage has come increased scrutiny and several security flaws have been found with this application on both Windows and macOS systems.\ Current detections focus on finding new child processes of this application on a per host basis. Investigative searches are included to gather information needed during an investigation. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Trusted Developer Utilities Proxy Execution] category = Adversary Tactics @@ -1519,6 +1635,7 @@ providing_technologies = none description = Monitor and detect behaviors used by attackers who leverage trusted developer utilities to execute malicious code. narrative = Adversaries may take advantage of trusted developer utilities to proxy execution of malicious payloads. There are many utilities used for software development related tasks that can be used to execute code in various forms to assist in development, debugging, and reverse engineering. These utilities may often be signed with legitimate certificates that allow them to execute on a system and proxy execution of malicious code through a trusted process that effectively bypasses application control solutions.\ The searches in this story help you detect and investigate suspicious activity that may indicate that an adversary is leveraging microsoft.workflow.compiler.exe to execute malicious code. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Trusted Developer Utilities Proxy Execution MSBuild] category = Adversary Tactics @@ -1548,6 +1665,7 @@ The objective of this step is meant to identify suspicious behavioral indicators 1. Network connections. Any network connections? Review the reputation of the remote IP or domain.\ Retrieval of script code\ The objective of this step is to confirm the executed script code is benign or malicious. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Unusual AWS EC2 Modifications] category = Cloud Security @@ -1558,13 +1676,14 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1"], "mitre_attack": ["T1078.004"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get Notable History - Response Task", "ESCU - Get EC2 Instance Details by instanceId - Response Task", "ESCU - AWS Investigate User Activities By ARN - Response Task"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get EC2 Instance Details by instanceId - Response Task"] support_searches = ["ESCU - Previously Seen EC2 Modifications By User"] data_models = [] providing_technologies = none description = Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. narrative = A common attack technique is to infiltrate a cloud instance and make modifications. The adversary can then secure access to your infrastructure or hide their activities. So it's important to stay alert to changes that may indicate that your environment has been compromised. \ Searches within this Analytic Story can help you detect the presence of a threat by monitoring for EC2 instances that have been created or changed--either by users that have never previously performed these activities or by known users who modify or create instances in a way that have not been done before. This story also provides investigative searches that help you go deeper once you detect suspicious behavior. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Unusual Processes] category = Malware @@ -1575,7 +1694,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1016", "T1036.003", "T1204.002", "T1218.011"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Notable History - Response Task"] +investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Parent Process Info - Response Task"] support_searches = ["ESCU - Baseline of Command Line Length - MLTK"] data_models = ["Endpoint"] providing_technologies = none @@ -1583,6 +1702,7 @@ description = Quickly identify systems running new or unusual processes in your narrative = Being able to profile a host's processes within your environment can help you more quickly identify processes that seem out of place when compared to the rest of the population of hosts or asset types.\ This Analytic Story lets you identify processes that are either a) not typically seen running or b) have some sort of suspicious command-line arguments associated with them. This Analytic Story will also help you identify the user running these processes and the associated process activity on the host.\ In the event an unusual process is identified, it is imperative to better understand how that process was able to execute on the host, when it first executed, and whether other hosts are affected. This extra information may provide clues that can help the analyst further investigate any suspicious activity. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Use of Cleartext Protocols] category = Best Practices @@ -1599,6 +1719,7 @@ data_models = ["Network_Traffic"] providing_technologies = none description = Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. narrative = Various legacy protocols operate by default in the clear, without the protections of encryption. This potentially leaks sensitive information that can be exploited by passively sniffing network traffic. Depending on the protocol, this information could be highly sensitive, or could allow for session hijacking. In addition, these protocols send authentication information, which would allow for the harvesting of usernames and passwords that could potentially be used to authenticate and compromise secondary systems. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Web Fraud Detection] category = Abuse @@ -1609,7 +1730,7 @@ version = 1 reference = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] detection_searches = ["ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule"] mappings = {"cis20": ["CIS 16", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078", "T1136"], "nist": ["DE.AE", "DE.CM", "DE.DP"]} -investigative_searches = ["ESCU - Get Emails From Specific Sender - Response Task", "ESCU - Get Web Session Information via session id - Response Task", "ESCU - Get Notable History - Response Task"] +investigative_searches = ["ESCU - Get Emails From Specific Sender - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Web Session Information via session id - Response Task"] support_searches = [] data_models = [] providing_technologies = none @@ -1620,6 +1741,7 @@ When developing a strategy for preventing fraud in your environment, its importa The account-harvesting search focuses on web pages used for user-account registration. It detects the creation of a large number of user accounts using the same email domain name, a type of activity frequently seen in advance of a fraud campaign.\ The anomalous clickspeed search looks for users who are moving through your website at a faster-than-normal speed or with a perfect click cadence (high periodicity or low standard deviation), which could indicate that the user is a script, not an actual human.\ Another search detects incidents wherein a single password is used across multiple accounts, which may indicate that a fraudster has infiltrated your environment and embedded a common password within a script. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Windows DNS SIGRed CVE-2020-1350] category = Adversary Tactics @@ -1636,6 +1758,7 @@ data_models = ["Network_Resolution"] providing_technologies = none description = Uncover activity consistent with CVE-2020-1350, or SIGRed. Discovered by Checkpoint researchers, this vulnerability affects Windows 2003 to 2019, and is triggered by a malicious DNS response (only affects DNS over TCP). An attacker can use the malicious payload to cause a buffer overflow on the vulnerable system, leading to compromise. The included searches in this Analytic Story are designed to identify the large response payload for SIG and KEY DNS records which can be used for the exploit. narrative = When a client requests a DNS record for a particular domain, that request gets routed first through the client's locally configured DNS server, then to any DNS server(s) configured as forwarders, and then onto the target domain's own DNS server(s). If a attacker wanted to, they could host a malicious DNS server that responds to the initial request with a specially crafted large response (~65KB). This response would flow through to the client's local DNS server, which if not patched for CVE-2020-1350, would cause the buffer overflow. The detection searches in this Analytic Story use wire data to detect the malicious behavior. Searches for Splunk Stream and Zeek are included. The Splunk Stream search correlates across stream:dns and stream:tcp, while the Zeek search correlates across bro:dns:json and bro:conn:json. These correlations are required to pick up both the DNS record types (SIG and KEY) along with the payload size (>65KB). +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Windows Defense Evasion Tactics] category = Adversary Tactics @@ -1644,14 +1767,15 @@ modification_date = 2018-05-31 id = 56e24a28-5003-4047-b2db-e8f3c4618064 version = 1 reference = ["https://attack.mitre.org/wiki/Defense_Evasion"] -detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Eventvwr UAC Bypass - Rule", "ESCU - FodHelper UAC Bypass - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Windows DisableAntiSpyware Registry - Rule"] +detection_searches = ["ESCU - Disable Registry Tool - Rule", "ESCU - Disable Show Hidden Files - Rule", "ESCU - Disable Windows Behavior Monitoring - Rule", "ESCU - Disable Windows SmartScreen Protection - Rule", "ESCU - Disabling CMD Application - Rule", "ESCU - Disabling ControlPanel - Rule", "ESCU - Disabling Firewall with Netsh - Rule", "ESCU - Disabling FolderOptions Windows Feature - Rule", "ESCU - Disabling NoRun Windows App - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Disabling SystemRestore In Registry - Rule", "ESCU - Disabling Task Manager - Rule", "ESCU - Eventvwr UAC Bypass - Rule", "ESCU - FodHelper UAC Bypass - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Windows DisableAntiSpyware Registry - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Delivery", "Exploitation", "Privilege Escalation"], "mitre_attack": ["T1112", "T1222.001", "T1548.002", "T1562.001", "T1564.001"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Notable History - Response Task"] +investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Parent Process Info - Response Task"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others narrative = Defense evasion is a tactic--identified in the MITRE ATT&CK framework--that adversaries employ in a variety of ways to bypass or defeat defensive security measures. There are many techniques enumerated by the MITRE ATT&CK framework that are applicable in this context. This Analytic Story includes searches designed to identify the use of such techniques on Windows platforms. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Windows File Extension and Association Abuse] category = Malware @@ -1662,7 +1786,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] detection_searches = ["ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1036.003", "T1546.001"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Notable History - Response Task"] +investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Parent Process Info - Response Task"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1672,6 +1796,7 @@ narrative = Attackers use a variety of techniques to entice users to run malicio Attackers take advantage of this expectation by obfuscating the true file extension. They can accomplish this in a couple of ways. One technique involves inserting multiple spaces in the file name before the extension to hide the extension from the GUI, obscuring the true nature of the file. Another approach involves prepending the real extension with a different one. This is especially effective when Windows is configured to "hide extensions for known file types." In this case, the real extension is not displayed, but the prepended one is, leading end users to believe the file is a different type than it actually is.\ Changing the association between a file extension and an application can allow an attacker to execute arbitrary code. The technique typically involves changing the association for an often-launched file type to associate instead with a malicious program the attacker has dropped on the endpoint. When the end user launches a file that has been manipulated in this way, it will execute the attacker's malware. It will also execute the application the end user expected to run, cleverly obscuring the fact that something suspicious has occurred.\ Run the searches in this story to detect and investigate suspicious behavior that may indicate abuse or manipulation of Windows file extensions and/or associations. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Windows Log Manipulation] category = Adversary Tactics @@ -1682,13 +1807,14 @@ version = 2 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] detection_searches = ["ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070", "T1070.001", "T1490"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Notable History - Response Task"] +investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Parent Process Info - Response Task"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. narrative = Because attackers often modify system logs to cover their tracks and/or to thwart the investigative process, log monitoring is an industry-recognized best practice. While there are legitimate reasons to manipulate system logs, it is still worthwhile to keep track of who manipulated the logs, when they manipulated them, and in what way they manipulated them (determining which accesses, tools, or utilities were employed). Even if no malicious activity is detected, the knowledge of an attempt to manipulate system logs may be indicative of a broader security risk that should be thoroughly investigated.\ The Analytic Story gives users two different ways to detect manipulation of Windows Event Logs and one way to detect deletion of the Update Sequence Number (USN) Change Journal. The story helps determine the history of the host and the users who have accessed it. Finally, the story aides in investigation by retrieving all the information on the process that caused these events (if the process has been identified). +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Windows Persistence Techniques] category = Adversary Tactics @@ -1699,12 +1825,13 @@ version = 2 reference = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] detection_searches = ["ESCU - Certutil exe certificate extraction - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Suspicious Scheduled Task from Public Directory - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation", "Installation", "Privilege Escalation"], "mitre_attack": ["T1053.005", "T1222.001", "T1543.003", "T1546.011", "T1547.001", "T1547.010", "T1564.001", "T1574.009", "T1574.011"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Notable History - Response Task"] +investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Parent Process Info - Response Task"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. narrative = Maintaining persistence is one of the first steps taken by attackers after the initial compromise. Attackers leverage various custom and built-in tools to ensure survivability and persistent access within a compromised enterprise. This Analytic Story provides searches to help you identify various behaviors used by attackers to maintain persistent access to a Windows environment. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Windows Privilege Escalation] category = Adversary Tactics @@ -1715,12 +1842,13 @@ version = 2 reference = ["https://attack.mitre.org/tactics/TA0004/"] detection_searches = ["ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Uncommon Processes On Endpoint - Rule"] mappings = {"cis20": ["CIS 2", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1068", "T1204.002", "T1546.008", "T1546.012"], "nist": ["DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Notable History - Response Task"] +investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Parent Process Info - Response Task"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. narrative = Privilege escalation is a "land-and-expand" technique, wherein an adversary gains an initial foothold on a host and then exploits its weaknesses to increase his privileges. The motivation is simple: certain actions on a Windows machine--such as installing software--may require higher-level privileges than those the attacker initially acquired. By increasing his privilege level, the attacker can gain the control required to carry out his malicious ends. This Analytic Story provides searches to detect and investigate behaviors that attackers may use to elevate their privileges in your environment. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Windows Service Abuse] category = Malware @@ -1731,11 +1859,12 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 2", "CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1543.003", "T1569.002", "T1574.011"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.AT", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Notable History - Response Task"] -support_searches = ["ESCU - Previously Seen Running Windows Services - Initial", "ESCU - Previously Seen Running Windows Services - Update"] +investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Parent Process Info - Response Task"] +support_searches = ["ESCU - Previously Seen Running Windows Services - Update", "ESCU - Previously Seen Running Windows Services - Initial"] data_models = ["Endpoint"] providing_technologies = none description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. narrative = The Windows operating system uses a services architecture to allow for running code in the background, similar to a UNIX daemon. Attackers will often leverage Windows services for persistence, hiding in plain sight, seeking the ability to run privileged code that can interact with the kernel. In many cases, attackers will create a new service to host their malicious code. Attackers have also been observed modifying unnecessary or unused services to point to their own code, as opposed to what was intended. In these cases, attackers often use tools to create or modify services in ways that are not typical for most environments, providing opportunities for detection. +product = ['Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] #### END STORIES #### \ No newline at end of file diff --git a/dist/escu/default/collections.conf b/dist/escu/default/collections.conf index 37f4c36c90..9bdda60900 100644 --- a/dist/escu/default/collections.conf +++ b/dist/escu/default/collections.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security_content -# On Date: 2021-03-29T18:33:55 UTC +# On Date: 2021-04-14T19:13:35 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/dist/escu/default/es_investigations.conf b/dist/escu/default/es_investigations.conf index d9c01329fe..0343ae28d2 100644 --- a/dist/escu/default/es_investigations.conf +++ b/dist/escu/default/es_investigations.conf @@ -4,14 +4,14 @@ label = AWS Cross Account Activity description = Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity. disabled = 0 -panels = ["panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_aws_investigate_user_activities_by_accesskeyid___response_task"] +panels = ["panel://workbench_panel_aws_investigate_user_activities_by_accesskeyid___response_task", "panel://workbench_panel_get_notable_history___response_task"] [panel_group://workbench_panel_group_aws_cryptomining] label = AWS Cryptomining description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. disabled = 0 -panels = ["panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_investigate_aws_activities_via_region_name___response_task", "panel://workbench_panel_get_ec2_launch_details___response_task", "panel://workbench_panel_aws_investigate_user_activities_by_arn___response_task", "panel://workbench_panel_get_ec2_instance_details_by_instanceid___response_task"] +panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn___response_task", "panel://workbench_panel_investigate_aws_activities_via_region_name___response_task", "panel://workbench_panel_get_ec2_launch_details___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_ec2_instance_details_by_instanceid___response_task"] [panel_group://workbench_panel_group_aws_iam_privilege_escalation] label = AWS IAM Privilege Escalation @@ -25,21 +25,21 @@ label = AWS Network ACL Activity description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. disabled = 0 -panels = ["panel://workbench_panel_get_dns_server_history_for_a_host___response_task", "panel://workbench_panel_aws_network_interface_details_via_resourceid___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic___response_task", "panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_dns_traffic_ratio___response_task", "panel://workbench_panel_aws_investigate_user_activities_by_arn___response_task", "panel://workbench_panel_get_process_information_for_port_activity___response_task", "panel://workbench_panel_aws_network_acl_details_from_id___response_task", "panel://workbench_panel_get_all_aws_activity_from_ip_address___response_task"] +panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn___response_task", "panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_aws_network_interface_details_via_resourceid___response_task", "panel://workbench_panel_get_dns_server_history_for_a_host___response_task", "panel://workbench_panel_get_process_information_for_port_activity___response_task", "panel://workbench_panel_get_all_aws_activity_from_ip_address___response_task", "panel://workbench_panel_get_dns_traffic_ratio___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic___response_task", "panel://workbench_panel_aws_network_acl_details_from_id___response_task"] [panel_group://workbench_panel_group_aws_security_hub_alerts] label = AWS Security Hub Alerts description = This story is focused around detecting Security Hub alerts generated from AWS disabled = 0 -panels = ["panel://workbench_panel_get_ec2_launch_details___response_task", "panel://workbench_panel_get_ec2_instance_details_by_instanceid___response_task", "panel://workbench_panel_aws_investigate_user_activities_by_arn___response_task"] +panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn___response_task", "panel://workbench_panel_get_ec2_instance_details_by_instanceid___response_task", "panel://workbench_panel_get_ec2_launch_details___response_task"] [panel_group://workbench_panel_group_aws_suspicious_provisioning_activities] label = AWS Suspicious Provisioning Activities description = Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. disabled = 0 -panels = ["panel://workbench_panel_get_all_aws_activity_from_country___response_task", "panel://workbench_panel_get_all_aws_activity_from_region___response_task", "panel://workbench_panel_aws_investigate_user_activities_by_arn___response_task", "panel://workbench_panel_get_all_aws_activity_from_city___response_task", "panel://workbench_panel_get_all_aws_activity_from_ip_address___response_task", "panel://workbench_panel_aws_investigate_security_hub_alerts_by_dest___response_task"] +panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn___response_task", "panel://workbench_panel_get_all_aws_activity_from_city___response_task", "panel://workbench_panel_aws_investigate_security_hub_alerts_by_dest___response_task", "panel://workbench_panel_get_all_aws_activity_from_ip_address___response_task", "panel://workbench_panel_get_all_aws_activity_from_country___response_task", "panel://workbench_panel_get_all_aws_activity_from_region___response_task"] [panel_group://workbench_panel_group_aws_user_monitoring] label = AWS User Monitoring @@ -53,14 +53,21 @@ label = Apache Struts Vulnerability description = Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. disabled = 0 -panels = ["panel://workbench_panel_investigate_suspicious_strings_in_http_header___response_task", "panel://workbench_panel_investigate_web_posts_from_src___response_task", "panel://workbench_panel_get_notable_history___response_task"] +panels = ["panel://workbench_panel_investigate_web_posts_from_src___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_investigate_suspicious_strings_in_http_header___response_task"] [panel_group://workbench_panel_group_asset_tracking] label = Asset Tracking description = Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further. disabled = 0 -panels = ["panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_first_occurrence_and_last_occurrence_of_a_mac_address___response_task"] +panels = ["panel://workbench_panel_get_first_occurrence_and_last_occurrence_of_a_mac_address___response_task", "panel://workbench_panel_get_notable_history___response_task"] + +[panel_group://workbench_panel_group_bits_jobs] +label = BITS Jobs +description = Adversaries may abuse BITS jobs to persistently execute or clean up after malicious payloads. +disabled = 0 + +panels = ["panel://workbench_panel_get_notable_history___response_task"] [panel_group://workbench_panel_group_baron_samedit_cve_2021_3156] label = Baron Samedit CVE-2021-3156 @@ -74,7 +81,7 @@ label = Brand Monitoring description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. disabled = 0 -panels = ["panel://workbench_panel_get_emails_from_specific_sender___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_email_info___response_task", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic___response_task"] +panels = ["panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_emails_from_specific_sender___response_task", "panel://workbench_panel_get_email_info___response_task", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic___response_task"] [panel_group://workbench_panel_group_clop_ransomware] label = Clop Ransomware @@ -88,7 +95,7 @@ label = Cloud Cryptomining description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. disabled = 0 -panels = ["panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_aws_investigate_security_hub_alerts_by_dest___response_task", "panel://workbench_panel_investigate_aws_activities_via_region_name___response_task", "panel://workbench_panel_get_ec2_launch_details___response_task", "panel://workbench_panel_aws_investigate_user_activities_by_arn___response_task", "panel://workbench_panel_get_ec2_instance_details_by_instanceid___response_task"] +panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn___response_task", "panel://workbench_panel_investigate_aws_activities_via_region_name___response_task", "panel://workbench_panel_get_ec2_launch_details___response_task", "panel://workbench_panel_aws_investigate_security_hub_alerts_by_dest___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_ec2_instance_details_by_instanceid___response_task"] [panel_group://workbench_panel_group_cloud_federated_credential_abuse] label = Cloud Federated Credential Abuse @@ -109,21 +116,21 @@ label = ColdRoot MacOS RAT description = Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. disabled = 0 -panels = ["panel://workbench_panel_investigate_network_traffic_from_src_ip___response_task", "panel://workbench_panel_get_notable_history___response_task"] +panels = ["panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_investigate_network_traffic_from_src_ip___response_task"] [panel_group://workbench_panel_group_collection_and_staging] label = Collection and Staging description = Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. disabled = 0 -panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_parent_process_info___response_task", "panel://workbench_panel_get_notable_history___response_task"] +panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_parent_process_info___response_task"] [panel_group://workbench_panel_group_command_and_control] label = Command and Control description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. disabled = 0 -panels = ["panel://workbench_panel_get_dns_server_history_for_a_host___response_task", "panel://workbench_panel_aws_network_interface_details_via_resourceid___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic___response_task", "panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_parent_process_info___response_task", "panel://workbench_panel_get_dns_traffic_ratio___response_task", "panel://workbench_panel_aws_investigate_user_activities_by_arn___response_task", "panel://workbench_panel_get_process_information_for_port_activity___response_task", "panel://workbench_panel_aws_network_acl_details_from_id___response_task", "panel://workbench_panel_get_all_aws_activity_from_ip_address___response_task"] +panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn___response_task", "panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_aws_network_interface_details_via_resourceid___response_task", "panel://workbench_panel_get_dns_server_history_for_a_host___response_task", "panel://workbench_panel_get_process_information_for_port_activity___response_task", "panel://workbench_panel_get_all_aws_activity_from_ip_address___response_task", "panel://workbench_panel_get_dns_traffic_ratio___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic___response_task", "panel://workbench_panel_aws_network_acl_details_from_id___response_task", "panel://workbench_panel_get_parent_process_info___response_task"] [panel_group://workbench_panel_group_common_phishing_frameworks] label = Common Phishing Frameworks @@ -144,14 +151,14 @@ label = Credential Dumping description = Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. disabled = 0 -panels = ["panel://workbench_panel_investigate_pass_the_ticket_attempts___response_task", "panel://workbench_panel_investigate_previous_unseen_user___response_task", "panel://workbench_panel_investigate_pass_the_hash_attempts___response_task", "panel://workbench_panel_investigate_failed_logins_for_multiple_destinations___response_task"] +panels = ["panel://workbench_panel_investigate_pass_the_hash_attempts___response_task", "panel://workbench_panel_investigate_previous_unseen_user___response_task", "panel://workbench_panel_investigate_failed_logins_for_multiple_destinations___response_task", "panel://workbench_panel_investigate_pass_the_ticket_attempts___response_task"] [panel_group://workbench_panel_group_dhs_report_ta18_074a] label = DHS Report TA18-074A description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. disabled = 0 -panels = ["panel://workbench_panel_get_process_file_activity___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_parent_process_info___response_task", "panel://workbench_panel_get_process_information_for_port_activity___response_task"] +panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_process_information_for_port_activity___response_task", "panel://workbench_panel_get_process_file_activity___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_parent_process_info___response_task"] [panel_group://workbench_panel_group_dns_amplification_attacks] label = DNS Amplification Attacks @@ -165,7 +172,7 @@ label = DNS Hijacking description = Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records. disabled = 0 -panels = ["panel://workbench_panel_get_dns_server_history_for_a_host___response_task", "panel://workbench_panel_dns_hijack_enrichment___response_task"] +panels = ["panel://workbench_panel_dns_hijack_enrichment___response_task", "panel://workbench_panel_get_dns_server_history_for_a_host___response_task"] [panel_group://workbench_panel_group_data_exfiltration] label = Data Exfiltration @@ -179,7 +186,7 @@ label = Data Protection description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. disabled = 0 -panels = ["panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_dns_server_history_for_a_host___response_task", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic___response_task", "panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_dns_traffic_ratio___response_task"] +panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_dns_server_history_for_a_host___response_task", "panel://workbench_panel_get_dns_traffic_ratio___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic___response_task"] [panel_group://workbench_panel_group_deobfuscate_decode_files_or_information] label = Deobfuscate-Decode Files or Information @@ -200,21 +207,28 @@ label = Disabling Security Tools description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. disabled = 0 -panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_parent_process_info___response_task", "panel://workbench_panel_get_notable_history___response_task"] +panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_parent_process_info___response_task"] + +[panel_group://workbench_panel_group_domain_trust_discovery] +label = Domain Trust Discovery +description = Adversaries may attempt to gather information on domain trust relationships that may be used to identify lateral movement opportunities in Windows multi-domain/forest environments. +disabled = 0 + +panels = ["panel://workbench_panel_get_notable_history___response_task"] [panel_group://workbench_panel_group_dynamic_dns] label = Dynamic DNS description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and deny lists. disabled = 0 -panels = ["panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_dns_traffic_ratio___response_task", "panel://workbench_panel_get_dns_server_history_for_a_host___response_task", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic___response_task"] +panels = ["panel://workbench_panel_get_process_responsible_for_the_dns_traffic___response_task", "panel://workbench_panel_get_dns_traffic_ratio___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_dns_server_history_for_a_host___response_task"] [panel_group://workbench_panel_group_emotet_malware__dhs_report_ta18_201a_] label = Emotet Malware DHS Report TA18-201A description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. disabled = 0 -panels = ["panel://workbench_panel_get_history_of_email_sources___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_parent_process_info___response_task", "panel://workbench_panel_get_process_information_for_port_activity___response_task"] +panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_process_information_for_port_activity___response_task", "panel://workbench_panel_get_history_of_email_sources___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_parent_process_info___response_task"] [panel_group://workbench_panel_group_f5_tmui_rce_cve_2020_5902] label = F5 TMUI RCE CVE-2020-5902 @@ -242,7 +256,7 @@ label = Hidden Cobra Malware description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. disabled = 0 -panels = ["panel://workbench_panel_get_history_of_email_sources___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_dns_server_history_for_a_host___response_task", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic___response_task", "panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_parent_process_info___response_task", "panel://workbench_panel_get_dns_traffic_ratio___response_task", "panel://workbench_panel_get_process_information_for_port_activity___response_task", "panel://workbench_panel_get_outbound_emails_to_hidden_cobra_threat_actors___response_task", "panel://workbench_panel_investigate_successful_remote_desktop_authentications___response_task"] +panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_dns_server_history_for_a_host___response_task", "panel://workbench_panel_get_process_information_for_port_activity___response_task", "panel://workbench_panel_get_history_of_email_sources___response_task", "panel://workbench_panel_get_dns_traffic_ratio___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic___response_task", "panel://workbench_panel_investigate_successful_remote_desktop_authentications___response_task", "panel://workbench_panel_get_outbound_emails_to_hidden_cobra_threat_actors___response_task", "panel://workbench_panel_get_parent_process_info___response_task"] [panel_group://workbench_panel_group_host_redirection] label = Host Redirection @@ -270,7 +284,7 @@ label = Kubernetes Scanning Activity description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. disabled = 0 -panels = ["panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_amazon_eks_kubernetes_activity_by_src_ip___response_task", "panel://workbench_panel_gcp_kubernetes_activity_by_src_ip___response_task"] +panels = ["panel://workbench_panel_gcp_kubernetes_activity_by_src_ip___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_amazon_eks_kubernetes_activity_by_src_ip___response_task"] [panel_group://workbench_panel_group_kubernetes_sensitive_object_access_activity] label = Kubernetes Sensitive Object Access Activity @@ -291,14 +305,14 @@ label = Lateral Movement description = Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. disabled = 0 -panels = ["panel://workbench_panel_get_history_of_email_sources___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_parent_process_info___response_task", "panel://workbench_panel_get_process_information_for_port_activity___response_task", "panel://workbench_panel_investigate_successful_remote_desktop_authentications___response_task"] +panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_process_information_for_port_activity___response_task", "panel://workbench_panel_get_history_of_email_sources___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_investigate_successful_remote_desktop_authentications___response_task", "panel://workbench_panel_get_parent_process_info___response_task"] [panel_group://workbench_panel_group_malicious_powershell] label = Malicious PowerShell description = Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. disabled = 0 -panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_parent_process_info___response_task", "panel://workbench_panel_get_history_of_email_sources___response_task", "panel://workbench_panel_get_notable_history___response_task"] +panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_history_of_email_sources___response_task", "panel://workbench_panel_get_parent_process_info___response_task"] [panel_group://workbench_panel_group_monitor_backup_solution] label = Monitor Backup Solution @@ -312,7 +326,7 @@ label = Monitor for Unauthorized Software description = Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. disabled = 0 -panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_parent_process_info___response_task", "panel://workbench_panel_get_notable_history___response_task"] +panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_parent_process_info___response_task"] [panel_group://workbench_panel_group_monitor_for_updates] label = Monitor for Updates @@ -333,7 +347,7 @@ label = Netsh Abuse description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. disabled = 0 -panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_parent_process_info___response_task", "panel://workbench_panel_get_notable_history___response_task"] +panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_parent_process_info___response_task"] [panel_group://workbench_panel_group_office_365_detections] label = Office 365 Detections @@ -347,7 +361,7 @@ label = Orangeworm Attack Group description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. disabled = 0 -panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_parent_process_info___response_task", "panel://workbench_panel_get_history_of_email_sources___response_task", "panel://workbench_panel_get_notable_history___response_task"] +panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_history_of_email_sources___response_task", "panel://workbench_panel_get_parent_process_info___response_task"] [panel_group://workbench_panel_group_phishing_payloads] label = Phishing Payloads @@ -361,21 +375,21 @@ label = Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. disabled = 0 -panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_parent_process_info___response_task", "panel://workbench_panel_get_history_of_email_sources___response_task", "panel://workbench_panel_get_notable_history___response_task"] +panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_history_of_email_sources___response_task", "panel://workbench_panel_get_parent_process_info___response_task"] [panel_group://workbench_panel_group_prohibited_traffic_allowed_or_protocol_mismatch] label = Prohibited Traffic Allowed or Protocol Mismatch description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. disabled = 0 -panels = ["panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_dns_server_history_for_a_host___response_task", "panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_parent_process_info___response_task", "panel://workbench_panel_get_process_information_for_port_activity___response_task"] +panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_process_information_for_port_activity___response_task", "panel://workbench_panel_get_dns_server_history_for_a_host___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_parent_process_info___response_task"] [panel_group://workbench_panel_group_ransomware] label = Ransomware description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. disabled = 0 -panels = ["panel://workbench_panel_get_history_of_email_sources___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_sysmon_wmi_activity_for_host___response_task", "panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_parent_process_info___response_task", "panel://workbench_panel_get_process_information_for_port_activity___response_task", "panel://workbench_panel_get_backup_logs_for_endpoint___response_task"] +panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_process_information_for_port_activity___response_task", "panel://workbench_panel_get_sysmon_wmi_activity_for_host___response_task", "panel://workbench_panel_get_backup_logs_for_endpoint___response_task", "panel://workbench_panel_get_history_of_email_sources___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_parent_process_info___response_task"] [panel_group://workbench_panel_group_ransomware_cloud] label = Ransomware Cloud @@ -410,7 +424,7 @@ label = SamSam Ransomware description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. disabled = 0 -panels = ["panel://workbench_panel_get_history_of_email_sources___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_parent_process_info___response_task", "panel://workbench_panel_get_process_information_for_port_activity___response_task", "panel://workbench_panel_get_backup_logs_for_endpoint___response_task", "panel://workbench_panel_investigate_successful_remote_desktop_authentications___response_task"] +panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_process_information_for_port_activity___response_task", "panel://workbench_panel_get_backup_logs_for_endpoint___response_task", "panel://workbench_panel_get_history_of_email_sources___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_investigate_successful_remote_desktop_authentications___response_task", "panel://workbench_panel_get_parent_process_info___response_task"] [panel_group://workbench_panel_group_silver_sparrow] label = Silver Sparrow @@ -438,14 +452,14 @@ label = Splunk Enterprise Vulnerability CVE-2018-11409 description = Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. disabled = 0 -panels = ["panel://workbench_panel_investigate_network_traffic_from_src_ip___response_task", "panel://workbench_panel_get_notable_history___response_task"] +panels = ["panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_investigate_network_traffic_from_src_ip___response_task"] [panel_group://workbench_panel_group_suspicious_aws_ec2_activities] label = Suspicious AWS EC2 Activities description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. disabled = 0 -panels = ["panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_aws_investigate_security_hub_alerts_by_dest___response_task", "panel://workbench_panel_investigate_aws_activities_via_region_name___response_task", "panel://workbench_panel_get_ec2_launch_details___response_task", "panel://workbench_panel_aws_investigate_user_activities_by_arn___response_task", "panel://workbench_panel_get_ec2_instance_details_by_instanceid___response_task"] +panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn___response_task", "panel://workbench_panel_investigate_aws_activities_via_region_name___response_task", "panel://workbench_panel_get_ec2_launch_details___response_task", "panel://workbench_panel_aws_investigate_security_hub_alerts_by_dest___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_ec2_instance_details_by_instanceid___response_task"] [panel_group://workbench_panel_group_suspicious_aws_login_activities] label = Suspicious AWS Login Activities @@ -459,14 +473,14 @@ label = Suspicious AWS S3 Activities description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. disabled = 0 -panels = ["panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_investigate_aws_activities_via_region_name___response_task", "panel://workbench_panel_aws_investigate_user_activities_by_arn___response_task", "panel://workbench_panel_aws_s3_bucket_details_via_bucketname___response_task", "panel://workbench_panel_get_all_aws_activity_from_ip_address___response_task"] +panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn___response_task", "panel://workbench_panel_investigate_aws_activities_via_region_name___response_task", "panel://workbench_panel_get_all_aws_activity_from_ip_address___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_aws_s3_bucket_details_via_bucketname___response_task"] [panel_group://workbench_panel_group_suspicious_aws_traffic] label = Suspicious AWS Traffic description = Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). disabled = 0 -panels = ["panel://workbench_panel_get_dns_server_history_for_a_host___response_task", "panel://workbench_panel_aws_network_interface_details_via_resourceid___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic___response_task", "panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_dns_traffic_ratio___response_task", "panel://workbench_panel_aws_investigate_user_activities_by_arn___response_task", "panel://workbench_panel_get_process_information_for_port_activity___response_task", "panel://workbench_panel_aws_network_acl_details_from_id___response_task", "panel://workbench_panel_get_all_aws_activity_from_ip_address___response_task"] +panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn___response_task", "panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_aws_network_interface_details_via_resourceid___response_task", "panel://workbench_panel_get_dns_server_history_for_a_host___response_task", "panel://workbench_panel_get_process_information_for_port_activity___response_task", "panel://workbench_panel_get_all_aws_activity_from_ip_address___response_task", "panel://workbench_panel_get_dns_traffic_ratio___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic___response_task", "panel://workbench_panel_aws_network_acl_details_from_id___response_task"] [panel_group://workbench_panel_group_suspicious_cloud_authentication_activities] label = Suspicious Cloud Authentication Activities @@ -480,7 +494,7 @@ label = Suspicious Cloud Instance Activities description = Monitor your cloud infrastructure provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your cloud environment. disabled = 0 -panels = ["panel://workbench_panel_get_all_aws_activity_from_ip_address___response_task", "panel://workbench_panel_aws_investigate_user_activities_by_arn___response_task"] +panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn___response_task", "panel://workbench_panel_get_all_aws_activity_from_ip_address___response_task"] [panel_group://workbench_panel_group_suspicious_cloud_provisioning_activities] label = Suspicious Cloud Provisioning Activities @@ -501,21 +515,21 @@ label = Suspicious Command-Line Executions description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. disabled = 0 -panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_parent_process_info___response_task", "panel://workbench_panel_get_notable_history___response_task"] +panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_parent_process_info___response_task"] [panel_group://workbench_panel_group_suspicious_dns_traffic] label = Suspicious DNS Traffic description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. disabled = 0 -panels = ["panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_dns_server_history_for_a_host___response_task", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic___response_task", "panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_parent_process_info___response_task", "panel://workbench_panel_get_dns_traffic_ratio___response_task"] +panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_dns_server_history_for_a_host___response_task", "panel://workbench_panel_get_dns_traffic_ratio___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic___response_task", "panel://workbench_panel_get_parent_process_info___response_task"] [panel_group://workbench_panel_group_suspicious_emails] label = Suspicious Emails description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. disabled = 0 -panels = ["panel://workbench_panel_get_emails_from_specific_sender___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_email_info___response_task"] +panels = ["panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_emails_from_specific_sender___response_task", "panel://workbench_panel_get_email_info___response_task"] [panel_group://workbench_panel_group_suspicious_gcp_storage_activities] label = Suspicious GCP Storage Activities @@ -529,14 +543,14 @@ label = Suspicious MSHTA Activity description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. disabled = 0 -panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_parent_process_info___response_task", "panel://workbench_panel_get_notable_history___response_task"] +panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_parent_process_info___response_task"] [panel_group://workbench_panel_group_suspicious_okta_activity] label = Suspicious Okta Activity description = Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. Okta is a popular tool to manage multiple users and the web-based applications they need to stay productive. The searches in this story will help monitor your Okta environment for suspicious activities and associated user behaviors. disabled = 0 -panels = ["panel://workbench_panel_investigate_user_activities_in_okta___response_task", "panel://workbench_panel_investigate_okta_activity_by_app___response_task", "panel://workbench_panel_investigate_okta_activity_by_ip_address___response_task"] +panels = ["panel://workbench_panel_investigate_user_activities_in_okta___response_task", "panel://workbench_panel_investigate_okta_activity_by_ip_address___response_task", "panel://workbench_panel_investigate_okta_activity_by_app___response_task"] [panel_group://workbench_panel_group_suspicious_regsvr32_activity] label = Suspicious Regsvr32 Activity @@ -557,14 +571,14 @@ label = Suspicious WMI Use description = Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. disabled = 0 -panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_parent_process_info___response_task", "panel://workbench_panel_get_sysmon_wmi_activity_for_host___response_task", "panel://workbench_panel_get_notable_history___response_task"] +panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_sysmon_wmi_activity_for_host___response_task", "panel://workbench_panel_get_parent_process_info___response_task"] [panel_group://workbench_panel_group_suspicious_windows_registry_activities] label = Suspicious Windows Registry Activities description = Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. disabled = 0 -panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_parent_process_info___response_task", "panel://workbench_panel_get_notable_history___response_task"] +panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_parent_process_info___response_task"] [panel_group://workbench_panel_group_suspicious_zoom_child_processes] label = Suspicious Zoom Child Processes @@ -592,14 +606,14 @@ label = Unusual AWS EC2 Modifications description = Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. disabled = 0 -panels = ["panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_ec2_instance_details_by_instanceid___response_task", "panel://workbench_panel_aws_investigate_user_activities_by_arn___response_task"] +panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_ec2_instance_details_by_instanceid___response_task"] [panel_group://workbench_panel_group_unusual_processes] label = Unusual Processes description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. disabled = 0 -panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_parent_process_info___response_task", "panel://workbench_panel_get_notable_history___response_task"] +panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_parent_process_info___response_task"] [panel_group://workbench_panel_group_use_of_cleartext_protocols] label = Use of Cleartext Protocols @@ -613,7 +627,7 @@ label = Web Fraud Detection description = Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. disabled = 0 -panels = ["panel://workbench_panel_get_emails_from_specific_sender___response_task", "panel://workbench_panel_get_web_session_information_via_session_id___response_task", "panel://workbench_panel_get_notable_history___response_task"] +panels = ["panel://workbench_panel_get_emails_from_specific_sender___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_web_session_information_via_session_id___response_task"] [panel_group://workbench_panel_group_windows_dns_sigred_cve_2020_1350] label = Windows DNS SIGRed CVE-2020-1350 @@ -627,42 +641,42 @@ label = Windows Defense Evasion Tactics description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others disabled = 0 -panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_parent_process_info___response_task", "panel://workbench_panel_get_notable_history___response_task"] +panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_parent_process_info___response_task"] [panel_group://workbench_panel_group_windows_file_extension_and_association_abuse] label = Windows File Extension and Association Abuse description = Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. disabled = 0 -panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_parent_process_info___response_task", "panel://workbench_panel_get_notable_history___response_task"] +panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_parent_process_info___response_task"] [panel_group://workbench_panel_group_windows_log_manipulation] label = Windows Log Manipulation description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. disabled = 0 -panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_parent_process_info___response_task", "panel://workbench_panel_get_notable_history___response_task"] +panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_parent_process_info___response_task"] [panel_group://workbench_panel_group_windows_persistence_techniques] label = Windows Persistence Techniques description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. disabled = 0 -panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_parent_process_info___response_task", "panel://workbench_panel_get_notable_history___response_task"] +panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_parent_process_info___response_task"] [panel_group://workbench_panel_group_windows_privilege_escalation] label = Windows Privilege Escalation description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. disabled = 0 -panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_parent_process_info___response_task", "panel://workbench_panel_get_notable_history___response_task"] +panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_parent_process_info___response_task"] [panel_group://workbench_panel_group_windows_service_abuse] label = Windows Service Abuse description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. disabled = 0 -panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_parent_process_info___response_task", "panel://workbench_panel_get_notable_history___response_task"] +panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_get_parent_process_info___response_task"] diff --git a/dist/escu/default/macros.conf b/dist/escu/default/macros.conf index 45a3fda118..d66aaf8158 100644 --- a/dist/escu/default/macros.conf +++ b/dist/escu/default/macros.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security_content -# On Date: 2021-03-29T18:33:55 UTC +# On Date: 2021-04-14T19:13:35 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -335,6 +335,10 @@ description = Update this macro to limit the output results to filter out false definition = search * description = Update this macro to limit the output results to filter out false positives. +[aws_excessive_security_scanning_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + [aws_network_access_control_list_created_with_all_open_ports_filter] definition = search * description = Update this macro to limit the output results to filter out false positives. @@ -431,6 +435,14 @@ description = Update this macro to limit the output results to filter out false definition = search * description = Update this macro to limit the output results to filter out false positives. +[bits_job_persistence_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[bitsadmin_download_file_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + [batch_file_write_to_system32_filter] definition = search * description = Update this macro to limit the output results to filter out false positives. @@ -575,6 +587,10 @@ description = Update this macro to limit the output results to filter out false definition = search * description = Update this macro to limit the output results to filter out false positives. +[dsquery_domain_discovery_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + [deleting_shadow_copies_filter] definition = search * description = Update this macro to limit the output results to filter out false positives. @@ -903,10 +919,54 @@ description = Update this macro to limit the output results to filter out false definition = search * description = Update this macro to limit the output results to filter out false positives. +[disable_registry_tool_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[disable_show_hidden_files_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[disable_windows_behavior_monitoring_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[disable_windows_smartscreen_protection_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[disabling_cmd_application_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[disabling_controlpanel_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[disabling_firewall_with_netsh_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[disabling_folderoptions_windows_feature_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[disabling_norun_windows_app_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + [disabling_remote_user_account_control_filter] definition = search * description = Update this macro to limit the output results to filter out false positives. +[disabling_systemrestore_in_registry_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[disabling_task_manager_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + [dump_lsass_via_comsvcs_dll_filter] definition = search * description = Update this macro to limit the output results to filter out false positives. @@ -1147,6 +1207,10 @@ description = Update this macro to limit the output results to filter out false definition = search * description = Update this macro to limit the output results to filter out false positives. +[malicious_powershell_executed_as_a_service_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + [monitor_dns_for_brand_abuse_filter] definition = search * description = Update this macro to limit the output results to filter out false positives. @@ -1255,6 +1319,10 @@ description = Update this macro to limit the output results to filter out false definition = search * description = Update this macro to limit the output results to filter out false positives. +[powershell_start_bitstransfer_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + [process_creating_lnk_file_in_suspicious_location_filter] definition = search * description = Update this macro to limit the output results to filter out false positives. diff --git a/dist/escu/default/savedsearches.conf b/dist/escu/default/savedsearches.conf index a88a9f3d30..0a839a5ab7 100644 --- a/dist/escu/default/savedsearches.conf +++ b/dist/escu/default/savedsearches.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security_content -# On Date: 2021-03-29T18:33:55 UTC +# On Date: 2021-04-14T19:13:35 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -37,6 +37,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule action.correlationsearch.annotations = {"analytic_story": ["AWS Suspicious Provisioning Activities"], "cis20": ["CIS 1"], "mitre_attack": ["T1535"], "nist": ["ID.AM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search looks for AWS provisioning activities from previously unseen cities. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." This search is deprecated and have been translated to use the latest Change Datamodel. +action.notable.param.rule_title = AWS Cloud Provisioning From Previously Unseen City +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -72,6 +78,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule action.correlationsearch.annotations = {"analytic_story": ["AWS Suspicious Provisioning Activities"], "cis20": ["CIS 1"], "mitre_attack": ["T1535"], "nist": ["ID.AM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search looks for AWS provisioning activities from previously unseen countries. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." This search is deprecated and have been translated to use the latest Change Datamodel. +action.notable.param.rule_title = AWS Cloud Provisioning From Previously Unseen Country +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -107,6 +119,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule action.correlationsearch.annotations = {"analytic_story": ["AWS Suspicious Provisioning Activities"], "cis20": ["CIS 1"], "nist": ["ID.AM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search looks for AWS provisioning activities from previously unseen IP addresses. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." This search is deprecated and have been translated to use the latest Change Datamodel. +action.notable.param.rule_title = AWS Cloud Provisioning From Previously Unseen IP Address +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -142,6 +160,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule action.correlationsearch.annotations = {"analytic_story": ["AWS Suspicious Provisioning Activities"], "cis20": ["CIS 1"], "mitre_attack": ["T1535"], "nist": ["ID.AM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search looks for AWS provisioning activities from previously unseen regions. Region in this context is similar to a state in the United States. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." This search is deprecated and have been translated to use the latest Change Datamodel. +action.notable.param.rule_title = AWS Cloud Provisioning From Previously Unseen Region +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -410,6 +434,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - AWS EKS Kubernetes cluster sensitive object access - Rule action.correlationsearch.annotations = {"analytic_story": ["Kubernetes Sensitive Object Access Activity"], "kill_chain_phases": ["Lateral Movement"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search provides information on Kubernetes accounts accessing sensitve objects such as configmaps or secrets +action.notable.param.rule_title = AWS EKS Kubernetes cluster sensitive object access +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -420,6 +449,45 @@ realtime_schedule = 0 is_visible = false search = `aws_cloudwatchlogs_eks` objectRef.resource=secrets OR configmaps sourceIPs{}!=::1 sourceIPs{}!=127.0.0.1 |table sourceIPs{} user.username user.groups{} objectRef.resource objectRef.namespace objectRef.name annotations.authorization.k8s.io/reason |dedup user.username user.groups{} |`aws_eks_kubernetes_cluster_sensitive_object_access_filter` +[ESCU - AWS Excessive Security Scanning - Rule] +action.escu = 0 +action.escu.enabled = 1 +description = This search looks for CloudTrail events and analyse the amount of eventNames which starts with Describe by a single user. This indicates that this user scans the configuration of your AWS cloud environment. +action.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1526"], "nist": ["PR.DS", "PR.AC", "DE.CM"]} +action.escu.data_models = [] +action.escu.eli5 = This search looks for CloudTrail events and analyse the amount of eventNames which starts with Describe by a single user. This indicates that this user scans the configuration of your AWS cloud environment. +action.escu.how_to_implement = You must install splunk AWS add on and Splunk App for AWS. This search works with cloudtrail logs. +action.escu.known_false_positives = While this search has no known false positives. +action.escu.creation_date = 2021-04-13 +action.escu.modification_date = 2021-04-13 +action.escu.confidence = high +action.escu.full_search_name = ESCU - AWS Excessive Security Scanning - Rule +action.escu.search_type = detection +action.escu.product = ["Splunk Security Analytics for AWS", "Splunk Enterprise", "Splunk Enterprise Security", "Splunk Cloud"] +action.escu.providing_technologies = [] +action.escu.analytic_story = ["AWS User Monitoring"] +action.risk = 1 +action.risk.param._risk_object = src +action.risk.param._risk_object_type = system +action.risk.param._risk_score = 20 +action.risk.param.verbose = 0 +cron_schedule = 0 * * * * +dispatch.earliest_time = -70m@m +dispatch.latest_time = -10m@m +action.correlationsearch.enabled = 1 +action.correlationsearch.label = ESCU - AWS Excessive Security Scanning - Rule +action.correlationsearch.annotations = {"analytic_story": ["AWS User Monitoring"], "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1526"], "nist": ["PR.DS", "PR.AC", "DE.CM"]} +schedule_window = auto +alert.digest_mode = 1 +disabled = true +enableSched = 1 +counttype = number of events +relation = greater than +quantity = 0 +realtime_schedule = 0 +is_visible = false +search = `cloudtrail` eventName=Describe* OR eventName=List* OR eventName=Get* | stats dc(eventName) as dc_events min(_time) as firstTime max(_time) as lastTime values(eventName) as eventName values(src) as src values(userAgent) as userAgent by user userIdentity.arn | where dc_events > 50 | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`|`aws_excessive_security_scanning_filter` + [ESCU - AWS Network Access Control List Created with All Open Ports - Rule] action.escu = 0 action.escu.enabled = 1 @@ -683,6 +751,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Abnormally High AWS Instances Launched by User - Rule action.correlationsearch.annotations = {"analytic_story": ["AWS Cryptomining", "Suspicious AWS EC2 Activities"], "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078.004"], "nist": ["DE.DP", "DE.AE"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search looks for CloudTrail events where a user successfully launches an abnormally high number of instances. This search is deprecated and have been translated to use the latest Change Datamodel +action.notable.param.rule_title = Abnormally High AWS Instances Launched by User +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -722,6 +795,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule action.correlationsearch.annotations = {"analytic_story": ["AWS Cryptomining", "Suspicious AWS EC2 Activities"], "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078.004"], "nist": ["DE.DP", "DE.AE"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search looks for CloudTrail events where a user successfully launches an abnormally high number of instances. This search is deprecated and have been translated to use the latest Change Datamodel. +action.notable.param.rule_title = Abnormally High AWS Instances Launched by User - MLTK +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -756,6 +835,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Abnormally High AWS Instances Terminated by User - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious AWS EC2 Activities"], "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078.004"], "nist": ["DE.DP", "DE.AE"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search looks for CloudTrail events where an abnormally high number of instances were successfully terminated by a user in a 10-minute window. This search is deprecated and have been translated to use the latest Change Datamodel. +action.notable.param.rule_title = Abnormally High AWS Instances Terminated by User +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -790,6 +874,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious AWS EC2 Activities"], "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078.004"], "nist": ["DE.DP", "DE.AE"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search looks for CloudTrail events where a user successfully terminates an abnormally high number of instances. This search is deprecated and have been translated to use the latest Change Datamodel. +action.notable.param.rule_title = Abnormally High AWS Instances Terminated by User - MLTK +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -974,18 +1064,12 @@ action.escu.product = ["Splunk Enterprise", "Splunk Enterprise Security", "Splun action.escu.providing_technologies = [] action.escu.analytic_story = ["Credential Dumping"] cron_schedule = 0 * * * * -dispatch.earliest_time = -30m@m -dispatch.latest_time = now +dispatch.earliest_time = -40m@m +dispatch.latest_time = -10m@m action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Access LSASS Memory for Dump Creation - Rule action.correlationsearch.annotations = {"analytic_story": ["Credential Dumping"], "cis20": ["CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003.001"], "nist": ["DE.CM"]} schedule_window = auto -action.notable = 1 -action.notable.param.nes_fields = ['dest'] -action.notable.param.rule_description = Detect memory dumping of the LSASS process. -action.notable.param.rule_title = Access LSASS Memory for Dump Creation Notable -action.notable.param.security_domain = endpoint -action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -1020,6 +1104,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Amazon EKS Kubernetes Pod scan detection - Rule action.correlationsearch.annotations = {"analytic_story": ["Kubernetes Scanning Activity"], "kill_chain_phases": ["Reconnaissance"], "mitre_attack": ["T1526"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search provides detection information on unauthenticated requests against Kubernetes' Pods API +action.notable.param.rule_title = Amazon EKS Kubernetes Pod scan detection +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -1054,6 +1143,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Amazon EKS Kubernetes cluster scan detection - Rule action.correlationsearch.annotations = {"analytic_story": ["Kubernetes Scanning Activity"], "kill_chain_phases": ["Reconnaissance"], "mitre_attack": ["T1526"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster in AWS +action.notable.param.rule_title = Amazon EKS Kubernetes cluster scan detection +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -1080,14 +1174,20 @@ action.escu.full_search_name = ESCU - Any Powershell DownloadFile - Rule action.escu.search_type = detection action.escu.product = ["Splunk Enterprise", "Splunk Enterprise Security", "Splunk Cloud"] action.escu.providing_technologies = [] -action.escu.analytic_story = ["Malicious PowerShell"] +action.escu.analytic_story = ["Malicious PowerShell", "Ingress Tool Transfer"] cron_schedule = 0 * * * * dispatch.earliest_time = -70m@m dispatch.latest_time = -10m@m action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Any Powershell DownloadFile - Rule -action.correlationsearch.annotations = {"analytic_story": ["Malicious PowerShell"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1059.001"]} +action.correlationsearch.annotations = {"analytic_story": ["Malicious PowerShell", "Ingress Tool Transfer"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1059.001"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The following analytic identifies the use of PowerShell downloading a file using `DownloadFile` method. This particular method is utilized in many different PowerShell frameworks to download files and output to disk. Identify the source (IP/domain) and destination file and triage appropriately. If AMSI logging or PowerShell transaction logs are available, review for further details of the implant. +action.notable.param.rule_title = Any Powershell DownloadFile +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -1114,14 +1214,20 @@ action.escu.full_search_name = ESCU - Any Powershell DownloadString - Rule action.escu.search_type = detection action.escu.product = ["Splunk Enterprise", "Splunk Enterprise Security", "Splunk Cloud"] action.escu.providing_technologies = [] -action.escu.analytic_story = ["Malicious PowerShell", "HAFNIUM Group"] +action.escu.analytic_story = ["Malicious PowerShell", "HAFNIUM Group", "Ingress Tool Transfer"] cron_schedule = 0 * * * * dispatch.earliest_time = -70m@m dispatch.latest_time = -10m@m action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Any Powershell DownloadString - Rule -action.correlationsearch.annotations = {"analytic_story": ["Malicious PowerShell", "HAFNIUM Group"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1059.001"]} +action.correlationsearch.annotations = {"analytic_story": ["Malicious PowerShell", "HAFNIUM Group", "Ingress Tool Transfer"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1059.001"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The following analytic identifies the use of PowerShell downloading a file using `DownloadString` method. This particular method is utilized in many different PowerShell frameworks to download files and output to disk. Identify the source (IP/domain) and destination file and triage appropriately. If AMSI logging or PowerShell transaction logs are available, review for further details of the implant. +action.notable.param.rule_title = Any Powershell DownloadString +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -1156,6 +1262,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Attempt To Add Certificate To Untrusted Store - Rule action.correlationsearch.annotations = {"analytic_story": ["Disabling Security Tools"], "cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1553.004"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = Attempt To Add Certificate To Untrusted Store +action.notable.param.rule_title = Attempt To Add Certificate To Untrusted Store +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -1184,7 +1296,7 @@ action.escu.product = ["Splunk Enterprise", "Splunk Enterprise Security", "Splun action.escu.providing_technologies = [] action.escu.analytic_story = ["Malicious PowerShell", "Credential Dumping", "HAFNIUM Group"] cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m +dispatch.earliest_time = -40m@m dispatch.latest_time = -10m@m action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule @@ -1224,6 +1336,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Attempt To Stop Security Service - Rule action.correlationsearch.annotations = {"analytic_story": ["Disabling Security Tools"], "cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1562.001"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for attempts to stop security-related services on the endpoint. +action.notable.param.rule_title = Attempt To Stop Security Service +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -1252,7 +1370,7 @@ action.escu.product = ["Splunk Enterprise", "Splunk Enterprise Security", "Splun action.escu.providing_technologies = [] action.escu.analytic_story = ["Credential Dumping"] cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m +dispatch.earliest_time = -40m@m dispatch.latest_time = -10m@m action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Attempted Credential Dump From Registry via Reg exe - Rule @@ -1292,6 +1410,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - BCDEdit Failure Recovery Modification - Rule action.correlationsearch.annotations = {"analytic_story": ["Ryuk Ransomware", "Ransomware"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1490"], "nist": ["PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for flags passed to bcdedit.exe modifications to the built-in Windows error recovery boot configurations. This is typically used by ransomware to prevent recovery. +action.notable.param.rule_title = BCDEdit Failure Recovery Modification +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -1302,6 +1426,86 @@ realtime_schedule = 0 is_visible = false search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = bcdedit.exe Processes.process="*recoveryenabled*" (Processes.process="* no*") by Processes.process_name Processes.process Processes.parent_process_name Processes.dest Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `bcdedit_failure_recovery_modification_filter` +[ESCU - BITS Job Persistence - Rule] +action.escu = 0 +action.escu.enabled = 1 +description = The following query identifies Microsoft Background Intelligent Transfer Service utility `bitsadmin.exe` scheduling a BITS job to persist on an endpoint. The query identifies the parameters used to create, resume or add a file to a BITS job. Typically seen combined in a oneliner or ran in sequence. If identified, review the BITS job created and capture any files written to disk. It is possible for BITS to be used to upload files and this may require further network data analysis to identify. You can use `bitsadmin /list /verbose` to list out the jobs during investigation. +action.escu.mappings = {"kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1197"]} +action.escu.data_models = ["Endpoint"] +action.escu.eli5 = The following query identifies Microsoft Background Intelligent Transfer Service utility `bitsadmin.exe` scheduling a BITS job to persist on an endpoint. The query identifies the parameters used to create, resume or add a file to a BITS job. Typically seen combined in a oneliner or ran in sequence. If identified, review the BITS job created and capture any files written to disk. It is possible for BITS to be used to upload files and this may require further network data analysis to identify. You can use `bitsadmin /list /verbose` to list out the jobs during investigation. +action.escu.how_to_implement = To successfully implement this search you need to be ingesting information on process that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` node. +action.escu.known_false_positives = Limited false positives will be present. Typically, applications will use `BitsAdmin.exe`. Any filtering should be done based on command-line arguments (legitimate applications) or parent process. +action.escu.creation_date = 2021-03-29 +action.escu.modification_date = 2021-03-29 +action.escu.confidence = high +action.escu.full_search_name = ESCU - BITS Job Persistence - Rule +action.escu.search_type = detection +action.escu.product = ["Splunk Enterprise", "Splunk Enterprise Security", "Splunk Cloud"] +action.escu.providing_technologies = [] +action.escu.analytic_story = ["BITS Jobs"] +cron_schedule = 0 * * * * +dispatch.earliest_time = -70m@m +dispatch.latest_time = -10m@m +action.correlationsearch.enabled = 1 +action.correlationsearch.label = ESCU - BITS Job Persistence - Rule +action.correlationsearch.annotations = {"analytic_story": ["BITS Jobs"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1197"]} +schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The following query identifies Microsoft Background Intelligent Transfer Service utility `bitsadmin.exe` scheduling a BITS job to persist on an endpoint. The query identifies the parameters used to create, resume or add a file to a BITS job. Typically seen combined in a oneliner or ran in sequence. If identified, review the BITS job created and capture any files written to disk. It is possible for BITS to be used to upload files and this may require further network data analysis to identify. You can use `bitsadmin /list /verbose` to list out the jobs during investigation. +action.notable.param.rule_title = BITS Job Persistence +action.notable.param.security_domain = endpoint +action.notable.param.severity = high +alert.digest_mode = 1 +disabled = true +enableSched = 1 +counttype = number of events +relation = greater than +quantity = 0 +realtime_schedule = 0 +is_visible = false +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=bitsadmin.exe Processes.process IN (*create*, *addfile*, *setnotifyflags*, *setnotifycmdline*, *setminretrydelay*, *setcustomheaders*, *resume* ) by Processes.dest Processes.user Processes.parent_process Processes.process_name Processes.process Processes.process_id Processes.parent_process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `bits_job_persistence_filter` + +[ESCU - BITSAdmin Download File - Rule] +action.escu = 0 +action.escu.enabled = 1 +description = The following query identifies Microsoft Background Intelligent Transfer Service utility `bitsadmin.exe` using the `transfer` parameter to download a remote object. In addition, look for `download` or `upload` on the command-line, the switches are not required to perform a transfer. Capture any files downloaded. Review the reputation of the IP or domain used. Typically once executed, a follow on command will be used to execute the dropped file. Note that the network connection or file modification events related will not spawn or create from `bitsadmin.exe`, but the artifacts will appear in a parallel process of `svchost.exe` with a command-line similar to `svchost.exe -k netsvcs -s BITS`. It's important to review all parallel and child processes to capture any behaviors and artifacts. In some suspicious and malicious instances, BITS jobs will be created. You can use `bitsadmin /list /verbose` to list out the jobs during investigation. +action.escu.mappings = {"kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1197", "T1105"]} +action.escu.data_models = ["Endpoint"] +action.escu.eli5 = The following query identifies Microsoft Background Intelligent Transfer Service utility `bitsadmin.exe` using the `transfer` parameter to download a remote object. In addition, look for `download` or `upload` on the command-line, the switches are not required to perform a transfer. Capture any files downloaded. Review the reputation of the IP or domain used. Typically once executed, a follow on command will be used to execute the dropped file. Note that the network connection or file modification events related will not spawn or create from `bitsadmin.exe`, but the artifacts will appear in a parallel process of `svchost.exe` with a command-line similar to `svchost.exe -k netsvcs -s BITS`. It's important to review all parallel and child processes to capture any behaviors and artifacts. In some suspicious and malicious instances, BITS jobs will be created. You can use `bitsadmin /list /verbose` to list out the jobs during investigation. +action.escu.how_to_implement = To successfully implement this search you need to be ingesting information on process that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` node. +action.escu.known_false_positives = Limited false positives, however it may be required to filter based on parent process name or network connection. +action.escu.creation_date = 2021-03-26 +action.escu.modification_date = 2021-03-26 +action.escu.confidence = high +action.escu.full_search_name = ESCU - BITSAdmin Download File - Rule +action.escu.search_type = detection +action.escu.product = ["Splunk Enterprise", "Splunk Enterprise Security", "Splunk Cloud"] +action.escu.providing_technologies = [] +action.escu.analytic_story = ["Ingress Tool Transfer", "BITS Jobs"] +cron_schedule = 0 * * * * +dispatch.earliest_time = -70m@m +dispatch.latest_time = -10m@m +action.correlationsearch.enabled = 1 +action.correlationsearch.label = ESCU - BITSAdmin Download File - Rule +action.correlationsearch.annotations = {"analytic_story": ["Ingress Tool Transfer", "BITS Jobs"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1197", "T1105"]} +schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The following query identifies Microsoft Background Intelligent Transfer Service utility `bitsadmin.exe` using the `transfer` parameter to download a remote object. In addition, look for `download` or `upload` on the command-line, the switches are not required to perform a transfer. Capture any files downloaded. Review the reputation of the IP or domain used. Typically once executed, a follow on command will be used to execute the dropped file. Note that the network connection or file modification events related will not spawn or create from `bitsadmin.exe`, but the artifacts will appear in a parallel process of `svchost.exe` with a command-line similar to `svchost.exe -k netsvcs -s BITS`. It's important to review all parallel and child processes to capture any behaviors and artifacts. In some suspicious and malicious instances, BITS jobs will be created. You can use `bitsadmin /list /verbose` to list out the jobs during investigation. +action.notable.param.rule_title = BITSAdmin Download File +action.notable.param.security_domain = endpoint +action.notable.param.severity = high +alert.digest_mode = 1 +disabled = true +enableSched = 1 +counttype = number of events +relation = greater than +quantity = 0 +realtime_schedule = 0 +is_visible = false +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=bitsadmin.exe Processes.process=*transfer* by Processes.dest Processes.user Processes.parent_process Processes.process_name Processes.process Processes.process_id Processes.parent_process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `bitsadmin_download_file_filter` + [ESCU - Batch File Write to System32 - Rule] action.escu = 0 action.escu.enabled = 1 @@ -1326,6 +1530,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Batch File Write to System32 - Rule action.correlationsearch.annotations = {"analytic_story": ["SamSam Ransomware"], "cis20": ["CIS 8"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1204.002"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The search looks for a batch file (.bat) written to the Windows system directory tree. +action.notable.param.rule_title = Batch File Write to System32 +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -1360,6 +1570,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - CertUtil Download With URLCache and Split Arguments - Rule action.correlationsearch.annotations = {"analytic_story": ["Ingress Tool Transfer"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1105"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = Certutil.exe may download a file from a remote destination using `-urlcache`. This behavior does require a URL to be passed on the command-line. In addition, `-f` (force) and `-split` (Split embedded ASN.1 elements, and save to files) will be used. It is not entirely common for `certutil.exe` to contact public IP space. However, it is uncommon for `certutil.exe` to write files to world writeable paths.\ During triage, capture any files on disk and review. Review the reputation of the remote IP or domain in question. +action.notable.param.rule_title = CertUtil Download With URLCache and Split Arguments +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -1394,6 +1610,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - CertUtil Download With VerifyCtl and Split Arguments - Rule action.correlationsearch.annotations = {"analytic_story": ["Ingress Tool Transfer"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1105"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = Certutil.exe may download a file from a remote destination using `-VerifyCtl`. This behavior does require a URL to be passed on the command-line. In addition, `-f` (force) and `-split` (Split embedded ASN.1 elements, and save to files) will be used. It is not entirely common for `certutil.exe` to contact public IP space. \ During triage, capture any files on disk and review. Review the reputation of the remote IP or domain in question. Using `-VerifyCtl`, the file will either be written to the current working directory or `%APPDATA%\..\LocalLow\Microsoft\CryptnetUrlCache\Content\`. +action.notable.param.rule_title = CertUtil Download With VerifyCtl and Split Arguments +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -1428,6 +1650,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - CertUtil With Decode Argument - Rule action.correlationsearch.annotations = {"analytic_story": ["Deobfuscate-Decode Files or Information"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1140"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = CertUtil.exe may be used to `encode` and `decode` a file, including PE and script code. Encoding will convert a file to base64 with `-----BEGIN CERTIFICATE-----` and `-----END CERTIFICATE-----` tags. Malicious usage will include decoding a encoded file that was downloaded. Once decoded, it will be loaded by a parallel process. Note that there are two additional command switches that may be used - `encodehex` and `decodehex`. Similarly, the file will be encoded in HEX and later decoded for further execution. During triage, identify the source of the file being decoded. Review its contents or execution behavior for further analysis. +action.notable.param.rule_title = CertUtil With Decode Argument +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -1462,6 +1690,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Certutil exe certificate extraction - Rule action.correlationsearch.annotations = {"analytic_story": ["Windows Persistence Techniques", "Cloud Federated Credential Abuse"], "kill_chain_phases": ["Installation"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search looks for arguments to certutil.exe indicating the manipulation or extraction of Certificate. This certificate can then be used to sign new authentication tokens specially inside Federated environments such as Windows ADFS. +action.notable.param.rule_title = Certutil exe certificate extraction +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -1496,6 +1730,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Child Processes of Spoolsv exe - Rule action.correlationsearch.annotations = {"analytic_story": ["Windows Privilege Escalation"], "cis20": ["CIS 5", "CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1068"], "nist": ["PR.AC", "PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for child processes of spoolsv.exe. This activity is associated with a POC privilege-escalation exploit associated with CVE-2018-8440. Spoolsv.exe is the process associated with the Print Spooler service in Windows and typically runs as SYSTEM. +action.notable.param.rule_title = Child Processes of Spoolsv exe +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -1532,6 +1772,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Clients Connecting to Multiple DNS Servers - Rule action.correlationsearch.annotations = {"analytic_story": ["DNS Hijacking", "Command and Control", "Suspicious DNS Traffic", "Host Redirection"], "cis20": ["CIS 9", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048.003"], "nist": ["PR.PT", "DE.AE", "PR.DS"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest', 'src'] +action.notable.param.rule_description = This search allows you to identify the endpoints that have connected to more than five DNS servers and made DNS Queries over the time frame of the search. +action.notable.param.rule_title = Clients Connecting to Multiple DNS Servers +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -1566,6 +1812,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Clop Common Exec Parameter - Rule action.correlationsearch.annotations = {"analytic_story": ["Clop Ransomware"], "kill_chain_phases": ["Obfuscation"], "mitre_attack": ["T1204"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The following analytics are designed to identifies some CLOP ransomware variant that using arguments to execute its main code or feature of its code. In this variant if the parameter is "runrun", CLOP ransomware will try to encrypt files in network shares and if it is "temp.dat", it will try to read from some stream pipe or file start encrypting files within the infected local machines. This technique can be also identified as an anti-sandbox technique to make its code non-responsive since it is waiting for some parameter to execute properly. +action.notable.param.rule_title = Clop Common Exec Parameter +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -1574,7 +1826,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` values(Processes.process) as cmdline values(Processes.parent_process_name) as parent_process values(Processes.process_name) count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process = "*runrun*" OR Processes.process = "*temp.dat*" by Processes.parent_process_name Processes.process_name Processes.process Processes.dest Processes.user Processes.process_id Processes.process_guid | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `clop_common_exec_parameter_filter` +search = | tstats `security_content_summariesonly` values(Processes.process) as cmdline values(Processes.parent_process_name) as parent_process values(Processes.process_name) count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name != "*temp.dat*" Processes.process = "*runrun*" OR Processes.process = "*temp.dat*" by Processes.parent_process_name Processes.process_name Processes.process Processes.dest Processes.user Processes.process_id Processes.process_guid | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `clop_common_exec_parameter_filter` [ESCU - Clop Ransomware Known Service Name - Rule] action.escu = 0 @@ -1600,6 +1852,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Clop Ransomware Known Service Name - Rule action.correlationsearch.annotations = {"analytic_story": ["Clop Ransomware"], "kill_chain_phases": ["Privilege Escalation"], "mitre_attack": ["T1543"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This detection is to identify the common service name created by the CLOP ransomware as part of its persistence and high privilege code execution in the infected machine. Ussually CLOP ransomware use StartServiceCtrlDispatcherW API in creating this service entry. +action.notable.param.rule_title = Clop Ransomware Known Service Name +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -1868,6 +2125,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Cloud Network Access Control List Deleted - Rule action.correlationsearch.annotations = {"analytic_story": ["Cloud Network ACL Activity"], "cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['src'] +action.notable.param.rule_description = Enforcing network-access controls is one of the defensive mechanisms used by cloud administrators to restrict access to a cloud instance. After the attacker has gained control of the console by compromising an admin account, they can delete a network ACL and gain access to the instance from anywhere. This search will query the Change datamodel to detect users deleting network ACLs. Deprecated because it's a duplicate +action.notable.param.rule_title = Cloud Network Access Control List Deleted +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -2064,6 +2327,13 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Cobalt Strike Named Pipes - Rule action.correlationsearch.annotations = {"analytic_story": ["Cobalt Strike"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1055"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The following analytic identifies the use of default or publicly known named pipes used with Cobalt Strike. A named pipe is a named, one-way or duplex pipe for communication between the pipe server and one or more pipe clients. Cobalt Strike uses named pipes in many ways and has default values used with the Artifact Kit and Malleable C2 Profiles. The following query assists with identifying these default named pipes. Each EDR product presents named pipes a little different. Consider taking the values and generating a query based on the product of choice. \ +Upon triage, review the process performing the named pipe. If it is explorer.exe, It is possible it was injected into by another process. Review recent parallel processes to identify suspicious patterns or behaviors. A parallel process may have a network connection, review and follow the connection back to identify any file modifications. +action.notable.param.rule_title = Cobalt Strike Named Pipes +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -2102,6 +2372,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Common Ransomware Extensions - Rule action.correlationsearch.annotations = {"analytic_story": ["SamSam Ransomware", "Ryuk Ransomware", "Ransomware", "Clop Ransomware"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1485"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The search looks for file modifications with extensions commonly used by Ransomware +action.notable.param.rule_title = Common Ransomware Extensions +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -2136,6 +2412,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Common Ransomware Notes - Rule action.correlationsearch.annotations = {"analytic_story": ["SamSam Ransomware", "Ransomware", "Ryuk Ransomware", "Clop Ransomware"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1485"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The search looks for files created with names matching those typically used in ransomware notes that tell the victim how to get their data back. +action.notable.param.rule_title = Common Ransomware Notes +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -2164,7 +2446,7 @@ action.escu.product = ["Splunk Enterprise", "Splunk Enterprise Security", "Splun action.escu.providing_technologies = [] action.escu.analytic_story = ["Credential Dumping"] cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m +dispatch.earliest_time = -40m@m dispatch.latest_time = -10m@m action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Create Remote Thread into LSASS - Rule @@ -2204,6 +2486,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Create Service In Suspicious File Path - Rule action.correlationsearch.annotations = {"analytic_story": ["Clop Ransomware"], "kill_chain_phases": ["Privilege Escalation"], "mitre_attack": ["T1569.001", "T1569.002"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This detection is to identify a creation of "user mode service" where the service file path is located in non-common service folder in windows. +action.notable.param.rule_title = Create Service In Suspicious File Path +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -2238,6 +2526,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Create local admin accounts using net exe - Rule action.correlationsearch.annotations = {"analytic_story": ["DHS Report TA18-074A"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1136.001"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for the creation of local administrator accounts using net.exe. +action.notable.param.rule_title = Create local admin accounts using net exe +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -2272,6 +2566,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Create or delete windows shares using net exe - Rule action.correlationsearch.annotations = {"analytic_story": ["Hidden Cobra Malware"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070.005"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for the creation or deletion of hidden shares using net.exe. +action.notable.param.rule_title = Create or delete windows shares using net exe +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -2300,7 +2600,7 @@ action.escu.product = ["Splunk Enterprise", "Splunk Enterprise Security", "Splun action.escu.providing_technologies = [] action.escu.analytic_story = ["Credential Dumping"] cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m +dispatch.earliest_time = -40m@m dispatch.latest_time = -10m@m action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Creation of Shadow Copy - Rule @@ -2334,7 +2634,7 @@ action.escu.product = ["Splunk Enterprise", "Splunk Enterprise Security", "Splun action.escu.providing_technologies = [] action.escu.analytic_story = ["Credential Dumping"] cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m +dispatch.earliest_time = -40m@m dispatch.latest_time = -10m@m action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Creation of Shadow Copy with wmic and powershell - Rule @@ -2368,7 +2668,7 @@ action.escu.product = ["Splunk Enterprise", "Splunk Enterprise Security", "Splun action.escu.providing_technologies = [] action.escu.analytic_story = ["Credential Dumping"] cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m +dispatch.earliest_time = -40m@m dispatch.latest_time = -10m@m action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Creation of lsass Dump with Taskmgr - Rule @@ -2402,7 +2702,7 @@ action.escu.product = ["Splunk Enterprise", "Splunk Enterprise Security", "Splun action.escu.providing_technologies = [] action.escu.analytic_story = ["Credential Dumping"] cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m +dispatch.earliest_time = -40m@m dispatch.latest_time = -10m@m action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule @@ -2436,7 +2736,7 @@ action.escu.product = ["Splunk Enterprise", "Splunk Enterprise Security", "Splun action.escu.providing_technologies = [] action.escu.analytic_story = ["Credential Dumping"] cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m +dispatch.earliest_time = -40m@m dispatch.latest_time = -10m@m action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Credential Dumping via Symlink to Shadow Copy - Rule @@ -2482,6 +2782,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - DNS Query Length Outliers - MLTK - Rule action.correlationsearch.annotations = {"analytic_story": ["Hidden Cobra Malware", "Suspicious DNS Traffic", "Command and Control"], "cis20": ["CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1071.004"], "nist": ["PR.PT", "DE.AE", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest', 'src'] +action.notable.param.rule_description = This search allows you to identify DNS requests that are unusually large for the record type being requested in your environment. +action.notable.param.rule_title = DNS Query Length Outliers - MLTK +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -2516,6 +2822,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - DNS Query Length With High Standard Deviation - Rule action.correlationsearch.annotations = {"analytic_story": ["Hidden Cobra Malware", "Suspicious DNS Traffic", "Command and Control"], "cis20": ["CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048.003"], "nist": ["PR.PT", "DE.AE", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search allows you to identify DNS requests and compute the standard deviation on the length of the names being resolved, then filter on two times the standard deviation to show you those queries that are unusually large for your environment. +action.notable.param.rule_title = DNS Query Length With High Standard Deviation +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -2550,6 +2861,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule action.correlationsearch.annotations = {"analytic_story": ["DNS Hijacking", "Command and Control", "Suspicious DNS Traffic", "Host Redirection"], "cis20": ["CIS 1", "CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1071.004"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest', 'src'] +action.notable.param.rule_description = This search will detect DNS requests resolved by unauthorized DNS servers. Legitimate DNS servers should be identified in the Enterprise Security Assets and Identity Framework. +action.notable.param.rule_title = DNS Query Requests Resolved by Unauthorized DNS Servers +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -2588,6 +2905,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - DNS record changed - Rule action.correlationsearch.annotations = {"analytic_story": ["DNS Hijacking"], "cis20": ["CIS 1", "CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1071.004"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['src'] +action.notable.param.rule_description = The search takes the DNS records and their answers results of the discovered_dns_records lookup and finds if any records have changed by searching DNS response from the Network_Resolution datamodel across the last day. +action.notable.param.rule_title = DNS record changed +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -2598,6 +2921,61 @@ realtime_schedule = 0 is_visible = false search = | inputlookup discovered_dns_records | rename answer as discovered_answer | join domain[|tstats `security_content_summariesonly` count values(DNS.record_type) as type, values(DNS.answer) as current_answer values(DNS.src) as src from datamodel=Network_Resolution where DNS.message_type=RESPONSE DNS.answer!="unknown" DNS.answer!="" by DNS.query | rename DNS.query as query | where query!="unknown" | rex field=query "(?\w+\.\w+?)(?:$|/)"] | makemv delim=" " answer | makemv delim=" " type | sort -count | table count,src,domain,type,query,current_answer,discovered_answer | makemv current_answer | mvexpand current_answer | makemv discovered_answer | eval n=mvfind(discovered_answer, current_answer) | where isnull(n) | `dns_record_changed_filter` +[ESCU - DSQuery Domain Discovery - Rule] +action.escu = 0 +action.escu.enabled = 1 +description = The following analytic identifies "dsquery.exe" execution with arguments looking for `TrustedDomain` query directly on the command-line. This is typically indicative of an Administrator or adversary perform domain trust discovery. Note that this query does not identify any other variations of "Dsquery.exe" usage.\ +Within this detection, it is assumed `dsquery.exe` is not moved or renamed.\ +The search will return the first time and last time these command-line arguments were used for these executions, as well as the target system, the user, process "dsquery.exe" and its parent process.\ +DSQuery.exe is natively found in `C:\Windows\system32` and `C:\Windows\syswow64` and only on Server operating system.\ +The following DLL(s) are loaded when DSQuery.exe is launched `dsquery.dll`. If found loaded by another process, it is possible dsquery is running within that process context in memory.\ +In addition to trust discovery, review parallel processes for additional behaviors performed. Identify the parent process and capture any files (batch files, for example) being used. +action.escu.mappings = {"kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1482"]} +action.escu.data_models = ["Endpoint"] +action.escu.eli5 = The following analytic identifies "dsquery.exe" execution with arguments looking for `TrustedDomain` query directly on the command-line. This is typically indicative of an Administrator or adversary perform domain trust discovery. Note that this query does not identify any other variations of "Dsquery.exe" usage.\ +Within this detection, it is assumed `dsquery.exe` is not moved or renamed.\ +The search will return the first time and last time these command-line arguments were used for these executions, as well as the target system, the user, process "dsquery.exe" and its parent process.\ +DSQuery.exe is natively found in `C:\Windows\system32` and `C:\Windows\syswow64` and only on Server operating system.\ +The following DLL(s) are loaded when DSQuery.exe is launched `dsquery.dll`. If found loaded by another process, it is possible dsquery is running within that process context in memory.\ +In addition to trust discovery, review parallel processes for additional behaviors performed. Identify the parent process and capture any files (batch files, for example) being used. +action.escu.how_to_implement = To successfully implement this search you need to be ingesting information on process that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` node. +action.escu.known_false_positives = Limited false positives. If there is a true false positive, filter based on command-line or parent process. +action.escu.creation_date = 2021-03-31 +action.escu.modification_date = 2021-03-31 +action.escu.confidence = high +action.escu.full_search_name = ESCU - DSQuery Domain Discovery - Rule +action.escu.search_type = detection +action.escu.product = ["Splunk Enterprise", "Splunk Enterprise Security", "Splunk Cloud"] +action.escu.providing_technologies = [] +action.escu.analytic_story = ["Domain Trust Discovery"] +cron_schedule = 0 * * * * +dispatch.earliest_time = -70m@m +dispatch.latest_time = -10m@m +action.correlationsearch.enabled = 1 +action.correlationsearch.label = ESCU - DSQuery Domain Discovery - Rule +action.correlationsearch.annotations = {"analytic_story": ["Domain Trust Discovery"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1482"]} +schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The following analytic identifies "dsquery.exe" execution with arguments looking for `TrustedDomain` query directly on the command-line. This is typically indicative of an Administrator or adversary perform domain trust discovery. Note that this query does not identify any other variations of "Dsquery.exe" usage.\ +Within this detection, it is assumed `dsquery.exe` is not moved or renamed.\ +The search will return the first time and last time these command-line arguments were used for these executions, as well as the target system, the user, process "dsquery.exe" and its parent process.\ +DSQuery.exe is natively found in `C:\Windows\system32` and `C:\Windows\syswow64` and only on Server operating system.\ +The following DLL(s) are loaded when DSQuery.exe is launched `dsquery.dll`. If found loaded by another process, it is possible dsquery is running within that process context in memory.\ +In addition to trust discovery, review parallel processes for additional behaviors performed. Identify the parent process and capture any files (batch files, for example) being used. +action.notable.param.rule_title = DSQuery Domain Discovery +action.notable.param.security_domain = endpoint +action.notable.param.severity = high +alert.digest_mode = 1 +disabled = true +enableSched = 1 +counttype = number of events +relation = greater than +quantity = 0 +realtime_schedule = 0 +is_visible = false +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=dsquery.exe Processes.process=*trustedDomain* by Processes.dest Processes.user Processes.parent_process Processes.process_name Processes.process Processes.process_id Processes.parent_process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `dsquery_domain_discovery_filter` + [ESCU - Deleting Shadow Copies - Rule] action.escu = 0 action.escu.enabled = 1 @@ -2622,6 +3000,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Deleting Shadow Copies - Rule action.correlationsearch.annotations = {"analytic_story": ["Windows Log Manipulation", "SamSam Ransomware", "Ransomware", "Clop Ransomware"], "cis20": ["CIS 8", "CIS 10"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1490"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The vssadmin.exe utility is used to interact with the Volume Shadow Copy Service. Wmic is an interface to the Windows Management Instrumentation. This search looks for either of these tools being used to delete shadow copies. +action.notable.param.rule_title = Deleting Shadow Copies +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -2667,6 +3051,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect API activity from users without MFA - Rule action.correlationsearch.annotations = {"analytic_story": ["AWS User Monitoring"], "cis20": ["CIS 16"], "nist": ["DE.DP", "PR.AC"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search looks for CloudTrail events where a user logged into the AWS account, is making API calls and has not enabled Multi Factor authentication. Multi factor authentication adds a layer of security by forcing the users to type a unique authentication code from an approved authentication device when they access AWS websites or services. AWS Best Practices recommend that you enable MFA for privileged IAM users. +action.notable.param.rule_title = Detect API activity from users without MFA +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -2752,6 +3142,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect AWS API Activities From Unapproved Accounts - Rule action.correlationsearch.annotations = {"analytic_story": ["AWS User Monitoring"], "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078.004"], "nist": ["DE.DP", "DE.CM", "PR.AC", "ID.AM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search looks for successful CloudTrail activity by user accounts that are not listed in the identity table or `aws_service_accounts.csv`. It returns event names and count, as well as the first and last time a specific user or service is detected, grouped by users. Deprecated because managing this list can be quite hard. +action.notable.param.rule_title = Detect AWS API Activities From Unapproved Accounts +action.notable.param.security_domain = access +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -2942,6 +3338,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Activity Related to Pass the Hash Attacks - Rule action.correlationsearch.annotations = {"analytic_story": ["Lateral Movement"], "cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1550.002"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search looks for specific authentication events from the Windows Security Event logs to detect potential attempts at using the Pass-the-Hash technique. +action.notable.param.rule_title = Detect Activity Related to Pass the Hash Attacks +action.notable.param.security_domain = access +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -2976,6 +3378,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Baron Samedit CVE-2021-3156 - Rule action.correlationsearch.annotations = {"analytic_story": ["Baron Samedit CVE-2021-3156"], "cis20": ["CIS 8", "CIS 12", "CIS 16"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1068"], "nist": ["DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search detects the heap-based buffer overflow of sudoedit +action.notable.param.rule_title = Detect Baron Samedit CVE-2021-3156 +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -3010,6 +3417,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Baron Samedit CVE-2021-3156 Segfault - Rule action.correlationsearch.annotations = {"analytic_story": ["Baron Samedit CVE-2021-3156"], "cis20": ["CIS 8", "CIS 12", "CIS 16"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1068"], "nist": ["DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search detects the heap-based buffer overflow of sudoedit +action.notable.param.rule_title = Detect Baron Samedit CVE-2021-3156 Segfault +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -3044,6 +3456,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Baron Samedit CVE-2021-3156 via OSQuery - Rule action.correlationsearch.annotations = {"analytic_story": ["Baron Samedit CVE-2021-3156"], "cis20": ["CIS 8", "CIS 12", "CIS 16"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1068"], "nist": ["DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search detects the heap-based buffer overflow of sudoedit +action.notable.param.rule_title = Detect Baron Samedit CVE-2021-3156 via OSQuery +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -3078,6 +3495,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Computer Changed with Anonymous Account - Rule action.correlationsearch.annotations = {"analytic_story": ["Detect Zerologon Attack"], "cis20": ["CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1210"], "nist": ["DE.AE", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search looks for Event Code 4742 (Computer Change) or EventCode 4624 (An account was successfully logged on) with an anonymous account. +action.notable.param.rule_title = Detect Computer Changed with Anonymous Account +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -3106,7 +3529,7 @@ action.escu.product = ["Splunk Enterprise", "Splunk Enterprise Security", "Splun action.escu.providing_technologies = [] action.escu.analytic_story = ["Credential Dumping", "Detect Zerologon Attack"] cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m +dispatch.earliest_time = -40m@m dispatch.latest_time = -10m@m action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Credential Dumping through LSASS access - Rule @@ -3150,6 +3573,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect DNS requests to Phishing Sites leveraging EvilGinx2 - Rule action.correlationsearch.annotations = {"analytic_story": ["Common Phishing Frameworks"], "cis20": ["CIS 8", "CIS 7"], "kill_chain_phases": ["Delivery", "Command and Control"], "mitre_attack": ["T1566.003"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest', 'src'] +action.notable.param.rule_description = This search looks for DNS requests for phishing domains that are leveraging EvilGinx tools to mimic websites. +action.notable.param.rule_title = Detect DNS requests to Phishing Sites leveraging EvilGinx2 +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -3188,6 +3617,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Excessive Account Lockouts From Endpoint - Rule action.correlationsearch.annotations = {"analytic_story": ["Account Monitoring and Controls"], "cis20": ["CIS 16"], "mitre_attack": ["T1078.002"], "nist": ["PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search identifies endpoints that have caused a relatively high number of account lockouts in a short period. +action.notable.param.rule_title = Detect Excessive Account Lockouts From Endpoint +action.notable.param.security_domain = access +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -3222,6 +3657,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Excessive User Account Lockouts - Rule action.correlationsearch.annotations = {"analytic_story": ["Account Monitoring and Controls"], "cis20": ["CIS 16"], "mitre_attack": ["T1078.003"], "nist": ["PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search detects user accounts that have been locked out a relatively high number of times in a short period. +action.notable.param.rule_title = Detect Excessive User Account Lockouts +action.notable.param.security_domain = access +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -3256,6 +3697,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Exchange Web Shell - Rule action.correlationsearch.annotations = {"analytic_story": ["HAFNIUM Group"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1505.003"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The following query identifies suspicious .aspx created in 3 paths identified by Microsoft as known drop locations for Exchange exploitation related to HAFNIUM group. Paths include: `\HttpProxy\owa\auth\`, `\inetpub\wwwroot\aspnet_client\`, and `\HttpProxy\OAB\`. Upon triage, the suspicious .aspx file will likely look obvious on the surface. inspect the contents for script code inside. Identify additional log sources, IIS included, to review source and other potential exploitation. +action.notable.param.rule_title = Detect Exchange Web Shell +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -3290,6 +3737,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect F5 TMUI RCE CVE-2020-5902 - Rule action.correlationsearch.annotations = {"analytic_story": ["F5 TMUI RCE CVE-2020-5902"], "cis20": ["CIS 8", "CIS 11"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1190"], "nist": ["DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search detects remote code exploit attempts on F5 BIG-IP, BIG-IQ, and Traffix SDC devices +action.notable.param.rule_title = Detect F5 TMUI RCE CVE-2020-5902 +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -3324,6 +3776,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect GCP Storage access from a new IP - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious GCP Storage Activities"], "cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1530"], "nist": ["PR.DS", "PR.AC", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search looks at GCP Storage bucket-access logs and detects new or previously unseen remote IP addresses that have successfully accessed a GCP Storage bucket. +action.notable.param.rule_title = Detect GCP Storage access from a new IP +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -3358,6 +3815,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect HTML Help Renamed - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious Compiled HTML Activity"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1218.001"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The following analytic identifies a renamed instance of hh.exe (HTML Help) executing a Compiled HTML Help (CHM). This particular technique will load Windows script code from a compiled help file. CHM files may contain nearly any file type embedded, but only execute html/htm. Upon a successful execution, the following script engines may be used for execution - JScript, VBScript, VBScript.Encode, JScript.Encode, JScript.Compact. Analyst may identify vbscript.dll or jscript.dll loading into hh.exe upon execution. The "htm" and "html" file extensions were the only extensions observed to be supported for the execution of Shortcut commands or WSH script code. During investigation, identify script content origination. Validate it is the legitimate version of hh.exe by reviewing the PE metadata. hh.exe is natively found in C:\Windows\system32 and C:\Windows\syswow64. +action.notable.param.rule_title = Detect HTML Help Renamed +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -3392,6 +3855,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect HTML Help Spawn Child Process - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious Compiled HTML Activity"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1218.001"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The following analytic identifies hh.exe (HTML Help) execution of a Compiled HTML Help (CHM) that spawns a child process. This particular technique will load Windows script code from a compiled help file. CHM files may contain nearly any file type embedded, but only execute html/htm. Upon a successful execution, the following script engines may be used for execution - JScript, VBScript, VBScript.Encode, JScript.Encode, JScript.Compact. Analyst may identify vbscript.dll or jscript.dll loading into hh.exe upon execution. The "htm" and "html" file extensions were the only extensions observed to be supported for the execution of Shortcut commands or WSH script code. During investigation, identify script content origination. Review child process events and investigate further. hh.exe is natively found in C:\Windows\system32 and C:\Windows\syswow64. +action.notable.param.rule_title = Detect HTML Help Spawn Child Process +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -3426,6 +3895,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect HTML Help URL in Command Line - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious Compiled HTML Activity"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1218.001"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The following analytic identifies hh.exe (HTML Help) execution of a Compiled HTML Help (CHM) file from a remote url. This particular technique will load Windows script code from a compiled help file. CHM files may contain nearly any file type embedded, but only execute html/htm. Upon a successful execution, the following script engines may be used for execution - JScript, VBScript, VBScript.Encode, JScript.Encode, JScript.Compact. Analyst may identify vbscript.dll or jscript.dll loading into hh.exe upon execution. The "htm" and "html" file extensions were the only extensions observed to be supported for the execution of Shortcut commands or WSH script code. During investigation, identify script content origination. Review reputation of remote IP and domain. Some instances, it is worth decompiling the .chm file to review its original contents. hh.exe is natively found in C:\Windows\system32 and C:\Windows\syswow64. +action.notable.param.rule_title = Detect HTML Help URL in Command Line +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -3460,6 +3935,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect HTML Help Using InfoTech Storage Handlers - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious Compiled HTML Activity"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1218.001"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The following analytic identifies hh.exe (HTML Help) execution of a Compiled HTML Help (CHM) file using InfoTech Storage Handlers. This particular technique will load Windows script code from a compiled help file, using InfoTech Storage Handlers. itss.dll will load upon execution. Three InfoTech Storage handlers are supported - ms-its, its, mk:@MSITStore. ITSS may be used to launch a specific html/htm file from within a CHM file. CHM files may contain nearly any file type embedded. Upon a successful execution, the following script engines may be used for execution - JScript, VBScript, VBScript.Encode, JScript.Encode, JScript.Compact. Analyst may identify vbscript.dll or jscript.dll loading into hh.exe upon execution. The "htm" and "html" file extensions were the only extensions observed to be supported for the execution of Shortcut commands or WSH script code. During investigation, identify script content origination. hh.exe is natively found in C:\Windows\system32 and C:\Windows\syswow64. +action.notable.param.rule_title = Detect HTML Help Using InfoTech Storage Handlers +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -3494,6 +3975,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect IPv6 Network Infrastructure Threats - Rule action.correlationsearch.annotations = {"analytic_story": ["Router and Infrastructure Security"], "cis20": ["CIS 1", "CIS 11"], "kill_chain_phases": ["Reconnaissance", "Delivery", "Actions on Objectives"], "mitre_attack": ["T1200", "T1498", "T1557.002"], "nist": ["ID.AM", "PR.DS"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = By enabling IPv6 First Hop Security as a Layer 2 Security measure on the organization's network devices, we will be able to detect various attacks such as packet forging in the Infrastructure. +action.notable.param.rule_title = Detect IPv6 Network Infrastructure Threats +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -3528,6 +4014,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Large Outbound ICMP Packets - Rule action.correlationsearch.annotations = {"analytic_story": ["Command and Control"], "cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1095"], "nist": ["DE.AE"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search looks for outbound ICMP packets with a packet size larger than 1,000 bytes. Various threat actors have been known to use ICMP as a command and control channel for their attack infrastructure. Large ICMP packets from an endpoint to a remote host may be indicative of this activity. +action.notable.param.rule_title = Detect Large Outbound ICMP Packets +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -3562,6 +4053,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Long DNS TXT Record Response - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious DNS Traffic", "Command and Control"], "cis20": ["CIS 8", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048.003"], "nist": ["PR.DS", "PR.PT", "DE.AE", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest', 'src'] +action.notable.param.rule_description = This search is used to detect attempts to use DNS tunneling, by calculating the length of responses to DNS TXT queries. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting unusually large volumes of DNS traffic. Deprecated because this detection should focus on DNS queries instead of DNS responses. +action.notable.param.rule_title = Detect Long DNS TXT Record Response +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -3596,6 +4093,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect MSHTA Url in Command Line - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious MSHTA Activity"], "cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1218.005"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This analytic identifies when Microsoft HTML Application Host (mshta.exe) utility is used to make remote http connections. Adversaries may use mshta.exe to proxy the download and execution of remote .hta files. The analytic identifies command line arguments of http and https being used. This technique is commonly used by malicious software to bypass preventative controls. The search will return the first time and last time these command-line arguments were used for these executions, as well as the target system, the user, process "rundll32.exe" and its parent process. +action.notable.param.rule_title = Detect MSHTA Url in Command Line +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -3624,7 +4127,7 @@ action.escu.product = ["Splunk Enterprise", "Splunk Enterprise Security", "Splun action.escu.providing_technologies = [] action.escu.analytic_story = ["Credential Dumping", "Detect Zerologon Attack", "Cloud Federated Credential Abuse"] cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m +dispatch.earliest_time = -40m@m dispatch.latest_time = -10m@m action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Mimikatz Using Loaded Images - Rule @@ -3664,6 +4167,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Mimikatz Via PowerShell And EventCode 4703 - Rule action.correlationsearch.annotations = {"analytic_story": ["Cloud Federated Credential Abuse"], "cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003.001"], "nist": ["PR.IP", "PR.AC", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search looks for PowerShell requesting privileges consistent with credential dumping. Deprecated, looks like things changed from a logging perspective. +action.notable.param.rule_title = Detect Mimikatz Via PowerShell And EventCode 4703 +action.notable.param.security_domain = access +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -3698,6 +4206,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect New Local Admin account - Rule action.correlationsearch.annotations = {"analytic_story": ["DHS Report TA18-074A", "HAFNIUM Group"], "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1136.001"], "nist": ["PR.AC", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for newly created accounts that have been elevated to local administrators. +action.notable.param.rule_title = Detect New Local Admin account +action.notable.param.security_domain = access +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -3732,6 +4246,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect New Login Attempts to Routers - Rule action.correlationsearch.annotations = {"analytic_story": ["Router and Infrastructure Security"], "cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "PR.AC", "PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The search queries the authentication logs for assets that are categorized as routers in the ES Assets and Identity Framework, to identify connections that have not been seen before in the last 30 days. +action.notable.param.rule_title = Detect New Login Attempts to Routers +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -3766,6 +4286,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect New Open GCP Storage Buckets - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious GCP Storage Activities"], "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1530"], "nist": ["PR.DS", "PR.AC", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'src'] +action.notable.param.rule_description = This search looks for GCP PubSub events where a user has created an open/public GCP Storage bucket. +action.notable.param.rule_title = Detect New Open GCP Storage Buckets +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -3878,6 +4404,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Oulook exe writing a zip file - Rule action.correlationsearch.annotations = {"analytic_story": ["Phishing Payloads"], "cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1566.001"], "nist": ["ID.AM", "PR.DS"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for execution of process `outlook.exe` where the process is writing a `.zip` file to the disk. +action.notable.param.rule_title = Detect Oulook exe writing a zip file +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -3912,6 +4444,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Outbound SMB Traffic - Rule action.correlationsearch.annotations = {"analytic_story": ["Hidden Cobra Malware", "DHS Report TA18-074A", "NOBELIUM Group"], "cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1071.002"], "nist": ["DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search looks for outbound SMB connections made by hosts within your network to the Internet. SMB traffic is used for Windows file-sharing activity. One of the techniques often used by attackers involves retrieving the credential hash using an SMB request made to a compromised server controlled by the threat actor. +action.notable.param.rule_title = Detect Outbound SMB Traffic +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -3946,6 +4483,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Path Interception By Creation Of program exe - Rule action.correlationsearch.annotations = {"analytic_story": ["Windows Persistence Techniques"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1574.009"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The detection Detect Path Interception By Creation Of program exe is detecting the abuse of unquoted service paths, which is a popular technique for privilege escalation. +action.notable.param.rule_title = Detect Path Interception By Creation Of program exe +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -3980,6 +4523,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Port Security Violation - Rule action.correlationsearch.annotations = {"analytic_story": ["Router and Infrastructure Security"], "cis20": ["CIS 1", "CIS 11"], "kill_chain_phases": ["Reconnaissance", "Delivery", "Exploitation", "Actions on Objectives"], "mitre_attack": ["T1200", "T1498", "T1557.002"], "nist": ["ID.AM", "PR.DS"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = By enabling Port Security on a Cisco switch you can restrict input to an interface by limiting and identifying MAC addresses of the workstations that are allowed to access the port. When you assign secure MAC addresses to a secure port, the port does not forward packets with source addresses outside the group of defined addresses. If you limit the number of secure MAC addresses to one and assign a single secure MAC address, the workstation attached to that port is assured the full bandwidth of the port. If a port is configured as a secure port and the maximum number of secure MAC addresses is reached, when the MAC address of a workstation attempting to access the port is different from any of the identified secure MAC addresses, a security violation occurs. +action.notable.param.rule_title = Detect Port Security Violation +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -4014,6 +4562,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Prohibited Applications Spawning cmd exe - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious Command-Line Executions", "Suspicious MSHTA Activity", "Suspicious Zoom Child Processes", "NOBELIUM Group"], "cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1059.003"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search looks for executions of cmd.exe spawned by a process that is often abused by attackers and that does not typically launch cmd.exe. +action.notable.param.rule_title = Detect Prohibited Applications Spawning cmd exe +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -4048,6 +4602,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect PsExec With accepteula Flag - Rule action.correlationsearch.annotations = {"analytic_story": ["SamSam Ransomware", "DHS Report TA18-074A", "HAFNIUM Group"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1021.002"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search looks for events where `PsExec.exe` is run with the `accepteula` flag in the command line. PsExec is a built-in Windows utility that enables you to execute processes on other systems. It is fully interactive for console applications. This tool is widely used for launching interactive command prompts on remote systems. Threat actors leverage this extensively for executing code on compromised systems. If an attacker is running PsExec for the first time, they will be prompted to accept the end-user license agreement (EULA), which can be passed as the argument `accepteula` within the command line. +action.notable.param.rule_title = Detect PsExec With accepteula Flag +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -4082,6 +4642,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Rare Executables - Rule action.correlationsearch.annotations = {"analytic_story": ["Emotet Malware DHS Report TA18-201A ", "Unusual Processes", "Cloud Federated Credential Abuse"], "cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.PT", "PR.DS", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search will return a table of rare processes, the names of the systems running them, and the users who initiated each process. +action.notable.param.rule_title = Detect Rare Executables +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -4116,6 +4682,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Regasm Spawning a Process - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious Regsvcs Regasm Activity"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1218.009"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The following analytic identifies regasm.exe spawning a process. This particular technique has been used in the wild to bypass application control products. Regasm.exe and Regsvcs.exe are signed by Microsoft. Spawning of a child process is rare from either process and should be investigated further. During investigation, identify and retrieve the content being loaded. Review parallel processes for additional suspicious behavior. Gather any other file modifications and review accordingly. regsvcs.exe and regasm.exe are natively found in C:\Windows\Microsoft.NET\Framework\v*\regasm|regsvcs.exe and C:\Windows\Microsoft.NET\Framework64\v*\regasm|regsvcs.exe. +action.notable.param.rule_title = Detect Regasm Spawning a Process +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -4150,6 +4722,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Regasm with Network Connection - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious Regsvcs Regasm Activity"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1218.009"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The following analytic identifies regasm.exe with a network connection to a public IP address, exluding private IP space. This particular technique has been used in the wild to bypass application control products. Regasm.exe and Regsvcs.exe are signed by Microsoft. By contacting a remote command and control server, the adversary will have the ability to escalate privileges and complete the objectives. During investigation, identify and retrieve the content being loaded. Review parallel processes for additional suspicious behavior. Gather any other file modifications and review accordingly. Review the reputation of the remote IP or domain and block as needed. regsvcs.exe and regasm.exe are natively found in C:\Windows\Microsoft.NET\Framework\v*\regasm|regsvcs.exe and C:\Windows\Microsoft.NET\Framework64\v*\regasm|regsvcs.exe. +action.notable.param.rule_title = Detect Regasm with Network Connection +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -4184,6 +4762,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Regasm with no Command Line Arguments - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious Regsvcs Regasm Activity"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1218.009"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The following analytic identifies regasm.exe with no command line arguments. This particular behavior occurs when another process injects into regasm.exe, no command line arguments will be present. During investigation, identify any network connections and parallel processes. Identify any suspicious module loads related to credential dumping or file writes. Regasm.exe are natively found in C:\Windows\Microsoft.NET\Framework\v*\regasm|regsvcs.exe and C:\Windows\Microsoft.NET\Framework64\v*\regasm|regsvcs.exe. +action.notable.param.rule_title = Detect Regasm with no Command Line Arguments +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -4218,6 +4802,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Regsvcs Spawning a Process - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious Regsvcs Regasm Activity"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1218.009"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The following analytic identifies regsvcs.exe spawning a process. This particular technique has been used in the wild to bypass application control products. Regasm.exe and Regsvcs.exe are signed by Microsoft. Spawning of a child process is rare from either process and should be investigated further. During investigation, identify and retrieve the content being loaded. Review parallel processes for additional suspicious behavior. Gather any other file modifications and review accordingly. regsvcs.exe and regasm.exe are natively found in C:\Windows\Microsoft.NET\Framework\v*\regasm|regsvcs.exe and C:\Windows\Microsoft.NET\Framework64\v*\regasm|regsvcs.exe. +action.notable.param.rule_title = Detect Regsvcs Spawning a Process +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -4252,6 +4842,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Regsvcs with Network Connection - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious Regsvcs Regasm Activity"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1218.009"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The following analytic identifies Regsvcs.exe with a network connection to a public IP address, exluding private IP space. This particular technique has been used in the wild to bypass application control products. Regasm.exe and Regsvcs.exe are signed by Microsoft. By contacting a remote command and control server, the adversary will have the ability to escalate privileges and complete the objectives. During investigation, identify and retrieve the content being loaded. Review parallel processes for additional suspicious behavior. Gather any other file modifications and review accordingly. Review the reputation of the remote IP or domain and block as needed. regsvcs.exe and regasm.exe are natively found in C:\Windows\Microsoft.NET\Framework\v*\regasm|regsvcs.exe and C:\Windows\Microsoft.NET\Framework64\v*\regasm|regsvcs.exe. +action.notable.param.rule_title = Detect Regsvcs with Network Connection +action.notable.param.security_domain = Endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -4286,6 +4882,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Regsvcs with No Command Line Arguments - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious Regsvcs Regasm Activity"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1218.009"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The following analytic identifies regsvcs.exe with no command line arguments. This particular behavior occurs when another process injects into regsvcs.exe, no command line arguments will be present. During investigation, identify any network connections and parallel processes. Identify any suspicious module loads related to credential dumping or file writes. Regasm.exe are natively found in C:\Windows\Microsoft.NET\Framework\v*\regasm|regsvcs.exe and C:\Windows\Microsoft.NET\Framework64\v*\regasm|regsvcs.exe. +action.notable.param.rule_title = Detect Regsvcs with No Command Line Arguments +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -4322,6 +4924,13 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Regsvr32 Application Control Bypass - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious Regsvr32 Activity", "Cobalt Strike"], "cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1218.010"], "nist": ["DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = Adversaries may abuse Regsvr32.exe to proxy execution of malicious code. Regsvr32.exe is a command-line program used to register and unregister object linking and embedding controls, including dynamic link libraries (DLLs), on Windows systems. Regsvr32.exe is also a Microsoft signed binary.This variation of the technique is often referred to as a "Squiblydoo" attack. \ +Upon investigating, look for network connections to remote destinations (internal or external). Be cautious to modify the query to look for "scrobj.dll", the ".dll" is not required to load scrobj. "scrobj.dll" will be loaded by "regsvr32.exe" upon execution. +action.notable.param.rule_title = Detect Regsvr32 Application Control Bypass +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -4396,6 +5005,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Rundll32 Application Control Bypass - advpack - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious Rundll32 Activity"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1218.011"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The following analytic identifies rundll32.exe loading advpack.dll and ieadvpack.dll by calling the LaunchINFSection function on the command line. This particular technique will load script code from a file. Upon a successful execution, the following module loads may occur - clr.dll, jscript.dll and scrobj.dll. During investigation, identify script content origination. Generally, a child process will spawn from rundll32.exe, but that may be bypassed based on script code contents. Rundll32.exe is natively found in C:\Windows\system32 and C:\Windows\syswow64. During investigation, review any network connections and obtain the script content executed. It's possible other files are on disk. +action.notable.param.rule_title = Detect Rundll32 Application Control Bypass - advpack +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -4430,6 +5045,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Rundll32 Application Control Bypass - setupapi - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious Rundll32 Activity"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1218.011"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The following analytic identifies rundll32.exe loading setupapi.dll and iesetupapi.dll by calling the LaunchINFSection function on the command line. This particular technique will load script code from a file. Upon a successful execution, the following module loads may occur - clr.dll, jscript.dll and scrobj.dll. During investigation, identify script content origination. Generally, a child process will spawn from rundll32.exe, but that may be bypassed based on script code contents. Rundll32.exe is natively found in C:\Windows\system32 and C:\Windows\syswow64. During investigation, review any network connections and obtain the script content executed. It's possible other files are on disk. +action.notable.param.rule_title = Detect Rundll32 Application Control Bypass - setupapi +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -4464,6 +5085,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Rundll32 Application Control Bypass - syssetup - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious Rundll32 Activity"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1218.011"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The following analytic identifies rundll32.exe loading syssetup.dll by calling the LaunchINFSection function on the command line. This particular technique will load script code from a file. Upon a successful execution, the following module loads may occur - clr.dll, jscript.dll and scrobj.dll. During investigation, identify script content origination. Generally, a child process will spawn from rundll32.exe, but that may be bypassed based on script code contents. Rundll32.exe is natively found in C:\Windows\system32 and C:\Windows\syswow64. During investigation, review any network connections and obtain the script content executed. It's possible other files are on disk. +action.notable.param.rule_title = Detect Rundll32 Application Control Bypass - syssetup +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -4498,6 +5125,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Rundll32 Inline HTA Execution - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious MSHTA Activity", "NOBELIUM Group"], "cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1218.005"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The following analytic identifies "rundll32.exe" execution with inline protocol handlers. "JavaScript", "VBScript", and "About" are the only supported options when invoking HTA content directly on the command-line. This type of behavior is commonly observed with fileless malware or application whitelisting bypass techniques. The search will return the first time and last time these command-line arguments were used for these executions, as well as the target system, the user, process "rundll32.exe" and its parent process. +action.notable.param.rule_title = Detect Rundll32 Inline HTA Execution +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -4537,6 +5170,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect S3 access from a new IP - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious AWS S3 Activities"], "cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1530"], "nist": ["PR.DS", "PR.AC", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search looks at S3 bucket-access logs and detects new or previously unseen remote IP addresses that have successfully accessed an S3 bucket. +action.notable.param.rule_title = Detect S3 access from a new IP +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -4571,6 +5209,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect SNICat SNI Exfiltration - Rule action.correlationsearch.annotations = {"analytic_story": ["Data Exfiltration"], "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1041"], "nist": ["PR.DS", "DE.CM", "DE.AE"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search looks for commands that the SNICat tool uses in the TLS SNI field. +action.notable.param.rule_title = Detect SNICat SNI Exfiltration +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -4605,6 +5248,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Software Download To Network Device - Rule action.correlationsearch.annotations = {"analytic_story": ["Router and Infrastructure Security"], "cis20": ["CIS 1", "CIS 11"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1542.005"], "nist": ["ID.AM", "PR.DS"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest', 'src'] +action.notable.param.rule_description = Adversaries may abuse netbooting to load an unauthorized network device operating system from a Trivial File Transfer Protocol (TFTP) server. TFTP boot (netbooting) is commonly used by network administrators to load configuration-controlled network device images from a centralized management server. Netbooting is one option in the boot sequence and can be used to centralize, manage, and control device images. +action.notable.param.rule_title = Detect Software Download To Network Device +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -4650,6 +5299,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Spike in AWS API Activity - Rule action.correlationsearch.annotations = {"analytic_story": ["AWS User Monitoring"], "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078.004"], "nist": ["DE.DP", "DE.CM", "PR.AC"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search will detect users creating spikes of API activity in your AWS environment. It will also update the cache file that factors in the latest data. This search is deprecated and have been translated to use the latest Change Datamodel. +action.notable.param.rule_title = Detect Spike in AWS API Activity +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -4723,6 +5378,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Spike in AWS Security Hub Alerts for User - Rule action.correlationsearch.annotations = {"analytic_story": ["AWS Security Hub Alerts"], "cis20": ["CIS 13"], "nist": ["DE.DP", "DE.AE"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search looks for a spike in number of of AWS security Hub alerts for an AWS IAM User in 4 hours intervals. +action.notable.param.rule_title = Detect Spike in AWS Security Hub Alerts for User +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -4762,6 +5423,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Spike in Network ACL Activity - Rule action.correlationsearch.annotations = {"analytic_story": ["AWS Network ACL Activity"], "cis20": ["CIS 12", "CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1562.007"], "nist": ["DE.DP", "DE.CM", "PR.AC"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search will detect users creating spikes in API activity related to network access-control lists (ACLs)in your AWS environment. This search is deprecated and have been translated to use the latest Change Datamodel. +action.notable.param.rule_title = Detect Spike in Network ACL Activity +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -4801,6 +5468,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Spike in S3 Bucket deletion - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious AWS S3 Activities"], "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1530"], "nist": ["DE.DP", "DE.CM", "PR.AC"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search detects users creating spikes in API activity related to deletion of S3 buckets in your AWS environment. It will also update the cache file that factors in the latest data. +action.notable.param.rule_title = Detect Spike in S3 Bucket deletion +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -4840,6 +5513,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Spike in Security Group Activity - Rule action.correlationsearch.annotations = {"analytic_story": ["AWS User Monitoring"], "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078.004"], "nist": ["DE.DP", "DE.CM", "PR.AC"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search will detect users creating spikes in API activity related to security groups in your AWS environment. It will also update the cache file that factors in the latest data. This search is deprecated and have been translated to use the latest Change Datamodel. +action.notable.param.rule_title = Detect Spike in Security Group Activity +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -4879,6 +5558,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule action.correlationsearch.annotations = {"analytic_story": ["AWS Network ACL Activity", "Suspicious AWS Traffic", "Command and Control"], "cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "nist": ["DE.AE", "DE.CM", "PR.AC"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search will detect spike in blocked outbound network connections originating from within your AWS environment. It will also update the cache file that factors in the latest data. +action.notable.param.rule_title = Detect Spike in blocked Outbound Traffic from your AWS +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -4913,6 +5597,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Traffic Mirroring - Rule action.correlationsearch.annotations = {"analytic_story": ["Router and Infrastructure Security"], "cis20": ["CIS 1", "CIS 11"], "kill_chain_phases": ["Delivery", "Actions on Objectives"], "mitre_attack": ["T1200", "T1498", "T1020.001"], "nist": ["ID.AM", "PR.DS"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = Adversaries may leverage traffic mirroring in order to automate data exfiltration over compromised network infrastructure. Traffic mirroring is a native feature for some network devices and used for network analysis and may be configured to duplicate traffic and forward to one or more destinations for analysis by a network analyzer or other monitoring device. +action.notable.param.rule_title = Detect Traffic Mirroring +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -4947,6 +5636,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect USB device insertion - Rule action.correlationsearch.annotations = {"analytic_story": ["Data Protection"], "cis20": ["CIS 13"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "nist": ["PR.PT", "PR.DS"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The search is used to detect hosts that generate Windows Event ID 4663 for successful attempts to write to or read from a removable storage and Event ID 4656 for failures, which occurs when a USB drive is plugged in. In this scenario we are querying the Change_Analysis data model to look for Windows Event ID 4656 or 4663 where the priority of the affected host is marked as high in the ES Assets and Identity Framework. +action.notable.param.rule_title = Detect USB device insertion +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -4981,6 +5676,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Unauthorized Assets by MAC address - Rule action.correlationsearch.annotations = {"analytic_story": ["Asset Tracking"], "cis20": ["CIS 1"], "kill_chain_phases": ["Reconnaissance", "Delivery", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = By populating the organization's assets within the assets_by_str.csv, we will be able to detect unauthorized devices that are trying to connect with the organization's network by inspecting DHCP request packets, which are issued by devices when they attempt to obtain an IP address from the DHCP server. The MAC address associated with the source of the DHCP request is checked against the list of known devices, and reports on those that are not found. +action.notable.param.rule_title = Detect Unauthorized Assets by MAC address +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -5015,6 +5715,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule action.correlationsearch.annotations = {"analytic_story": ["Emotet Malware DHS Report TA18-201A ", "Suspicious Command-Line Executions"], "cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1059.003"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for the execution of the cscript.exe or wscript.exe processes, with a parent of cmd.exe. The search will return the count, the first and last time this execution was seen on a machine, the user, and the destination of the machine +action.notable.param.rule_title = Detect Use of cmd exe to Launch Script Interpreters +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -5049,6 +5755,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Windows DNS SIGRed via Splunk Stream - Rule action.correlationsearch.annotations = {"analytic_story": ["Windows DNS SIGRed CVE-2020-1350"], "cis20": ["CIS 8", "CIS 12"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1203"], "nist": ["DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search detects SIGRed via Splunk Stream. +action.notable.param.rule_title = Detect Windows DNS SIGRed via Splunk Stream +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -5083,6 +5794,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Windows DNS SIGRed via Zeek - Rule action.correlationsearch.annotations = {"analytic_story": ["Windows DNS SIGRed CVE-2020-1350"], "cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1203"], "nist": ["DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search detects SIGRed via Zeek DNS and Zeek Conn data. +action.notable.param.rule_title = Detect Windows DNS SIGRed via Zeek +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -5117,6 +5833,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Zerologon via Zeek - Rule action.correlationsearch.annotations = {"analytic_story": ["Detect Zerologon Attack"], "cis20": ["CIS 8", "CIS 11"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1190"], "nist": ["DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search detects attempts to run exploits for the Zerologon CVE-2020-1472 vulnerability via Zeek RPC +action.notable.param.rule_title = Detect Zerologon via Zeek +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -5151,6 +5872,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule action.correlationsearch.annotations = {"analytic_story": ["JBoss Vulnerability", "SamSam Ransomware"], "kill_chain_phases": ["Reconnaissance"], "mitre_attack": ["T1082"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search looks for specific GET or HEAD requests to web servers that are indicative of reconnaissance attempts to identify vulnerable JBoss servers. JexBoss is described as the exploit tool of choice for this malicious activity. +action.notable.param.rule_title = Detect attackers scanning for vulnerable JBoss servers +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -5191,6 +5918,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect hosts connecting to dynamic domain providers - Rule action.correlationsearch.annotations = {"analytic_story": ["Data Protection", "Prohibited Traffic Allowed or Protocol Mismatch", "DNS Hijacking", "Suspicious DNS Traffic", "Dynamic DNS", "Command and Control"], "cis20": ["CIS 8", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1189"], "nist": ["PR.DS", "PR.PT", "DE.AE", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = Malicious actors often abuse legitimate Dynamic DNS services to host malicious payloads or interactive command and control nodes. Attackers will automate domain resolution changes by routing dynamic domains to countless IP addresses to circumvent firewall blocks, block lists as well as frustrate a network defenders analytic and investigative processes. This search will look for DNS queries made from within your infrastructure to suspicious dynamic domains. +action.notable.param.rule_title = Detect hosts connecting to dynamic domain providers +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -5225,6 +5957,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect malicious requests to exploit JBoss servers - Rule action.correlationsearch.annotations = {"analytic_story": ["JBoss Vulnerability", "SamSam Ransomware"], "cis20": ["CIS 12", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "PR.PT", "PR.IP", "DE.AE", "PR.MA", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search is used to detect malicious HTTP requests crafted to exploit jmx-console in JBoss servers. The malicious requests have a long URL length, as the payload is embedded in the URL. +action.notable.param.rule_title = Detect malicious requests to exploit JBoss servers +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -5259,6 +5997,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect mshta inline hta execution - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious MSHTA Activity"], "cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1218.005"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The following analytic identifies "mshta.exe" execution with inline protocol handlers. "JavaScript", "VBScript", and "About" are the only supported options when invoking HTA content directly on the command-line. The search will return the first time and last time these command-line arguments were used for these executions, as well as the target system, the user, process "mshta.exe" and its parent process. +action.notable.param.rule_title = Detect mshta inline hta execution +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -5293,6 +6037,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect mshta renamed - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious MSHTA Activity"], "cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1218.005"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The following analytic identifies renamed instances of mshta.exe executing. Mshta.exe is natively found in C:\Windows\system32 and C:\Windows\syswow64. This analytic utilizes the internal name of the PE to identify if is the legitimate mshta binary. Further analysis should be performed to review the executed content and validation it is the real mshta. +action.notable.param.rule_title = Detect mshta renamed +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -5332,6 +6082,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect new API calls from user roles - Rule action.correlationsearch.annotations = {"analytic_story": ["AWS User Monitoring"], "cis20": ["CIS 1"], "mitre_attack": ["T1078.004"], "nist": ["ID.AM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search detects new API calls that have either never been seen before or that have not been seen in the previous hour, where the identity type is `AssumedRole`. +action.notable.param.rule_title = Detect new API calls from user roles +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -5366,6 +6122,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect new user AWS Console Login - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious AWS Login Activities"], "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078.004"], "nist": ["DE.DP", "DE.AE"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour. Deprecated now this search is updated to use the Authentication datamodel. +action.notable.param.rule_title = Detect new user AWS Console Login +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -5400,6 +6162,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect processes used for System Network Configuration Discovery - Rule action.correlationsearch.annotations = {"analytic_story": ["Unusual Processes"], "cis20": ["CIS 2"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "mitre_attack": ["T1016"], "nist": ["ID.AM", "PR.DS"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for fast execution of processes used for system network configuration discovery on the endpoint. +action.notable.param.rule_title = Detect processes used for System Network Configuration Discovery +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -5436,6 +6204,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect web traffic to dynamic domain providers - Rule action.correlationsearch.annotations = {"analytic_story": ["Dynamic DNS"], "cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1071.001"], "nist": ["PR.IP", "DE.DP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest', 'src'] +action.notable.param.rule_description = This search looks for web connections to dynamic DNS providers. +action.notable.param.rule_title = Detect web traffic to dynamic domain providers +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -5470,6 +6244,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detection of DNS Tunnels - Rule action.correlationsearch.annotations = {"analytic_story": ["Data Protection", "Suspicious DNS Traffic", "Command and Control"], "cis20": ["CIS 13"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1048.003"], "nist": ["PR.PT", "PR.DS"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['src'] +action.notable.param.rule_description = This search is used to detect DNS tunneling, by calculating the sum of the length of DNS queries and DNS answers. The search also filters out potential false positives by filtering out queries made to internal systems and the queries originating from internal DNS, Web, and Email servers. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting an unusually large volume of DNS traffic. Deprecated because existing detection is doing the same. +action.notable.param.rule_title = Detection of DNS Tunnels +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -5504,6 +6284,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detection of tools built by NirSoft - Rule action.correlationsearch.annotations = {"analytic_story": ["Emotet Malware DHS Report TA18-201A "], "cis20": ["CIS 3"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1072"], "nist": ["PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search looks for specific command-line arguments that may indicate the execution of tools made by Nirsoft, which are legitimate, but may be abused by attackers. +action.notable.param.rule_title = Detection of tools built by NirSoft +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -5514,6 +6300,366 @@ realtime_schedule = 0 is_visible = false search = | tstats `security_content_summariesonly` count min(_time) values(Processes.process) as process max(_time) as lastTime from datamodel=Endpoint.Processes where (Processes.process="* /stext *" OR Processes.process="* /scomma *" ) by Processes.parent_process Processes.process_name Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` |`security_content_ctime(lastTime)` | `detection_of_tools_built_by_nirsoft_filter` +[ESCU - Disable Registry Tool - Rule] +action.escu = 0 +action.escu.enabled = 1 +description = This search is to identifies modification of registry to disable the regedit or registry tools of windows operating system. Since registry tool is a swiss knife in analyzing registry, malware such as RAT or trojan Spy disable this application to prevent the removal of their registry entry such as persistence, file less components and defense evasion. +action.escu.mappings = {"kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1562.001"]} +action.escu.data_models = ["Endpoint"] +action.escu.eli5 = This search is to identifies modification of registry to disable the regedit or registry tools of windows operating system. Since registry tool is a swiss knife in analyzing registry, malware such as RAT or trojan Spy disable this application to prevent the removal of their registry entry such as persistence, file less components and defense evasion. +action.escu.how_to_implement = To successfully implement this search you need to be ingesting information on process that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Registry` node. Also make sure that this registry was included in your config files ex. sysmon config to be monitored. +action.escu.known_false_positives = admin may disable this application for non technical user. +action.escu.creation_date = 2021-03-31 +action.escu.modification_date = 2021-03-31 +action.escu.confidence = high +action.escu.full_search_name = ESCU - Disable Registry Tool - Rule +action.escu.search_type = detection +action.escu.product = ["Splunk Enterprise", "Splunk Enterprise Security", "Splunk Cloud"] +action.escu.providing_technologies = [] +action.escu.analytic_story = ["Windows Defense Evasion Tactics"] +cron_schedule = 0 * * * * +dispatch.earliest_time = -70m@m +dispatch.latest_time = -10m@m +action.correlationsearch.enabled = 1 +action.correlationsearch.label = ESCU - Disable Registry Tool - Rule +action.correlationsearch.annotations = {"analytic_story": ["Windows Defense Evasion Tactics"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1562.001"]} +schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search is to identifies modification of registry to disable the regedit or registry tools of windows operating system. Since registry tool is a swiss knife in analyzing registry, malware such as RAT or trojan Spy disable this application to prevent the removal of their registry entry such as persistence, file less components and defense evasion. +action.notable.param.rule_title = Disable Registry Tool +action.notable.param.security_domain = endpoint +action.notable.param.severity = high +alert.digest_mode = 1 +disabled = true +enableSched = 1 +counttype = number of events +relation = greater than +quantity = 0 +realtime_schedule = 0 +is_visible = false +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Registry where Registry.registry_path= "*\\SOFTWARE\\Microsoft\\Windows\\CurrentVersion\\Policies\\System\\DisableRegistryTools" Registry.registry_value_name = "DWORD (0x00000001)" by Registry.registry_path Registry.registry_key_name Registry.registry_value_name Registry.dest | `drop_dm_object_name(Registry)` | `security_content_ctime(firstTime)` |`security_content_ctime(lastTime)` | `disable_registry_tool_filter` + +[ESCU - Disable Show Hidden Files - Rule] +action.escu = 0 +action.escu.enabled = 1 +description = The following search is to idetifies a modification in registry to prevent the user seeing all the files with hidden attributes. This event or techniques are known on some worm and trojan spy malware that will drop hidden files on the infected machine. +action.escu.mappings = {"kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1564.001", "T1562.001"]} +action.escu.data_models = ["Endpoint"] +action.escu.eli5 = The following search is to idetifies a modification in registry to prevent the user seeing all the files with hidden attributes. This event or techniques are known on some worm and trojan spy malware that will drop hidden files on the infected machine. +action.escu.how_to_implement = To successfully implement this search you need to be ingesting information on process that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Registry` node. Also make sure that this registry was included in your config files ex. sysmon config to be monitored. +action.escu.known_false_positives = unknown +action.escu.creation_date = 2021-03-31 +action.escu.modification_date = 2021-03-31 +action.escu.confidence = high +action.escu.full_search_name = ESCU - Disable Show Hidden Files - Rule +action.escu.search_type = detection +action.escu.product = ["Splunk Enterprise", "Splunk Enterprise Security", "Splunk Cloud"] +action.escu.providing_technologies = [] +action.escu.analytic_story = ["Windows Defense Evasion Tactics"] +cron_schedule = 0 * * * * +dispatch.earliest_time = -70m@m +dispatch.latest_time = -10m@m +action.correlationsearch.enabled = 1 +action.correlationsearch.label = ESCU - Disable Show Hidden Files - Rule +action.correlationsearch.annotations = {"analytic_story": ["Windows Defense Evasion Tactics"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1564.001", "T1562.001"]} +schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The following search is to idetifies a modification in registry to prevent the user seeing all the files with hidden attributes. This event or techniques are known on some worm and trojan spy malware that will drop hidden files on the infected machine. +action.notable.param.rule_title = Disable Show Hidden Files +action.notable.param.security_domain = endpoint +action.notable.param.severity = high +alert.digest_mode = 1 +disabled = true +enableSched = 1 +counttype = number of events +relation = greater than +quantity = 0 +realtime_schedule = 0 +is_visible = false +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Registry where (Registry.registry_path= "*\\SOFTWARE\\Microsoft\\Windows\\CurrentVersion\\Explorer\\Advanced\\Hidden" OR Registry.registry_path= "*\\SOFTWARE\\Microsoft\\Windows\\CurrentVersion\\Explorer\\Advanced\\HideFileExt" Registry.registry_value_name = "DWORD (0x00000001)") OR (Registry.registry_path= "*\\SOFTWARE\\Microsoft\\Windows\\CurrentVersion\\Explorer\\Advanced\\ShowSuperHidden" Registry.registry_value_name = "DWORD (0x00000000)") by Registry.registry_path Registry.registry_key_name Registry.registry_value_name Registry.dest | `drop_dm_object_name(Registry)` | `security_content_ctime(firstTime)` |`security_content_ctime(lastTime)` | `disable_show_hidden_files_filter` + +[ESCU - Disable Windows Behavior Monitoring - Rule] +action.escu = 0 +action.escu.enabled = 1 +description = This search is to identifies a modification in registry to disable the windows denfender real time behavior monitoring. This event or technique is commonly seen in RAT, bot, or Trojan to disable AV to evade detections. +action.escu.mappings = {"kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1562.001"]} +action.escu.data_models = ["Endpoint"] +action.escu.eli5 = This search is to identifies a modification in registry to disable the windows denfender real time behavior monitoring. This event or technique is commonly seen in RAT, bot, or Trojan to disable AV to evade detections. +action.escu.how_to_implement = To successfully implement this search you need to be ingesting information on process that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Registry` node. Also make sure that this registry was included in your config files ex. sysmon config to be monitored. +action.escu.known_false_positives = admin or user may choose to disable this windows features. +action.escu.creation_date = 2021-03-31 +action.escu.modification_date = 2021-03-31 +action.escu.confidence = high +action.escu.full_search_name = ESCU - Disable Windows Behavior Monitoring - Rule +action.escu.search_type = detection +action.escu.product = ["Splunk Enterprise", "Splunk Enterprise Security", "Splunk Cloud"] +action.escu.providing_technologies = [] +action.escu.analytic_story = ["Windows Defense Evasion Tactics"] +cron_schedule = 0 * * * * +dispatch.earliest_time = -70m@m +dispatch.latest_time = -10m@m +action.correlationsearch.enabled = 1 +action.correlationsearch.label = ESCU - Disable Windows Behavior Monitoring - Rule +action.correlationsearch.annotations = {"analytic_story": ["Windows Defense Evasion Tactics"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1562.001"]} +schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search is to identifies a modification in registry to disable the windows denfender real time behavior monitoring. This event or technique is commonly seen in RAT, bot, or Trojan to disable AV to evade detections. +action.notable.param.rule_title = Disable Windows Behavior Monitoring +action.notable.param.security_domain = endpoint +action.notable.param.severity = high +alert.digest_mode = 1 +disabled = true +enableSched = 1 +counttype = number of events +relation = greater than +quantity = 0 +realtime_schedule = 0 +is_visible = false +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Registry where Registry.registry_path= "*\\SOFTWARE\\Policies\\Microsoft\\Windows Defender\\Real-Time Protection\\DisableBehaviorMonitoring" OR Registry.registry_path= "*\\SOFTWARE\\Policies\\Microsoft\\Windows Defender\\Real-Time Protection\\DisableOnAccessProtection" OR Registry.registry_path= "*\\SOFTWARE\\Policies\\Microsoft\\Windows Defender\\Real-Time Protection\\DisableScanOnRealtimeEnable" Registry.registry_value_name = "DWORD (0x00000001)" by Registry.registry_path Registry.registry_key_name Registry.registry_value_name Registry.dest | `drop_dm_object_name(Registry)` | `security_content_ctime(firstTime)` |`security_content_ctime(lastTime)` | `disable_windows_behavior_monitoring_filter` + +[ESCU - Disable Windows SmartScreen Protection - Rule] +action.escu = 0 +action.escu.enabled = 1 +description = The following search identifies a modification of registry to disable the smartscreen protection of windows machine. This is windows feature provide an early warning system against website that might engage in phishing attack or malware distribution. This modification are seen in RAT malware to cover their tracks upon downloading other of its component or other payload. +action.escu.mappings = {"kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1562.001"]} +action.escu.data_models = ["Endpoint"] +action.escu.eli5 = The following search identifies a modification of registry to disable the smartscreen protection of windows machine. This is windows feature provide an early warning system against website that might engage in phishing attack or malware distribution. This modification are seen in RAT malware to cover their tracks upon downloading other of its component or other payload. +action.escu.how_to_implement = To successfully implement this search you need to be ingesting information on process that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Registry` node. Also make sure that this registry was included in your config files ex. sysmon config to be monitored. +action.escu.known_false_positives = admin or user may choose to disable this windows features. +action.escu.creation_date = 2021-03-31 +action.escu.modification_date = 2021-03-31 +action.escu.confidence = high +action.escu.full_search_name = ESCU - Disable Windows SmartScreen Protection - Rule +action.escu.search_type = detection +action.escu.product = ["Splunk Enterprise", "Splunk Enterprise Security", "Splunk Cloud"] +action.escu.providing_technologies = [] +action.escu.analytic_story = ["Windows Defense Evasion Tactics"] +cron_schedule = 0 * * * * +dispatch.earliest_time = -70m@m +dispatch.latest_time = -10m@m +action.correlationsearch.enabled = 1 +action.correlationsearch.label = ESCU - Disable Windows SmartScreen Protection - Rule +action.correlationsearch.annotations = {"analytic_story": ["Windows Defense Evasion Tactics"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1562.001"]} +schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The following search identifies a modification of registry to disable the smartscreen protection of windows machine. This is windows feature provide an early warning system against website that might engage in phishing attack or malware distribution. This modification are seen in RAT malware to cover their tracks upon downloading other of its component or other payload. +action.notable.param.rule_title = Disable Windows SmartScreen Protection +action.notable.param.security_domain = endpoint +action.notable.param.severity = high +alert.digest_mode = 1 +disabled = true +enableSched = 1 +counttype = number of events +relation = greater than +quantity = 0 +realtime_schedule = 0 +is_visible = false +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Registry where Registry.registry_path= "*HKLM\\SOFTWARE\\Microsoft\\Windows\\CurrentVersion\\Explorer\\SmartScreenEnabled" Registry.registry_value_name = "Off" by Registry.registry_path Registry.registry_key_name Registry.registry_value_name Registry.dest | `drop_dm_object_name(Registry)` | `security_content_ctime(firstTime)` |`security_content_ctime(lastTime)` | `disable_windows_smartscreen_protection_filter` + +[ESCU - Disabling CMD Application - Rule] +action.escu = 0 +action.escu.enabled = 1 +description = this search is to identify modification in registry to disable cmd prompt application. This technique is commonly seen in RAT, Trojan or WORM to prevent triaging or deleting there samples through cmd application which is one of the tool of analyst to traverse on directory and files. +action.escu.mappings = {"kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1562.001"]} +action.escu.data_models = ["Endpoint"] +action.escu.eli5 = this search is to identify modification in registry to disable cmd prompt application. This technique is commonly seen in RAT, Trojan or WORM to prevent triaging or deleting there samples through cmd application which is one of the tool of analyst to traverse on directory and files. +action.escu.how_to_implement = To successfully implement this search you need to be ingesting information on process that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Registry` node. Also make sure that this registry was included in your config files ex. sysmon config to be monitored. +action.escu.known_false_positives = admin may disable this application for non technical user. +action.escu.creation_date = 2021-03-31 +action.escu.modification_date = 2021-03-31 +action.escu.confidence = high +action.escu.full_search_name = ESCU - Disabling CMD Application - Rule +action.escu.search_type = detection +action.escu.product = ["Splunk Enterprise", "Splunk Enterprise Security", "Splunk Cloud"] +action.escu.providing_technologies = [] +action.escu.analytic_story = ["Windows Defense Evasion Tactics"] +cron_schedule = 0 * * * * +dispatch.earliest_time = -70m@m +dispatch.latest_time = -10m@m +action.correlationsearch.enabled = 1 +action.correlationsearch.label = ESCU - Disabling CMD Application - Rule +action.correlationsearch.annotations = {"analytic_story": ["Windows Defense Evasion Tactics"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1562.001"]} +schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = this search is to identify modification in registry to disable cmd prompt application. This technique is commonly seen in RAT, Trojan or WORM to prevent triaging or deleting there samples through cmd application which is one of the tool of analyst to traverse on directory and files. +action.notable.param.rule_title = Disabling CMD Application +action.notable.param.security_domain = endpoint +action.notable.param.severity = high +alert.digest_mode = 1 +disabled = true +enableSched = 1 +counttype = number of events +relation = greater than +quantity = 0 +realtime_schedule = 0 +is_visible = false +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Registry where Registry.registry_path= "*\\SOFTWARE\\Policies\\Microsoft\\Windows\\System\\DisableCMD" Registry.registry_value_name = "DWORD (0x00000001)" by Registry.registry_path Registry.registry_key_name Registry.registry_value_name Registry.dest | `drop_dm_object_name(Registry)` | `security_content_ctime(firstTime)` |`security_content_ctime(lastTime)` | `disabling_cmd_application_filter` + +[ESCU - Disabling ControlPanel - Rule] +action.escu = 0 +action.escu.enabled = 1 +description = this search is to identify registry modification to disable control panel window. This technique is commonly seen in malware to prevent their artifacts , persistence removed on the infected machine. +action.escu.mappings = {"kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1562.001"]} +action.escu.data_models = ["Endpoint"] +action.escu.eli5 = this search is to identify registry modification to disable control panel window. This technique is commonly seen in malware to prevent their artifacts , persistence removed on the infected machine. +action.escu.how_to_implement = To successfully implement this search you need to be ingesting information on process that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Registry` node. Also make sure that this registry was included in your config files ex. sysmon config to be monitored. +action.escu.known_false_positives = admin may disable this application for non technical user. +action.escu.creation_date = 2021-03-31 +action.escu.modification_date = 2021-03-31 +action.escu.confidence = high +action.escu.full_search_name = ESCU - Disabling ControlPanel - Rule +action.escu.search_type = detection +action.escu.product = ["Splunk Enterprise", "Splunk Enterprise Security", "Splunk Cloud"] +action.escu.providing_technologies = [] +action.escu.analytic_story = ["Windows Defense Evasion Tactics"] +cron_schedule = 0 * * * * +dispatch.earliest_time = -70m@m +dispatch.latest_time = -10m@m +action.correlationsearch.enabled = 1 +action.correlationsearch.label = ESCU - Disabling ControlPanel - Rule +action.correlationsearch.annotations = {"analytic_story": ["Windows Defense Evasion Tactics"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1562.001"]} +schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = this search is to identify registry modification to disable control panel window. This technique is commonly seen in malware to prevent their artifacts , persistence removed on the infected machine. +action.notable.param.rule_title = Disabling ControlPanel +action.notable.param.security_domain = endpoint +action.notable.param.severity = high +alert.digest_mode = 1 +disabled = true +enableSched = 1 +counttype = number of events +relation = greater than +quantity = 0 +realtime_schedule = 0 +is_visible = false +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Registry where Registry.registry_path= "*\\SOFTWARE\\Microsoft\\Windows\\CurrentVersion\\Policies\\Explorer\\NoControlPanel" Registry.registry_value_name = "DWORD (0x00000001)" by Registry.registry_path Registry.registry_key_name Registry.registry_value_name Registry.dest | `drop_dm_object_name(Registry)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `disabling_controlpanel_filter` + +[ESCU - Disabling Firewall with Netsh - Rule] +action.escu = 0 +action.escu.enabled = 1 +description = This search is to identifies suspicious firewall disabling using netsh application. this technique is commonly seen in malware that tries to communicate or download its component or other payload to its C2 server. +action.escu.mappings = {"kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1562.001"]} +action.escu.data_models = ["Endpoint"] +action.escu.eli5 = This search is to identifies suspicious firewall disabling using netsh application. this technique is commonly seen in malware that tries to communicate or download its component or other payload to its C2 server. +action.escu.how_to_implement = You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. +action.escu.known_false_positives = admin may disable firewall during testing or fixing network problem. +action.escu.creation_date = 2021-03-31 +action.escu.modification_date = 2021-03-31 +action.escu.confidence = high +action.escu.full_search_name = ESCU - Disabling Firewall with Netsh - Rule +action.escu.search_type = detection +action.escu.product = ["Splunk Enterprise", "Splunk Enterprise Security", "Splunk Cloud"] +action.escu.providing_technologies = [] +action.escu.analytic_story = ["Windows Defense Evasion Tactics"] +cron_schedule = 0 * * * * +dispatch.earliest_time = -70m@m +dispatch.latest_time = -10m@m +action.correlationsearch.enabled = 1 +action.correlationsearch.label = ESCU - Disabling Firewall with Netsh - Rule +action.correlationsearch.annotations = {"analytic_story": ["Windows Defense Evasion Tactics"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1562.001"]} +schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search is to identifies suspicious firewall disabling using netsh application. this technique is commonly seen in malware that tries to communicate or download its component or other payload to its C2 server. +action.notable.param.rule_title = Disabling Firewall with Netsh +action.notable.param.security_domain = endpoint +action.notable.param.severity = high +alert.digest_mode = 1 +disabled = true +enableSched = 1 +counttype = number of events +relation = greater than +quantity = 0 +realtime_schedule = 0 +is_visible = false +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=netsh.exe Processes.process= "*firewall*" (Processes.process= "*off*" OR Processes.process= "*disable*") by Processes.dest Processes.user Processes.parent_process Processes.process_name Processes.process Processes.process_id Processes.parent_process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `disabling_firewall_with_netsh_filter` + +[ESCU - Disabling FolderOptions Windows Feature - Rule] +action.escu = 0 +action.escu.enabled = 1 +description = This search is to identify registry modification to disable folder options feature of windows to show hidden files, file extension and etc. This technique used by malware in combination if disabling show hidden files feature to hide their files and also to hide the file extension to lure the user base on file icons or fake file extensions. +action.escu.mappings = {"kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1562.001"]} +action.escu.data_models = ["Endpoint"] +action.escu.eli5 = This search is to identify registry modification to disable folder options feature of windows to show hidden files, file extension and etc. This technique used by malware in combination if disabling show hidden files feature to hide their files and also to hide the file extension to lure the user base on file icons or fake file extensions. +action.escu.how_to_implement = To successfully implement this search you need to be ingesting information on process that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Registry` node. Also make sure that this registry was included in your config files ex. sysmon config to be monitored. +action.escu.known_false_positives = admin may disable this application for non technical user. +action.escu.creation_date = 2021-03-31 +action.escu.modification_date = 2021-03-31 +action.escu.confidence = high +action.escu.full_search_name = ESCU - Disabling FolderOptions Windows Feature - Rule +action.escu.search_type = detection +action.escu.product = ["Splunk Enterprise", "Splunk Enterprise Security", "Splunk Cloud"] +action.escu.providing_technologies = [] +action.escu.analytic_story = ["Windows Defense Evasion Tactics"] +cron_schedule = 0 * * * * +dispatch.earliest_time = -70m@m +dispatch.latest_time = -10m@m +action.correlationsearch.enabled = 1 +action.correlationsearch.label = ESCU - Disabling FolderOptions Windows Feature - Rule +action.correlationsearch.annotations = {"analytic_story": ["Windows Defense Evasion Tactics"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1562.001"]} +schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search is to identify registry modification to disable folder options feature of windows to show hidden files, file extension and etc. This technique used by malware in combination if disabling show hidden files feature to hide their files and also to hide the file extension to lure the user base on file icons or fake file extensions. +action.notable.param.rule_title = Disabling FolderOptions Windows Feature +action.notable.param.security_domain = endpoint +action.notable.param.severity = high +alert.digest_mode = 1 +disabled = true +enableSched = 1 +counttype = number of events +relation = greater than +quantity = 0 +realtime_schedule = 0 +is_visible = false +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Registry where Registry.registry_path= "*\\SOFTWARE\\Microsoft\\Windows\\CurrentVersion\\Policies\\Explorer\\NoFolderOptions" Registry.registry_value_name = "DWORD (0x00000001)" by Registry.registry_path Registry.registry_key_name Registry.registry_value_name Registry.dest | `drop_dm_object_name(Registry)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `disabling_folderoptions_windows_feature_filter` + +[ESCU - Disabling NoRun Windows App - Rule] +action.escu = 0 +action.escu.enabled = 1 +description = This search is to identify modification of registry to disable run application in window start menu. this application is known to be a helpful shortcut to windows OS user to run known application and also to execute some reg or batch script. This technique is used malware to make cleaning of its infection more harder by preventing known application run easily through run shortcut. +action.escu.mappings = {"kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1562.001"]} +action.escu.data_models = ["Endpoint"] +action.escu.eli5 = This search is to identify modification of registry to disable run application in window start menu. this application is known to be a helpful shortcut to windows OS user to run known application and also to execute some reg or batch script. This technique is used malware to make cleaning of its infection more harder by preventing known application run easily through run shortcut. +action.escu.how_to_implement = To successfully implement this search you need to be ingesting information on process that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Registry` node. Also make sure that this registry was included in your config files ex. sysmon config to be monitored. +action.escu.known_false_positives = admin may disable this application for non technical user. +action.escu.creation_date = 2021-03-31 +action.escu.modification_date = 2021-03-31 +action.escu.confidence = high +action.escu.full_search_name = ESCU - Disabling NoRun Windows App - Rule +action.escu.search_type = detection +action.escu.product = ["Splunk Enterprise", "Splunk Enterprise Security", "Splunk Cloud"] +action.escu.providing_technologies = [] +action.escu.analytic_story = ["Windows Defense Evasion Tactics"] +cron_schedule = 0 * * * * +dispatch.earliest_time = -70m@m +dispatch.latest_time = -10m@m +action.correlationsearch.enabled = 1 +action.correlationsearch.label = ESCU - Disabling NoRun Windows App - Rule +action.correlationsearch.annotations = {"analytic_story": ["Windows Defense Evasion Tactics"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1562.001"]} +schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search is to identify modification of registry to disable run application in window start menu. this application is known to be a helpful shortcut to windows OS user to run known application and also to execute some reg or batch script. This technique is used malware to make cleaning of its infection more harder by preventing known application run easily through run shortcut. +action.notable.param.rule_title = Disabling NoRun Windows App +action.notable.param.security_domain = endpoint +action.notable.param.severity = high +alert.digest_mode = 1 +disabled = true +enableSched = 1 +counttype = number of events +relation = greater than +quantity = 0 +realtime_schedule = 0 +is_visible = false +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Registry where Registry.registry_path= "*\\SOFTWARE\\Microsoft\\Windows\\CurrentVersion\\Policies\\Explorer\\NoRun" Registry.registry_value_name = "DWORD (0x00000001)" by Registry.registry_path Registry.registry_key_name Registry.registry_value_name Registry.dest | `drop_dm_object_name(Registry)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `disabling_norun_windows_app_filter` + [ESCU - Disabling Remote User Account Control - Rule] action.escu = 0 action.escu.enabled = 1 @@ -5538,6 +6684,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Disabling Remote User Account Control - Rule action.correlationsearch.annotations = {"analytic_story": ["Windows Defense Evasion Tactics", "Suspicious Windows Registry Activities"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1548.002"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = The search looks for modifications to registry keys that control the enforcement of Windows User Account Control (UAC). +action.notable.param.rule_title = Disabling Remote User Account Control +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -5548,6 +6700,86 @@ realtime_schedule = 0 is_visible = false search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Registry where Registry.registry_path=*HKLM\\SOFTWARE\\Microsoft\\Windows\\CurrentVersion\\Policies\\System\\EnableLUA* Registry.registry_value_name="DWORD (0x00000000)" by Registry.dest, Registry.registry_key_name Registry.user Registry.registry_path Registry.registry_value_name Registry.action | `drop_dm_object_name(Registry)` | `disabling_remote_user_account_control_filter` +[ESCU - Disabling SystemRestore In Registry - Rule] +action.escu = 0 +action.escu.enabled = 1 +description = The following search identifies the modification of registry related in disabling the system restore of a machine. This event or behavior are seen in some RAT malware to make the restore of the infected machine difficult and keep their infection on the box. +action.escu.mappings = {"kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1562.001"]} +action.escu.data_models = ["Endpoint"] +action.escu.eli5 = The following search identifies the modification of registry related in disabling the system restore of a machine. This event or behavior are seen in some RAT malware to make the restore of the infected machine difficult and keep their infection on the box. +action.escu.how_to_implement = To successfully implement this search you need to be ingesting information on process that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Registry` node. Also make sure that this registry was included in your config files ex. sysmon config to be monitored. +action.escu.known_false_positives = in some cases admin can disable systemrestore on a machine. +action.escu.creation_date = 2021-03-31 +action.escu.modification_date = 2021-03-31 +action.escu.confidence = high +action.escu.full_search_name = ESCU - Disabling SystemRestore In Registry - Rule +action.escu.search_type = detection +action.escu.product = ["Splunk Enterprise", "Splunk Enterprise Security", "Splunk Cloud"] +action.escu.providing_technologies = [] +action.escu.analytic_story = ["Windows Defense Evasion Tactics"] +cron_schedule = 0 * * * * +dispatch.earliest_time = -70m@m +dispatch.latest_time = -10m@m +action.correlationsearch.enabled = 1 +action.correlationsearch.label = ESCU - Disabling SystemRestore In Registry - Rule +action.correlationsearch.annotations = {"analytic_story": ["Windows Defense Evasion Tactics"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1562.001"]} +schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The following search identifies the modification of registry related in disabling the system restore of a machine. This event or behavior are seen in some RAT malware to make the restore of the infected machine difficult and keep their infection on the box. +action.notable.param.rule_title = Disabling SystemRestore In Registry +action.notable.param.security_domain = endpoint +action.notable.param.severity = high +alert.digest_mode = 1 +disabled = true +enableSched = 1 +counttype = number of events +relation = greater than +quantity = 0 +realtime_schedule = 0 +is_visible = false +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Registry where Registry.registry_path= "*\\SOFTWARE\\Microsoft\\Windows NT\\CurrentVersion\\SystemRestore\\DisableSR" OR Registry.registry_path= "*\\SOFTWARE\\Microsoft\\Windows NT\\CurrentVersion\\SystemRestore\\DisableConfig" Registry.registry_value_name = "DWORD (0x00000001)" by Registry.registry_path Registry.registry_key_name Registry.registry_value_name Registry.dest | `drop_dm_object_name(Registry)` | `security_content_ctime(firstTime)` |`security_content_ctime(lastTime)` | `disabling_systemrestore_in_registry_filter` + +[ESCU - Disabling Task Manager - Rule] +action.escu = 0 +action.escu.enabled = 1 +description = This search is to identifies modification of registry to disable the task manager of windows operating system. this event or technique are commonly seen in malware such as RAT, Trojan, TrojanSpy or worm to prevent the user to terminate their process. +action.escu.mappings = {"kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1562.001"]} +action.escu.data_models = ["Endpoint"] +action.escu.eli5 = This search is to identifies modification of registry to disable the task manager of windows operating system. this event or technique are commonly seen in malware such as RAT, Trojan, TrojanSpy or worm to prevent the user to terminate their process. +action.escu.how_to_implement = To successfully implement this search you need to be ingesting information on process that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Registry` node. Also make sure that this registry was included in your config files ex. sysmon config to be monitored. +action.escu.known_false_positives = admin may disable this application for non technical user. +action.escu.creation_date = 2021-03-31 +action.escu.modification_date = 2021-03-31 +action.escu.confidence = high +action.escu.full_search_name = ESCU - Disabling Task Manager - Rule +action.escu.search_type = detection +action.escu.product = ["Splunk Enterprise", "Splunk Enterprise Security", "Splunk Cloud"] +action.escu.providing_technologies = [] +action.escu.analytic_story = ["Windows Defense Evasion Tactics"] +cron_schedule = 0 * * * * +dispatch.earliest_time = -70m@m +dispatch.latest_time = -10m@m +action.correlationsearch.enabled = 1 +action.correlationsearch.label = ESCU - Disabling Task Manager - Rule +action.correlationsearch.annotations = {"analytic_story": ["Windows Defense Evasion Tactics"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1562.001"]} +schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search is to identifies modification of registry to disable the task manager of windows operating system. this event or technique are commonly seen in malware such as RAT, Trojan, TrojanSpy or worm to prevent the user to terminate their process. +action.notable.param.rule_title = Disabling Task Manager +action.notable.param.security_domain = endpoint +action.notable.param.severity = high +alert.digest_mode = 1 +disabled = true +enableSched = 1 +counttype = number of events +relation = greater than +quantity = 0 +realtime_schedule = 0 +is_visible = false +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Registry where Registry.registry_path= "*\\SOFTWARE\\Microsoft\\Windows\\CurrentVersion\\Policies\\System\\DisableTaskMgr" Registry.registry_value_name = "DWORD (0x00000001)" by Registry.registry_path Registry.registry_key_name Registry.registry_value_name Registry.dest | `drop_dm_object_name(Registry)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `disabling_task_manager_filter` + [ESCU - Dump LSASS via comsvcs DLL - Rule] action.escu = 0 action.escu.enabled = 1 @@ -5566,7 +6798,7 @@ action.escu.product = ["Splunk Enterprise", "Splunk Enterprise Security", "Splun action.escu.providing_technologies = [] action.escu.analytic_story = ["Credential Dumping", "Suspicious Rundll32 Activity", "HAFNIUM Group"] cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m +dispatch.earliest_time = -40m@m dispatch.latest_time = -10m@m action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Dump LSASS via comsvcs DLL - Rule @@ -5602,7 +6834,7 @@ action.escu.product = ["Splunk Enterprise", "Splunk Enterprise Security", "Splun action.escu.providing_technologies = [] action.escu.analytic_story = ["Credential Dumping", "HAFNIUM Group"] cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m +dispatch.earliest_time = -40m@m dispatch.latest_time = -10m@m action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Dump LSASS via procdump - Rule @@ -5638,7 +6870,7 @@ action.escu.product = ["Splunk Enterprise", "Splunk Enterprise Security", "Splun action.escu.providing_technologies = [] action.escu.analytic_story = ["Credential Dumping", "HAFNIUM Group"] cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m +dispatch.earliest_time = -40m@m dispatch.latest_time = -10m@m action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Dump LSASS via procdump Rename - Rule @@ -5683,6 +6915,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - EC2 Instance Modified With Previously Unseen User - Rule action.correlationsearch.annotations = {"analytic_story": ["Unusual AWS EC2 Modifications"], "cis20": ["CIS 1"], "mitre_attack": ["T1078.004"], "nist": ["ID.AM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for EC2 instances being modified by users who have not previously modified them. This search is deprecated and have been translated to use the latest Change Datamodel. +action.notable.param.rule_title = EC2 Instance Modified With Previously Unseen User +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -5722,6 +6960,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - EC2 Instance Started In Previously Unseen Region - Rule action.correlationsearch.annotations = {"analytic_story": ["AWS Cryptomining", "Suspicious AWS EC2 Activities"], "cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1535"], "nist": ["DE.DP", "DE.AE"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search looks for CloudTrail events where an instance is started in a particular region in the last one hour and then compares it to a lookup file of previously seen regions where an instance was started +action.notable.param.rule_title = EC2 Instance Started In Previously Unseen Region +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -5756,6 +6999,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - EC2 Instance Started With Previously Unseen AMI - Rule action.correlationsearch.annotations = {"analytic_story": ["AWS Cryptomining"], "cis20": ["CIS 1"], "nist": ["ID.AM"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search looks for EC2 instances being created with previously unseen AMIs. This search is deprecated and have been translated to use the latest Change Datamodel. +action.notable.param.rule_title = EC2 Instance Started With Previously Unseen AMI +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -5790,6 +7038,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule action.correlationsearch.annotations = {"analytic_story": ["AWS Cryptomining"], "cis20": ["CIS 1"], "nist": ["ID.AM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for EC2 instances being created with previously unseen instance types. This search is deprecated and have been translated to use the latest Change Datamodel. +action.notable.param.rule_title = EC2 Instance Started With Previously Unseen Instance Type +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -5824,6 +7078,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - EC2 Instance Started With Previously Unseen User - Rule action.correlationsearch.annotations = {"analytic_story": ["AWS Cryptomining", "Suspicious AWS EC2 Activities"], "cis20": ["CIS 1"], "mitre_attack": ["T1078.004"], "nist": ["ID.AM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search looks for EC2 instances being created by users who have not created them before. This search is deprecated and have been translated to use the latest Change Datamodel. +action.notable.param.rule_title = EC2 Instance Started With Previously Unseen User +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -5860,6 +7120,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Email Attachments With Lots Of Spaces - Rule action.correlationsearch.annotations = {"analytic_story": ["Emotet Malware DHS Report TA18-201A ", "Suspicious Emails"], "cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = Attackers often use spaces as a means to obfuscate an attachment's file extension. This search looks for messages with email attachments that have many spaces within the file names. +action.notable.param.rule_title = Email Attachments With Lots Of Spaces +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -5894,6 +7159,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Email files written outside of the Outlook directory - Rule action.correlationsearch.annotations = {"analytic_story": ["Collection and Staging"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1114.001"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The search looks at the change-analysis data model and detects email files created outside the normal Outlook directory. +action.notable.param.rule_title = Email files written outside of the Outlook directory +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -5928,6 +7199,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Email servers sending high volume traffic to hosts - Rule action.correlationsearch.annotations = {"analytic_story": ["Collection and Staging", "HAFNIUM Group"], "cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1114.002"], "nist": ["PR.PT", "DE.CM", "DE.AE"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. +action.notable.param.rule_title = Email servers sending high volume traffic to hosts +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -5962,6 +7238,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Eventvwr UAC Bypass - Rule action.correlationsearch.annotations = {"analytic_story": ["Windows Defense Evasion Tactics"], "kill_chain_phases": ["Exploitation", "Privilege Escalation"], "mitre_attack": ["T1548.002"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The following search identifies Eventvwr bypass by identifying the registry modification into a specific path that eventvwr.msc looks to (but is not valid) upon execution. A successful attack will include a suspicious command to be executed upon eventvwr.msc loading. Upon triage, review the parallel processes that have executed. Identify any additional registry modifications on the endpoint that may look suspicious. Remediate as necessary. +action.notable.param.rule_title = Eventvwr UAC Bypass +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -5996,6 +7278,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Excessive DNS Failures - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious DNS Traffic", "Command and Control"], "cis20": ["CIS 8", "CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1071.004"], "nist": ["PR.PT", "DE.AE", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search identifies DNS query failures by counting the number of DNS responses that do not indicate success, and trigger on more than 50 occurrences. +action.notable.param.rule_title = Excessive DNS Failures +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -6030,6 +7317,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Execution of File With Spaces Before Extension - Rule action.correlationsearch.annotations = {"analytic_story": ["Windows File Extension and Association Abuse"], "cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1036.003"], "nist": ["DE.CM", "PR.PT", "PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for processes launched from files with at least five spaces in the name before the extension. This is typically done to obfuscate the file extension by pushing it outside of the default view. +action.notable.param.rule_title = Execution of File With Spaces Before Extension +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -6064,6 +7357,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Execution of File with Multiple Extensions - Rule action.correlationsearch.annotations = {"analytic_story": ["Windows File Extension and Association Abuse"], "cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1036.003"], "nist": ["DE.CM", "PR.PT", "PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for processes launched from files that have double extensions in the file name. This is typically done to obscure the "real" file extension and make it appear as though the file being accessed is a data file, as opposed to executable content. +action.notable.param.rule_title = Execution of File with Multiple Extensions +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -6098,6 +7397,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Extended Period Without Successful Netbackup Backups - Rule action.correlationsearch.annotations = {"analytic_story": ["Monitor Backup Solution"], "cis20": ["CIS 10"], "nist": ["PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search returns a list of hosts that have not successfully completed a backup in over a week. Deprecated because it's a infrastructure monitoring. +action.notable.param.rule_title = Extended Period Without Successful Netbackup Backups +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -6132,6 +7437,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - File with Samsam Extension - Rule action.correlationsearch.annotations = {"analytic_story": ["SamSam Ransomware"], "cis20": ["CIS 8"], "kill_chain_phases": ["Installation"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The search looks for file writes with extensions consistent with a SamSam ransomware attack. +action.notable.param.rule_title = File with Samsam Extension +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -6166,6 +7477,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - First Time Seen Child Process of Zoom - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious Zoom Child Processes"], "cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1068"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search looks for child processes spawned by zoom.exe or zoom.us that has not previously been seen. +action.notable.param.rule_title = First Time Seen Child Process of Zoom +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -6200,6 +7517,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - First Time Seen Running Windows Service - Rule action.correlationsearch.annotations = {"analytic_story": ["Windows Service Abuse", "Orangeworm Attack Group", "NOBELIUM Group"], "cis20": ["CIS 2", "CIS 9"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1569.002"], "nist": ["ID.AM", "PR.DS", "PR.AC", "DE.AE"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search looks for the first and last time a Windows service is seen running in your environment. This table is then cached. +action.notable.param.rule_title = First Time Seen Running Windows Service +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -6234,6 +7557,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - First time seen command line argument - Rule action.correlationsearch.annotations = {"analytic_story": ["DHS Report TA18-074A", "Suspicious Command-Line Executions", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Hidden Cobra Malware"], "cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1059.001", "T1059.003"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search looks for command-line arguments that use a `/c` parameter to execute a command that has not previously been seen. +action.notable.param.rule_title = First time seen command line argument +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -6276,6 +7604,16 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - FodHelper UAC Bypass - Rule action.correlationsearch.annotations = {"analytic_story": ["Windows Defense Evasion Tactics"], "kill_chain_phases": ["Exploitation", "Privilege Escalation"], "mitre_attack": ["T1112", "T1548.002"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = Fodhelper.exe has a known UAC bypass as it attempts to look for specific registry keys upon execution, that do not exist. Therefore, an attacker can write its malicious commands in these registry keys to be executed by fodhelper.exe with the highest privilege. \ +1. `HKCU:\Software\Classes\ms-settings\shell\open\command`\ +1. `HKCU:\Software\Classes\ms-settings\shell\open\command\DelegateExecute`\ +1. `HKCU:\Software\Classes\ms-settings\shell\open\command\(default)`\ +Upon triage, fodhelper.exe will have a child process and read access will occur on the registry keys. Isolate the endpoint and review parallel processes for additional behavior. +action.notable.param.rule_title = FodHelper UAC Bypass +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -6310,6 +7648,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - GCP Detect accounts with high risk roles by project - Rule action.correlationsearch.annotations = {"analytic_story": ["GCP Cross Account Activity"], "kill_chain_phases": ["Lateral Movement"], "mitre_attack": ["T1078"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search provides detection of accounts with high risk roles by projects. Compromised accounts with high risk roles can move laterally or even scalate privileges at different projects depending on organization schema. +action.notable.param.rule_title = GCP Detect accounts with high risk roles by project +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -6344,6 +7687,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - GCP Detect gcploit framework - Rule action.correlationsearch.annotations = {"analytic_story": ["GCP Cross Account Activity"], "kill_chain_phases": ["Lateral Movement"], "mitre_attack": ["T1078"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'src'] +action.notable.param.rule_description = This search provides detection of GCPloit exploitation framework. This framework can be used to escalate privileges and move laterally from compromised high privilege accounts. +action.notable.param.rule_title = GCP Detect gcploit framework +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -6378,6 +7727,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - GCP Detect high risk permissions by resource and account - Rule action.correlationsearch.annotations = {"analytic_story": ["GCP Cross Account Activity"], "kill_chain_phases": ["Lateral Movement"], "mitre_attack": ["T1078"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search provides detection of high risk permissions by resource and accounts. These are permissions that can allow attackers with compromised accounts to move laterally and escalate privileges. +action.notable.param.rule_title = GCP Detect high risk permissions by resource and account +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -6412,6 +7766,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - GCP GCR container uploaded - Rule action.correlationsearch.annotations = {"analytic_story": ["Container Implantation Monitoring and Investigation"], "mitre_attack": ["T1525"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search show information on uploaded containers including source user, account, action, bucket name event name, http user agent, message and destination path. +action.notable.param.rule_title = GCP GCR container uploaded +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -6446,6 +7806,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - GCP Kubernetes cluster pod scan detection - Rule action.correlationsearch.annotations = {"analytic_story": ["Kubernetes Scanning Activity"], "kill_chain_phases": ["Reconnaissance"], "mitre_attack": ["T1526"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster's pods +action.notable.param.rule_title = GCP Kubernetes cluster pod scan detection +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -6480,6 +7845,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - GCP Kubernetes cluster scan detection - Rule action.correlationsearch.annotations = {"analytic_story": ["Kubernetes Scanning Activity"], "kill_chain_phases": ["Reconnaissance"], "mitre_attack": ["T1526"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster +action.notable.param.rule_title = GCP Kubernetes cluster scan detection +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -6514,6 +7884,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Hiding Files And Directories With Attrib exe - Rule action.correlationsearch.annotations = {"analytic_story": ["Windows Defense Evasion Tactics", "Windows Persistence Techniques"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1222.001"], "nist": ["DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = Attackers leverage an existing Windows binary, attrib.exe, to mark specific as hidden by using specific flags so that the victim does not see the file. The search looks for specific command-line arguments to detect the use of attrib.exe to hide files. +action.notable.param.rule_title = Hiding Files And Directories With Attrib exe +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -6548,6 +7924,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - High File Deletion Frequency - Rule action.correlationsearch.annotations = {"analytic_story": ["Clop Ransomware"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1485"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search looks for high frequency of file deletion relative to process name and process id. These events usually happen when the ransomware tries to encrypt the files with the ransomware file extensions and sysmon treat the original files to be deleted as soon it was replace as encrypted data. +action.notable.param.rule_title = High File Deletion Frequency +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -6582,6 +7964,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - High Number of Login Failures from a single source - Rule action.correlationsearch.annotations = {"analytic_story": ["Office 365 Detections"], "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1110.001"], "nist": ["DE.DP", "DE.AE"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search will detect more than 5 login failures in Office365 Azure Active Directory from a single source IP address. Please adjust the threshold value of 5 as suited for your environment. +action.notable.param.rule_title = High Number of Login Failures from a single source +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -6616,6 +8004,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - High Process Termination Frequency - Rule action.correlationsearch.annotations = {"analytic_story": ["Clop Ransomware"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1486"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This analytics are designed to indentify a high frequency of process termination on a machine which is a common behavior of ransomware malware before encrypting files. This technique is designed to avoid an exception error while accessing (docs, images, database and etc..) in the infected machine for encryption. +action.notable.param.rule_title = High Process Termination Frequency +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -6650,6 +8043,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Hosts receiving high volume of network traffic from email server - Rule action.correlationsearch.annotations = {"analytic_story": ["Collection and Staging"], "cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1114.002"], "nist": ["PR.PT", "DE.CM", "DE.AE"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. +action.notable.param.rule_title = Hosts receiving high volume of network traffic from email server +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -6684,6 +8082,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Identify New User Accounts - Rule action.correlationsearch.annotations = {"analytic_story": ["Account Monitoring and Controls"], "cis20": ["CIS 16"], "mitre_attack": ["T1078.002"], "nist": ["PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This detection search will help profile user accounts in your environment by identifying newly created accounts that have been added to your network in the past week. +action.notable.param.rule_title = Identify New User Accounts +action.notable.param.security_domain = access +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -6718,6 +8121,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Kerberoasting spn request with RC4 encryption - Rule action.correlationsearch.annotations = {"analytic_story": ["Lateral Movement"], "cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1558.003"], "nist": ["DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search detects a potential kerberoasting attack via service principal name requests +action.notable.param.rule_title = Kerberoasting spn request with RC4 encryption +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -6752,6 +8160,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Kubernetes AWS detect RBAC authorization by account - Rule action.correlationsearch.annotations = {"analytic_story": ["Kubernetes Sensitive Role Activity"], "kill_chain_phases": ["Lateral Movement"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search provides information on Kubernetes RBAC authorizations by accounts, this search can be modified by adding top to see both extremes of RBAC by accounts occurrences +action.notable.param.rule_title = Kubernetes AWS detect RBAC authorization by account +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -6786,6 +8199,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Kubernetes AWS detect most active service accounts by pod - Rule action.correlationsearch.annotations = {"analytic_story": ["Kubernetes Sensitive Role Activity"], "kill_chain_phases": ["Lateral Movement"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search provides information on Kubernetes service accounts,accessing pods by IP address, verb and decision +action.notable.param.rule_title = Kubernetes AWS detect most active service accounts by pod +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -6820,6 +8238,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Kubernetes AWS detect sensitive role access - Rule action.correlationsearch.annotations = {"analytic_story": ["Kubernetes Sensitive Role Activity"], "kill_chain_phases": ["Lateral Movement"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search provides information on Kubernetes accounts accessing sensitve objects such as configmpas or secrets +action.notable.param.rule_title = Kubernetes AWS detect sensitive role access +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -6854,6 +8277,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Kubernetes AWS detect service accounts forbidden failure access - Rule action.correlationsearch.annotations = {"analytic_story": ["Kubernetes Sensitive Object Access Activity"], "kill_chain_phases": ["Lateral Movement"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search provides information on Kubernetes service accounts with failure or forbidden access status, this search can be extended by using top or rare operators to find trends or rarities in failure status, user agents, source IPs and request URI +action.notable.param.rule_title = Kubernetes AWS detect service accounts forbidden failure access +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -6888,6 +8316,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Kubernetes AWS detect suspicious kubectl calls - Rule action.correlationsearch.annotations = {"analytic_story": ["Kubernetes Sensitive Object Access Activity"], "kill_chain_phases": ["Lateral Movement"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search provides information on anonymous Kubectl calls with IP, verb namespace and object access context +action.notable.param.rule_title = Kubernetes AWS detect suspicious kubectl calls +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -6922,6 +8356,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Kubernetes Azure detect RBAC authorization by account - Rule action.correlationsearch.annotations = {"analytic_story": ["Kubernetes Sensitive Role Activity"], "kill_chain_phases": ["Lateral Movement"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search provides information on Kubernetes RBAC authorizations by accounts, this search can be modified by adding rare or top to see both extremes of RBAC by accounts occurrences +action.notable.param.rule_title = Kubernetes Azure detect RBAC authorization by account +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -6956,6 +8395,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Kubernetes Azure detect most active service accounts by pod namespace - Rule action.correlationsearch.annotations = {"analytic_story": ["Kubernetes Sensitive Role Activity"], "kill_chain_phases": ["Lateral Movement"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search provides information on Kubernetes service accounts,accessing pods and namespaces by IP address and verb +action.notable.param.rule_title = Kubernetes Azure detect most active service accounts by pod namespace +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -6990,6 +8434,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Kubernetes Azure detect sensitive object access - Rule action.correlationsearch.annotations = {"analytic_story": ["Kubernetes Sensitive Object Access Activity"], "kill_chain_phases": ["Lateral Movement"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search provides information on Kubernetes accounts accessing sensitve objects such as configmpas or secrets +action.notable.param.rule_title = Kubernetes Azure detect sensitive object access +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -7024,6 +8473,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Kubernetes Azure detect sensitive role access - Rule action.correlationsearch.annotations = {"analytic_story": ["Kubernetes Sensitive Role Activity"], "kill_chain_phases": ["Lateral Movement"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search provides information on Kubernetes accounts accessing sensitve objects such as configmpas or secrets +action.notable.param.rule_title = Kubernetes Azure detect sensitive role access +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -7058,6 +8512,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Kubernetes Azure detect service accounts forbidden failure access - Rule action.correlationsearch.annotations = {"analytic_story": ["Kubernetes Sensitive Object Access Activity"], "kill_chain_phases": ["Lateral Movement"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search provides information on Kubernetes service accounts with failure or forbidden access status +action.notable.param.rule_title = Kubernetes Azure detect service accounts forbidden failure access +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -7092,6 +8551,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Kubernetes Azure detect suspicious kubectl calls - Rule action.correlationsearch.annotations = {"analytic_story": ["Kubernetes Sensitive Object Access Activity"], "kill_chain_phases": ["Lateral Movement"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search provides information on rare Kubectl calls with IP, verb namespace and object access context +action.notable.param.rule_title = Kubernetes Azure detect suspicious kubectl calls +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -7126,6 +8590,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Kubernetes Azure pod scan fingerprint - Rule action.correlationsearch.annotations = {"analytic_story": ["Kubernetes Scanning Activity"], "kill_chain_phases": ["Reconnaissance"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search provides information of unauthenticated requests via source IP user agent, request URI and response status data against Kubernetes cluster pod in Azure +action.notable.param.rule_title = Kubernetes Azure pod scan fingerprint +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -7160,6 +8629,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Kubernetes Azure scan fingerprint - Rule action.correlationsearch.annotations = {"analytic_story": ["Kubernetes Scanning Activity"], "kill_chain_phases": ["Reconnaissance"], "mitre_attack": ["T1526"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search provides information of unauthenticated requests via source IP user agent, request URI and response status data against Kubernetes cluster in Azure +action.notable.param.rule_title = Kubernetes Azure scan fingerprint +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -7194,6 +8668,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Kubernetes GCP detect RBAC authorizations by account - Rule action.correlationsearch.annotations = {"analytic_story": ["Kubernetes Sensitive Role Activity"], "kill_chain_phases": ["Lateral Movement"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search provides information on Kubernetes RBAC authorizations by accounts, this search can be modified by adding top to see both extremes of RBAC by accounts occurrences +action.notable.param.rule_title = Kubernetes GCP detect RBAC authorizations by account +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -7228,6 +8708,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Kubernetes GCP detect most active service accounts by pod - Rule action.correlationsearch.annotations = {"analytic_story": ["Kubernetes Sensitive Role Activity"], "kill_chain_phases": ["Lateral Movement"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search provides information on Kubernetes service accounts,accessing pods by IP address, verb and decision +action.notable.param.rule_title = Kubernetes GCP detect most active service accounts by pod +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -7262,6 +8748,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Kubernetes GCP detect sensitive object access - Rule action.correlationsearch.annotations = {"analytic_story": ["Kubernetes Sensitive Object Access Activity"], "kill_chain_phases": ["Lateral Movement"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search provides information on Kubernetes accounts accessing sensitve objects such as configmaps or secrets +action.notable.param.rule_title = Kubernetes GCP detect sensitive object access +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -7296,6 +8788,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Kubernetes GCP detect sensitive role access - Rule action.correlationsearch.annotations = {"analytic_story": ["Kubernetes Sensitive Role Activity"], "kill_chain_phases": ["Lateral Movement"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search provides information on Kubernetes accounts accessing sensitve objects such as configmpas or secrets +action.notable.param.rule_title = Kubernetes GCP detect sensitive role access +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -7330,6 +8828,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Kubernetes GCP detect service accounts forbidden failure access - Rule action.correlationsearch.annotations = {"analytic_story": ["Kubernetes Sensitive Object Access Activity"], "kill_chain_phases": ["Lateral Movement"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search provides information on Kubernetes service accounts with failure or forbidden access status, this search can be extended by using top or rare operators to find trends or rarities in failure status, user agents, source IPs and request URI +action.notable.param.rule_title = Kubernetes GCP detect service accounts forbidden failure access +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -7364,6 +8868,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Kubernetes GCP detect suspicious kubectl calls - Rule action.correlationsearch.annotations = {"analytic_story": ["Kubernetes Sensitive Object Access Activity"], "kill_chain_phases": ["Lateral Movement"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search provides information on anonymous Kubectl calls with IP, verb namespace and object access context +action.notable.param.rule_title = Kubernetes GCP detect suspicious kubectl calls +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -7398,6 +8908,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Large Volume of DNS ANY Queries - Rule action.correlationsearch.annotations = {"analytic_story": ["DNS Amplification Attacks"], "cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1498.002"], "nist": ["PR.PT", "DE.AE", "PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = The search is used to identify attempts to use your DNS Infrastructure for DDoS purposes via a DNS amplification attack leveraging ANY queries. +action.notable.param.rule_title = Large Volume of DNS ANY Queries +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -7432,6 +8947,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - MacOS - Re-opened Applications - Rule action.correlationsearch.annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Installation", "Command and Control"], "nist": ["DE.DP", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for processes referencing the plist files that determine which applications are re-opened when a user reboots their machine. +action.notable.param.rule_title = MacOS - Re-opened Applications +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -7466,6 +8987,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule action.correlationsearch.annotations = {"analytic_story": ["Malicious PowerShell", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "HAFNIUM Group"], "cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1059.001"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for PowerShell processes started with parameters to modify the execution policy of the run, run in a hidden window, and connect to the Internet. This combination of command-line options is suspicious because it's overriding the default PowerShell execution policy, attempts to hide its activity from the user, and connects to the Internet. Deprecated becaue hidden is not needed when download file with System.Net.WebClient. +action.notable.param.rule_title = Malicious PowerShell Process - Connect To Internet With Hidden Window +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -7500,6 +9027,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Malicious PowerShell Process - Encoded Command - Rule action.correlationsearch.annotations = {"analytic_story": ["Malicious PowerShell", "NOBELIUM Group"], "cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1027"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for PowerShell processes that have encoded the script within the command-line. Malware has been seen using this parameter, as it obfuscates the code and makes it relatively easy to pass a script on the command-line. +action.notable.param.rule_title = Malicious PowerShell Process - Encoded Command +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -7534,6 +9067,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule action.correlationsearch.annotations = {"analytic_story": ["DHS Report TA18-074A", "HAFNIUM Group"], "cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1059.001"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search looks for PowerShell processes started with parameters used to bypass the local execution policy for scripts. These parameters are often observed in attacks leveraging PowerShell scripts as they override the default PowerShell execution policy. +action.notable.param.rule_title = Malicious PowerShell Process - Execution Policy Bypass +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -7568,6 +9107,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule action.correlationsearch.annotations = {"analytic_story": ["Malicious PowerShell"], "cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1059.001"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for PowerShell processes started with a base64 encoded command-line passed to it, with parameters to modify the execution policy for the process, and those that prevent the display of an interactive prompt to the user. This combination of command-line options is suspicious because it overrides the default PowerShell execution policy, attempts to hide itself from the user, and passes an encoded script to be run on the command-line. Deprecated because almost the same as Malicious PowerShell Process - Encoded Command +action.notable.param.rule_title = Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -7602,6 +9147,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule action.correlationsearch.annotations = {"analytic_story": ["Malicious PowerShell"], "cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1059.001"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for PowerShell processes launched with arguments that have characters indicative of obfuscation on the command-line. +action.notable.param.rule_title = Malicious PowerShell Process With Obfuscation Techniques +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -7612,6 +9163,46 @@ realtime_schedule = 0 is_visible = false search = | tstats `security_content_summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=powershell.exe by Processes.user Processes.process_name Processes.parent_process_name Processes.dest Processes.process | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| eval num_obfuscation = (mvcount(split(process,"`"))-1) + (mvcount(split(process, "^"))-1) + (mvcount(split(process, "'"))-1) | `malicious_powershell_process_with_obfuscation_techniques_filter` | search num_obfuscation > 10 +[ESCU - Malicious Powershell Executed As A Service - Rule] +action.escu = 0 +action.escu.enabled = 1 +description = This detection is to identify the abuse the Windows SC.exe to execute malicious commands or payloads via PowerShell. +action.escu.mappings = {"kill_chain_phases": ["Privilege Escalation"], "mitre_attack": ["T1569.002"]} +action.escu.data_models = [] +action.escu.eli5 = This detection is to identify the abuse the Windows SC.exe to execute malicious commands or payloads via PowerShell. +action.escu.how_to_implement = To successfully implement this search, you need to be ingesting Windows System logs with the Service name, Service File Name Service Start type, and Service Type from your endpoints. +action.escu.known_false_positives = Creating a hidden powershell service is rare and could key off of those instances. +action.escu.creation_date = 2021-04-07 +action.escu.modification_date = 2021-04-07 +action.escu.confidence = high +action.escu.full_search_name = ESCU - Malicious Powershell Executed As A Service - Rule +action.escu.search_type = detection +action.escu.product = ["Splunk Enterprise", "Splunk Enterprise Security", "Splunk Cloud"] +action.escu.providing_technologies = [] +action.escu.analytic_story = ["Malicious Powershell"] +cron_schedule = 0 * * * * +dispatch.earliest_time = -70m@m +dispatch.latest_time = -10m@m +action.correlationsearch.enabled = 1 +action.correlationsearch.label = ESCU - Malicious Powershell Executed As A Service - Rule +action.correlationsearch.annotations = {"analytic_story": ["Malicious Powershell"], "kill_chain_phases": ["Privilege Escalation"], "mitre_attack": ["T1569.002"]} +schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This detection is to identify the abuse the Windows SC.exe to execute malicious commands or payloads via PowerShell. +action.notable.param.rule_title = Malicious Powershell Executed As A Service +action.notable.param.security_domain = endpoint +action.notable.param.severity = high +alert.digest_mode = 1 +disabled = true +enableSched = 1 +counttype = number of events +relation = greater than +quantity = 0 +realtime_schedule = 0 +is_visible = false +search = `wineventlog_system` EventCode=7045 Service_File_Name IN ("*powershell.exe*", "*-nop*", "*hid*") | stats count min(_time) as firstTime max(_time) as lastTime by EventCode Service_File_Name Service_Name Service_Start_Type Service_Type Service_Account user | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `malicious_powershell_executed_as_a_service_filter` + [ESCU - Monitor DNS For Brand Abuse - Rule] action.escu = 0 action.escu.enabled = 1 @@ -7636,6 +9227,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Monitor DNS For Brand Abuse - Rule action.correlationsearch.annotations = {"analytic_story": ["Brand Monitoring"], "kill_chain_phases": ["Delivery", "Actions on Objectives"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search looks for DNS requests for faux domains similar to the domains that you want to have monitored for abuse. +action.notable.param.rule_title = Monitor DNS For Brand Abuse +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -7670,6 +9266,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Monitor Email For Brand Abuse - Rule action.correlationsearch.annotations = {"analytic_story": ["Brand Monitoring", "Suspicious Emails"], "cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search looks for emails claiming to be sent from a domain similar to one that you want to have monitored for abuse. +action.notable.param.rule_title = Monitor Email For Brand Abuse +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -7704,6 +9305,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Monitor Registry Keys for Print Monitors - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious Windows Registry Activities", "Windows Persistence Techniques"], "cis20": ["CIS 8", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1547.010"], "nist": ["PR.PT", "DE.CM", "PR.AC"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search looks for registry activity associated with modifications to the registry key `HKLM\SYSTEM\CurrentControlSet\Control\Print\Monitors`. In this scenario, an attacker can load an arbitrary .dll into the print-monitor registry by giving the full path name to the after.dll. The system will execute the .dll with elevated (SYSTEM) permissions and will persist after reboot. +action.notable.param.rule_title = Monitor Registry Keys for Print Monitors +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -7738,6 +9345,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Monitor Web Traffic For Brand Abuse - Rule action.correlationsearch.annotations = {"analytic_story": ["Brand Monitoring"], "cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['src'] +action.notable.param.rule_description = This search looks for Web requests to faux domains similar to the one that you want to have monitored for abuse. +action.notable.param.rule_title = Monitor Web Traffic For Brand Abuse +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -7772,6 +9385,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Multiple Okta Users With Invalid Credentials From The Same IP - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious Okta Activity"], "cis20": ["CIS 16"], "mitre_attack": ["T1078.001"], "nist": ["DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search detects Okta login failures due to bad credentials for multiple users originating from the same ip address. +action.notable.param.rule_title = Multiple Okta Users With Invalid Credentials From The Same IP +action.notable.param.security_domain = access +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -7798,14 +9416,20 @@ action.escu.full_search_name = ESCU - NLTest Domain Trust Discovery - Rule action.escu.search_type = detection action.escu.product = ["Splunk Enterprise", "Splunk Enterprise Security", "Splunk Cloud"] action.escu.providing_technologies = [] -action.escu.analytic_story = ["Ryuk Ransomware"] +action.escu.analytic_story = ["Ryuk Ransomware", "Domain Trust Discovery"] cron_schedule = 0 * * * * dispatch.earliest_time = -70m@m dispatch.latest_time = -10m@m action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - NLTest Domain Trust Discovery - Rule -action.correlationsearch.annotations = {"analytic_story": ["Ryuk Ransomware"], "cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1482"], "nist": ["PR.PT", "DE.CM"]} +action.correlationsearch.annotations = {"analytic_story": ["Ryuk Ransomware", "Domain Trust Discovery"], "cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1482"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for the execution of `nltest.exe` with command-line arguments utilized to query for Domain Trust information. Two arguments `/domain trusts`, returns a list of trusted domains, and `/all_trusts`, returns all trusted domains. Red Teams and adversaries alike use NLTest.exe to enumerate the current domain to assist with further understanding where to pivot next. +action.notable.param.rule_title = NLTest Domain Trust Discovery +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -7840,6 +9464,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - New container uploaded to AWS ECR - Rule action.correlationsearch.annotations = {"analytic_story": ["Container Implantation Monitoring and Investigation"], "mitre_attack": ["T1525"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'src'] +action.notable.param.rule_description = This searches show information on uploaded containers including source user, image id, source IP user type, http user agent, region, first time, last time of operation (PutImage). These searches are based on Cloud Infrastructure Data Model. +action.notable.param.rule_title = New container uploaded to AWS ECR +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -7874,6 +9504,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Nishang PowershellTCPOneLine - Rule action.correlationsearch.annotations = {"analytic_story": ["HAFNIUM Group"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1059.001"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This query detects the Nishang Invoke-PowerShellTCPOneLine utility that spawns a call back to a remote command and control server. This is a powershell oneliner. In addition, this will capture on the command-line additional utilities used by Nishang. Triage the endpoint and identify any parallel processes that look suspicious. Review the reputation of the remote IP or domain contacted by the powershell process. +action.notable.param.rule_title = Nishang PowershellTCPOneLine +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -7908,6 +9544,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - No Windows Updates in a time frame - Rule action.correlationsearch.annotations = {"analytic_story": ["Monitor for Updates"], "cis20": ["CIS 18"], "nist": ["PR.PT", "PR.MA"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search looks for Windows endpoints that have not generated an event indicating a successful Windows update in the last 60 days. Windows updates are typically released monthly and applied shortly thereafter. An endpoint that has not successfully applied an update in this time frame indicates the endpoint is not regularly being patched for some reason. +action.notable.param.rule_title = No Windows Updates in a time frame +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -7940,7 +9582,7 @@ action.escu.product = ["Splunk Enterprise", "Splunk Enterprise Security", "Splun action.escu.providing_technologies = [] action.escu.analytic_story = ["Credential Dumping", "HAFNIUM Group"] cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m +dispatch.earliest_time = -40m@m dispatch.latest_time = -10m@m action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Ntdsutil Export NTDS - Rule @@ -8409,6 +10051,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Okta Account Lockout Events - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious Okta Activity"], "cis20": ["CIS 16"], "mitre_attack": ["T1078.001"], "nist": ["DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = Detect Okta user lockout events +action.notable.param.rule_title = Okta Account Lockout Events +action.notable.param.security_domain = access +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -8443,6 +10090,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Okta Failed SSO Attempts - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious Okta Activity"], "cis20": ["CIS 16"], "mitre_attack": ["T1078.001"], "nist": ["DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = Detect failed Okta SSO events +action.notable.param.rule_title = Okta Failed SSO Attempts +action.notable.param.security_domain = access +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -8477,6 +10129,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Okta User Logins From Multiple Cities - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious Okta Activity"], "cis20": ["CIS 16"], "mitre_attack": ["T1078.001"], "nist": ["DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search detects logins from the same user from different cities in a 24 hour period. +action.notable.param.rule_title = Okta User Logins From Multiple Cities +action.notable.param.security_domain = access +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -8511,6 +10169,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Open Redirect in Splunk Web - Rule action.correlationsearch.annotations = {"analytic_story": ["Splunk Enterprise Vulnerability"], "cis20": ["CIS 3", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "RS.MI", "PR.PT", "PR.AC", "PR.IP", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search allows you to look for evidence of exploitation for CVE-2016-4859, the Splunk Open Redirect Vulnerability. +action.notable.param.rule_title = Open Redirect in Splunk Web +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -8545,6 +10208,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Osquery pack - ColdRoot detection - Rule action.correlationsearch.annotations = {"analytic_story": ["ColdRoot MacOS RAT"], "cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Installation", "Command and Control"], "nist": ["DE.DP", "DE.CM", "PR.PT"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search looks for ColdRoot events from the osx-attacks osquery pack. +action.notable.param.rule_title = Osquery pack - ColdRoot detection +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -8579,6 +10247,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Overwriting Accessibility Binaries - Rule action.correlationsearch.annotations = {"analytic_story": ["Windows Privilege Escalation"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1546.008"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = Microsoft Windows contains accessibility features that can be launched with a key combination before a user has logged in. An adversary can modify or replace these programs so they can get a command prompt or backdoor without logging in to the system. This search looks for modifications to these binaries. +action.notable.param.rule_title = Overwriting Accessibility Binaries +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -8589,6 +10263,46 @@ realtime_schedule = 0 is_visible = false search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_path) as file_path from datamodel=Endpoint.Filesystem where (Filesystem.file_path=*\\Windows\\System32\\sethc.exe* OR Filesystem.file_path=*\\Windows\\System32\\utilman.exe* OR Filesystem.file_path=*\\Windows\\System32\\osk.exe* OR Filesystem.file_path=*\\Windows\\System32\\Magnify.exe* OR Filesystem.file_path=*\\Windows\\System32\\Narrator.exe* OR Filesystem.file_path=*\\Windows\\System32\\DisplaySwitch.exe* OR Filesystem.file_path=*\\Windows\\System32\\AtBroker.exe*) by Filesystem.file_name Filesystem.dest | `drop_dm_object_name(Filesystem)` | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `overwriting_accessibility_binaries_filter` +[ESCU - PowerShell Start-BitsTransfer - Rule] +action.escu = 0 +action.escu.enabled = 1 +description = Start-BitsTransfer is the PowerShell "version" of BitsAdmin.exe. Similar functionality is present. This technique variation is not as commonly used by adversaries, but has been abused in the past. Lesser known uses include the ability to set the `-TransferType` to `Upload` for exfiltration of files. In an instance where `Upload` is used, it is highly possible files will be archived. During triage, review parallel processes and process lineage. Capture any files on disk and review. For the remote domain or IP, what is the reputation? +action.escu.mappings = {"kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1197"]} +action.escu.data_models = ["Endpoint"] +action.escu.eli5 = Start-BitsTransfer is the PowerShell "version" of BitsAdmin.exe. Similar functionality is present. This technique variation is not as commonly used by adversaries, but has been abused in the past. Lesser known uses include the ability to set the `-TransferType` to `Upload` for exfiltration of files. In an instance where `Upload` is used, it is highly possible files will be archived. During triage, review parallel processes and process lineage. Capture any files on disk and review. For the remote domain or IP, what is the reputation? +action.escu.how_to_implement = To successfully implement this search you need to be ingesting information on process that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` node. +action.escu.known_false_positives = Limited false positives. It is possible administrators will utilize Start-BitsTransfer for administrative tasks, otherwise filter based parent process or command-line arguments. +action.escu.creation_date = 2021-03-29 +action.escu.modification_date = 2021-03-29 +action.escu.confidence = high +action.escu.full_search_name = ESCU - PowerShell Start-BitsTransfer - Rule +action.escu.search_type = detection +action.escu.product = ["Splunk Enterprise", "Splunk Enterprise Security", "Splunk Cloud"] +action.escu.providing_technologies = [] +action.escu.analytic_story = ["BITS Jobs"] +cron_schedule = 0 * * * * +dispatch.earliest_time = -70m@m +dispatch.latest_time = -10m@m +action.correlationsearch.enabled = 1 +action.correlationsearch.label = ESCU - PowerShell Start-BitsTransfer - Rule +action.correlationsearch.annotations = {"analytic_story": ["BITS Jobs"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1197"]} +schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = Start-BitsTransfer is the PowerShell "version" of BitsAdmin.exe. Similar functionality is present. This technique variation is not as commonly used by adversaries, but has been abused in the past. Lesser known uses include the ability to set the `-TransferType` to `Upload` for exfiltration of files. In an instance where `Upload` is used, it is highly possible files will be archived. During triage, review parallel processes and process lineage. Capture any files on disk and review. For the remote domain or IP, what is the reputation? +action.notable.param.rule_title = PowerShell Start-BitsTransfer +action.notable.param.security_domain = endpoint +action.notable.param.severity = high +alert.digest_mode = 1 +disabled = true +enableSched = 1 +counttype = number of events +relation = greater than +quantity = 0 +realtime_schedule = 0 +is_visible = false +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=powershell.exe Processes.process=*start-bitstransfer* by Processes.dest Processes.user Processes.parent_process Processes.process_name Processes.process Processes.process_id Processes.parent_process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `powershell_start_bitstransfer_filter` + [ESCU - Process Creating LNK file in Suspicious Location - Rule] action.escu = 0 action.escu.enabled = 1 @@ -8613,6 +10327,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Process Creating LNK file in Suspicious Location - Rule action.correlationsearch.annotations = {"analytic_story": ["Phishing Payloads"], "cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1566.002"], "nist": ["ID.AM", "PR.DS"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for a process launching an `*.lnk` file under `C:\User*` or `*\Local\Temp\*`. This is common behavior used by various spear phishing tools. +action.notable.param.rule_title = Process Creating LNK file in Suspicious Location +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -8647,6 +10367,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Process Deleting Its Process File Path - Rule action.correlationsearch.annotations = {"analytic_story": ["Clop Ransomware"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1003.002"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This detection is to identify a suspicious process that tries to delete the process file path related to its process. This technique is known to be defense evasion once a certain condition of malware is satisfied or not. Clop ransomware use this technique where it will try to delete its process file path using a .bat command if the keyboard layout is not the layout it tries to infect. +action.notable.param.rule_title = Process Deleting Its Process File Path +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -8681,6 +10407,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Process Execution via WMI - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious WMI Use"], "cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for processes launched via WMI. +action.notable.param.rule_title = Process Execution via WMI +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -8715,6 +10447,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Processes Tapping Keyboard Events - Rule action.correlationsearch.annotations = {"analytic_story": ["ColdRoot MacOS RAT"], "cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Command and Control"], "nist": ["DE.DP"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search looks for processes in an MacOS system that is tapping keyboard events in MacOS, and essentially monitoring all keystrokes made by a user. This is a common technique used by RATs to log keystrokes from a victim, although it can also be used by legitimate processes like Siri to react on human input +action.notable.param.rule_title = Processes Tapping Keyboard Events +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -8749,6 +10486,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Processes created by netsh - Rule action.correlationsearch.annotations = {"analytic_story": ["Netsh Abuse"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1562.004"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for processes launching netsh.exe to execute various commands via the netsh command-line utility. Netsh.exe is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper .dll when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe that are executing commands via the command line. Deprecated because we have another detection of the same type. +action.notable.param.rule_title = Processes created by netsh +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -8783,6 +10526,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Processes launching netsh - Rule action.correlationsearch.annotations = {"analytic_story": ["Netsh Abuse", "Disabling Security Tools", "DHS Report TA18-074A"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1562.004"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for processes launching netsh.exe. Netsh is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper DLL when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe and executing commands via the command line. +action.notable.param.rule_title = Processes launching netsh +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -8817,6 +10566,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Prohibited Network Traffic Allowed - Rule action.correlationsearch.annotations = {"analytic_story": ["Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "Command and Control"], "cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Delivery", "Command and Control"], "mitre_attack": ["T1048"], "nist": ["DE.AE", "PR.AC"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search looks for network traffic defined by port and transport layer protocol in the Enterprise Security lookup table "lookup_interesting_ports", that is marked as prohibited, and has an associated 'allow' action in the Network_Traffic data model. This could be indicative of a misconfigured network device. +action.notable.param.rule_title = Prohibited Network Traffic Allowed +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -8851,6 +10605,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Prohibited Software On Endpoint - Rule action.correlationsearch.annotations = {"analytic_story": ["Monitor for Unauthorized Software", "Emotet Malware DHS Report TA18-201A ", "SamSam Ransomware"], "cis20": ["CIS 2"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for applications on the endpoint that you have marked as prohibited. +action.notable.param.rule_title = Prohibited Software On Endpoint +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -8885,6 +10645,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Protocol or Port Mismatch - Rule action.correlationsearch.annotations = {"analytic_story": ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control"], "cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048.003"], "nist": ["DE.AE", "PR.AC"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search looks for network traffic on common ports where a higher layer protocol does not match the port that is being used. For example, this search should identify cases where protocols other than HTTP are running on TCP port 80. This can be used by attackers to circumvent firewall restrictions, or as an attempt to hide malicious communications over ports and protocols that are typically allowed and not well inspected. +action.notable.param.rule_title = Protocol or Port Mismatch +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -8919,6 +10684,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Protocols passing authentication in cleartext - Rule action.correlationsearch.annotations = {"analytic_story": ["Use of Cleartext Protocols"], "cis20": ["CIS 9", "CIS 14"], "kill_chain_phases": ["Reconnaissance", "Actions on Objectives"], "nist": ["PR.PT", "DE.AE", "PR.AC", "PR.DS"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest', 'src'] +action.notable.param.rule_description = This search looks for cleartext protocols at risk of leaking credentials. Currently, this consists of legacy protocols such as telnet, POP3, IMAP, and non-anonymous FTP sessions. While some of these protocols can be used over SSL, they typically run on different assigned ports in those cases. +action.notable.param.rule_title = Protocols passing authentication in cleartext +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -8953,6 +10724,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Ransomware Notes bulk creation - Rule action.correlationsearch.annotations = {"analytic_story": ["Clop Ransomware"], "kill_chain_phases": ["Obfuscation"], "mitre_attack": ["T1486"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = The following analytics identifies a big number of instance of ransomware notes (filetype e.g .txt, .html, .hta) file creation to the infected machine. This behavior is a good sensor if the ransomware note filename is quite new for security industry or the ransomware note filename is not in your lookup table list for monitoring. +action.notable.param.rule_title = Ransomware Notes bulk creation +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -8987,6 +10763,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule action.correlationsearch.annotations = {"analytic_story": ["Windows Service Abuse", "Windows Persistence Techniques"], "cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack": ["T1574.011"], "nist": ["PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The search looks for reg.exe modifying registry keys that define Windows services and their configurations. +action.notable.param.rule_title = Reg exe Manipulating Windows Services Registry Keys +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -9021,6 +10803,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Reg exe used to hide files directories via registry keys - Rule action.correlationsearch.annotations = {"analytic_story": ["Windows Defense Evasion Tactics", "Suspicious Windows Registry Activities", "Windows Persistence Techniques"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1564.001"], "nist": ["DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The search looks for command-line arguments used to hide a file or directory using the reg add command. +action.notable.param.rule_title = Reg exe used to hide files directories via registry keys +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -9055,6 +10843,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Registry Keys Used For Persistence - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious Windows Registry Activities", "Suspicious MSHTA Activity", "DHS Report TA18-074A", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Ransomware", "Windows Persistence Techniques", "Emotet Malware DHS Report TA18-201A "], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1547.001"], "nist": ["PR.PT", "DE.CM", "DE.AE"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The search looks for modifications to registry keys that can be used to launch an application or service at system startup. +action.notable.param.rule_title = Registry Keys Used For Persistence +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -9089,6 +10883,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Registry Keys Used For Privilege Escalation - Rule action.correlationsearch.annotations = {"analytic_story": ["Windows Privilege Escalation", "Suspicious Windows Registry Activities", "Cloud Federated Credential Abuse"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1546.012"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for modifications to registry keys that can be used to elevate privileges. The registry keys under "Image File Execution Options" are used to intercept calls to an executable and can be used to attach malicious binaries to benign system binaries. +action.notable.param.rule_title = Registry Keys Used For Privilege Escalation +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -9123,6 +10923,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Registry Keys for Creating SHIM Databases - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious Windows Registry Activities", "Windows Persistence Techniques"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1546.011"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for registry activity associated with application compatibility shims, which can be leveraged by attackers for various nefarious purposes. +action.notable.param.rule_title = Registry Keys for Creating SHIM Databases +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -9157,6 +10963,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Remote Desktop Network Bruteforce - Rule action.correlationsearch.annotations = {"analytic_story": ["SamSam Ransomware", "Ryuk Ransomware"], "cis20": ["CIS 12", "CIS 9", "CIS 16"], "kill_chain_phases": ["Reconnaissance", "Delivery"], "mitre_attack": ["T1021.001"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest', 'src'] +action.notable.param.rule_description = This search looks for RDP application network traffic and filters any source/destination pair generating more than twice the standard deviation of the average traffic. +action.notable.param.rule_title = Remote Desktop Network Bruteforce +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -9191,6 +11003,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Remote Desktop Network Traffic - Rule action.correlationsearch.annotations = {"analytic_story": ["SamSam Ransomware", "Ryuk Ransomware", "Hidden Cobra Malware", "Lateral Movement"], "cis20": ["CIS 3", "CIS 9", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1021.001"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest', 'src'] +action.notable.param.rule_description = This search looks for network traffic on TCP/3389, the default port used by remote desktop. While remote desktop traffic is not uncommon on a network, it is usually associated with known hosts. This search will ignore common RDP sources and common RDP destinations so you can focus on the uncommon uses of remote desktop on your network. +action.notable.param.rule_title = Remote Desktop Network Traffic +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -9225,6 +11043,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Remote Desktop Process Running On System - Rule action.correlationsearch.annotations = {"analytic_story": ["Hidden Cobra Malware", "Lateral Movement"], "cis20": ["CIS 3", "CIS 9", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1021.001"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for the remote desktop process mstsc.exe running on systems upon which it doesn't typically run. This is accomplished by filtering out all systems that are noted in the `common_rdp_source category` in the Assets and Identity framework. +action.notable.param.rule_title = Remote Desktop Process Running On System +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -9259,6 +11083,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Remote Process Instantiation via WMI - Rule action.correlationsearch.annotations = {"analytic_story": ["Ransomware", "Suspicious WMI Use"], "cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for wmic.exe being launched with parameters to spawn a process on a remote system. +action.notable.param.rule_title = Remote Process Instantiation via WMI +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -9274,7 +11104,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search monitors for remote modifications to registry keys. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search monitors for remote modifications to registry keys. action.escu.how_to_implement = To successfully implement this search, you must populate the `Endpoint` data model. This is typically populated via endpoint detection-and-response product, such as Carbon Black, or endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the registry. Deprecated because I don't think the logic is right. action.escu.known_false_positives = This technique may be legitimately used by administrators to modify remote registries, so it's important to filter these events out. @@ -9293,6 +11123,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Remote Registry Key modifications - Rule action.correlationsearch.annotations = {"analytic_story": ["Windows Defense Evasion Tactics", "Suspicious Windows Registry Activities", "Windows Persistence Techniques"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search monitors for remote modifications to registry keys. +action.notable.param.rule_title = Remote Registry Key modifications +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -9301,7 +11137,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count values(Registry.registry_key_name) as registry_key_name values(Registry.registry_path) as registry_path min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Registry where Registry.registry_path="\\\\*" by Registry.dest , Registry.user | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `drop_dm_object_name(Registry)` | `remote_registry_key_modifications_filter` +search = | tstats `security_content_summariesonly` count values(Registry.registry_key_name) as registry_key_name values(Registry.registry_path) as registry_path min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Registry where Registry.registry_path="\\\\*" by Registry.dest , Registry.user | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `drop_dm_object_name(Registry)` | `remote_registry_key_modifications_filter` [ESCU - Remote WMI Command Attempt - Rule] action.escu = 0 @@ -9327,6 +11163,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Remote WMI Command Attempt - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious WMI Use"], "cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for wmic.exe being launched with parameters to operate on remote systems. +action.notable.param.rule_title = Remote WMI Command Attempt +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -9361,6 +11203,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Resize ShadowStorage volume - Rule action.correlationsearch.annotations = {"analytic_story": ["Clop Ransomware"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1490"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The following analytics identifies the resizing of shadowstorage by ransomware malware to avoid the shadow volumes being made again. this technique is an alternative by ransomware attacker than deleting the shadowstorage which is known alert in defensive team. one example of ransomware that use this technique is CLOP ransomware where it drops a .bat file that will resize the shadowstorage to minimum size as much as possible +action.notable.param.rule_title = Resize ShadowStorage volume +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -9395,6 +11243,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - RunDLL Loading DLL By Ordinal - Rule action.correlationsearch.annotations = {"analytic_story": ["Unusual Processes"], "cis20": ["CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack": ["T1218.011"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for executing scripts with rundll32. Adversaries may abuse rundll32.exe to proxy execution of malicious code. Using rundll32.exe, vice executing directly, may avoid triggering security tools that may not monitor execution of the rundll32.exe process because of allowlists or false positives from normal operations. +action.notable.param.rule_title = RunDLL Loading DLL By Ordinal +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -9429,6 +11283,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Ryuk Test Files Detected - Rule action.correlationsearch.annotations = {"analytic_story": ["Ryuk Ransomware"], "cis20": ["CIS 8"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1486"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = The search looks for files that contain the key word *Ryuk* under any folder in the C drive, which is consistent with Ryuk propagation. +action.notable.param.rule_title = Ryuk Test Files Detected +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -9463,6 +11322,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Ryuk Wake on LAN Command - Rule action.correlationsearch.annotations = {"analytic_story": ["Ryuk Ransomware"], "kill_chain_phases": ["Exploitation", "Lateral Movement"], "mitre_attack": ["T1059.003"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This Splunk query identifies the use of Wake-on-LAN utilized by Ryuk ransomware. The Ryuk Ransomware uses the Wake-on-Lan feature to turn on powered off devices on a compromised network to have greater success encrypting them. This is a high fidelity indicator of Ryuk ransomware executing on an endpoint. Upon triage, isolate the endpoint. Additional file modification events will be within the users profile (\appdata\roaming) and in public directories (users\public\). Review all Scheduled Tasks on the isolated endpoint and across the fleet. Suspicious Scheduled Tasks will include a path to a unknown binary and those endpoints should be isolated until triaged. +action.notable.param.rule_title = Ryuk Wake on LAN Command +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -9497,6 +11362,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - SMB Traffic Spike - Rule action.correlationsearch.annotations = {"analytic_story": ["Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Ransomware", "DHS Report TA18-074A"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1021.002"], "nist": ["DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['src'] +action.notable.param.rule_description = This search looks for spikes in the number of Server Message Block (SMB) traffic connections. +action.notable.param.rule_title = SMB Traffic Spike +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -9534,6 +11405,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - SMB Traffic Spike - MLTK - Rule action.correlationsearch.annotations = {"analytic_story": ["Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Ransomware", "DHS Report TA18-074A"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1021.002"], "nist": ["DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest', 'src'] +action.notable.param.rule_description = This search uses the Machine Learning Toolkit (MLTK) to identify spikes in the number of Server Message Block (SMB) connections. +action.notable.param.rule_title = SMB Traffic Spike - MLTK +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -9568,6 +11445,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - SQL Injection with Long URLs - Rule action.correlationsearch.annotations = {"analytic_story": ["SQL Injection"], "cis20": ["CIS 4", "CIS 13", "CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1190"], "nist": ["PR.DS", "ID.RA", "PR.PT", "PR.IP", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest', 'src'] +action.notable.param.rule_description = This search looks for long URLs that have several SQL commands visible within them. +action.notable.param.rule_title = SQL Injection with Long URLs +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -9602,6 +11485,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Samsam Test File Write - Rule action.correlationsearch.annotations = {"analytic_story": ["SamSam Ransomware"], "cis20": ["CIS 8"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1486"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The search looks for a file named "test.txt" written to the windows system directory tree, which is consistent with Samsam propagation. +action.notable.param.rule_title = Samsam Test File Write +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -9636,6 +11525,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Sc exe Manipulating Windows Services - Rule action.correlationsearch.annotations = {"analytic_story": ["Windows Service Abuse", "DHS Report TA18-074A", "Orangeworm Attack Group", "Windows Persistence Techniques", "Disabling Security Tools", "NOBELIUM Group"], "cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack": ["T1543.003"], "nist": ["PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for arguments to sc.exe indicating the creation or modification of a Windows service. +action.notable.param.rule_title = Sc exe Manipulating Windows Services +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -9670,6 +11565,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Scheduled Task Deleted Or Created via CMD - Rule action.correlationsearch.annotations = {"analytic_story": ["DHS Report TA18-074A", "NOBELIUM Group"], "cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053.005"], "nist": ["PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for flags passed to schtasks.exe on the command-line that indicate a task was created via command like. This has been associated with the Dragonfly threat actor, and the SUNBURST attack against Solarwinds. +action.notable.param.rule_title = Scheduled Task Deleted Or Created via CMD +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -9704,6 +11605,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Scheduled tasks used in BadRabbit ransomware - Rule action.correlationsearch.annotations = {"analytic_story": ["Ransomware"], "cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053.005"], "nist": ["PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search looks for flags passed to schtasks.exe on the command-line that indicate that task names related to the execution of Bad Rabbit ransomware were created or deleted. Deprecated because we already have a similar detection +action.notable.param.rule_title = Scheduled tasks used in BadRabbit ransomware +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -9738,6 +11645,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Schtasks scheduling job on remote system - Rule action.correlationsearch.annotations = {"analytic_story": ["Lateral Movement", "NOBELIUM Group"], "cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053.005"], "nist": ["PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for flags passed to schtasks.exe on the command-line that indicate a job is being scheduled on a remote system. +action.notable.param.rule_title = Schtasks scheduling job on remote system +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -9772,6 +11685,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Schtasks used for forcing a reboot - Rule action.correlationsearch.annotations = {"analytic_story": ["Windows Persistence Techniques", "Ransomware"], "cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053.005"], "nist": ["PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for flags passed to schtasks.exe on the command-line that indicate that a forced reboot of system is scheduled. +action.notable.param.rule_title = Schtasks used for forcing a reboot +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -9806,6 +11725,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Script Execution via WMI - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious WMI Use"], "cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for scripts launched via WMI. +action.notable.param.rule_title = Script Execution via WMI +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -9840,6 +11765,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Shim Database File Creation - Rule action.correlationsearch.annotations = {"analytic_story": ["Windows Persistence Techniques"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1546.011"], "nist": ["DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search looks for shim database files being written to default directories. The sdbinst.exe application is used to install shim database files (.sdb). According to Microsoft, a shim is a small library that transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. +action.notable.param.rule_title = Shim Database File Creation +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -9874,6 +11805,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Shim Database Installation With Suspicious Parameters - Rule action.correlationsearch.annotations = {"analytic_story": ["Windows Persistence Techniques"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1546.011"], "nist": ["DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search detects the process execution and arguments required to silently create a shim database. The sdbinst.exe application is used to install shim database files (.sdb). A shim is a small library which transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. +action.notable.param.rule_title = Shim Database Installation With Suspicious Parameters +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -9908,6 +11845,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Short Lived Windows Accounts - Rule action.correlationsearch.annotations = {"analytic_story": ["Account Monitoring and Controls"], "cis20": ["CIS 16"], "mitre_attack": ["T1136.001"], "nist": ["PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search detects accounts that were created and deleted in a short time period. +action.notable.param.rule_title = Short Lived Windows Accounts +action.notable.param.security_domain = access +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -9942,6 +11885,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Single Letter Process On Endpoint - Rule action.correlationsearch.annotations = {"analytic_story": ["DHS Report TA18-074A"], "cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1204.002"], "nist": ["ID.AM", "PR.DS"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search looks for process names that consist only of a single letter. +action.notable.param.rule_title = Single Letter Process On Endpoint +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -9976,6 +11924,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Spectre and Meltdown Vulnerable Systems - Rule action.correlationsearch.annotations = {"analytic_story": ["Spectre And Meltdown Vulnerabilities"], "cis20": ["CIS 4"], "nist": ["ID.RA", "RS.MI", "PR.IP", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The search is used to detect systems that are still vulnerable to the Spectre and Meltdown vulnerabilities. +action.notable.param.rule_title = Spectre and Meltdown Vulnerable Systems +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -10010,6 +11964,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Spike in File Writes - Rule action.correlationsearch.annotations = {"analytic_story": ["SamSam Ransomware", "Ryuk Ransomware", "Ransomware"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The search looks for a sharp increase in the number of files written to a particular host +action.notable.param.rule_title = Spike in File Writes +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -10044,6 +12004,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Splunk Enterprise Information Disclosure - Rule action.correlationsearch.annotations = {"analytic_story": ["Splunk Enterprise Vulnerability CVE-2018-11409"], "cis20": ["CIS 3", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "RS.MI", "PR.PT", "PR.AC", "PR.IP", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search allows you to look for evidence of exploitation for CVE-2018-11409, a Splunk Enterprise Information Disclosure Bug. +action.notable.param.rule_title = Splunk Enterprise Information Disclosure +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -10078,6 +12044,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Sunburst Correlation DLL and Network Event - Rule action.correlationsearch.annotations = {"analytic_story": ["NOBELIUM Group"], "cis20": ["CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1203"], "nist": ["DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The malware sunburst will load the malicious dll by SolarWinds.BusinessLayerHost.exe. After a period of 12-14 days, the malware will attempt to resolve a subdomain of avsvmcloud.com. This detections will correlate both events. +action.notable.param.rule_title = Sunburst Correlation DLL and Network Event +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -10112,6 +12084,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Supernova Webshell - Rule action.correlationsearch.annotations = {"analytic_story": ["NOBELIUM Group"], "cis20": ["CIS 4", "CIS 13", "CIS 18"], "kill_chain_phases": ["Exfiltration"], "mitre_attack": ["T1505.003"], "nist": ["PR.DS", "ID.RA", "PR.PT", "PR.IP", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest', 'src'] +action.notable.param.rule_description = This search aims to detect the Supernova webshell used in the SUNBURST attack. +action.notable.param.rule_title = Supernova Webshell +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -10127,7 +12105,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for changes to registry values that control Windows file associations, executed by a process that is not typical for legitimate, routine changes to this area. action.escu.mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1546.001"], "nist": ["DE.CM", "PR.PT", "PR.IP"]} -action.escu.data_models = [] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search looks for changes to registry values that control Windows file associations, executed by a process that is not typical for legitimate, routine changes to this area. action.escu.how_to_implement = To successfully implement this search you need to be ingesting information on registry changes that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` and `Registry` nodes. action.escu.known_false_positives = There may be other processes in your environment that users may legitimately use to modify file associations. If this is the case and you are finding false positives, you can modify the search to add those processes as exceptions. @@ -10146,6 +12124,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Suspicious Changes to File Associations - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious Windows Registry Activities", "Windows File Extension and Association Abuse"], "cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1546.001"], "nist": ["DE.CM", "PR.PT", "PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search looks for changes to registry values that control Windows file associations, executed by a process that is not typical for legitimate, routine changes to this area. +action.notable.param.rule_title = Suspicious Changes to File Associations +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -10154,7 +12138,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Processes.process_name) as process_name values(Processes.parent_process_name) as parent_process_name FROM datamodel=Endpoint.Processes where Processes.process_name!=Explorer.exe AND Processes.process_name!=OpenWith.exe by Processes.process_id Processes.dest | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | join [| tstats `security_content_summariesonly` values(Registry.registry_path) as registry_path count FROM datamodel=Endpoint.Registry where Registry.registry_path=*\\Explorer\\FileExts* by Registry.process_id Registry.dest | `drop_dm_object_name("Registry")` | table process_id dest registry_path]| `suspicious_changes_to_file_associations_filter` +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Processes.process_name) as process_name values(Processes.parent_process_name) as parent_process_name FROM datamodel=Endpoint.Processes where Processes.process_name!=Explorer.exe AND Processes.process_name!=OpenWith.exe by Processes.process_id Processes.dest | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | join [| tstats `security_content_summariesonly` values(Registry.registry_path) as registry_path count from datamodel=Endpoint.Registry where Registry.registry_path=*\\Explorer\\FileExts* by Registry.process_id Registry.dest | `drop_dm_object_name("Registry")` | table process_id dest registry_path]| `suspicious_changes_to_file_associations_filter` [ESCU - Suspicious Curl Network Connection - Rule] action.escu = 0 @@ -10180,6 +12164,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Suspicious Curl Network Connection - Rule action.correlationsearch.annotations = {"analytic_story": ["Silver Sparrow", "Ingress Tool Transfer"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1105"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The following analytic identifies the use of a curl contacting suspicious remote domains to checkin to command and control servers or download further implants. In the context of Silver Sparrow, curl is identified contacting s3.amazonaws.com. This particular behavior is common with MacOS adware-malicious software. +action.notable.param.rule_title = Suspicious Curl Network Connection +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -10214,6 +12204,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Suspicious DLLHost no Command Line Arguments - Rule action.correlationsearch.annotations = {"analytic_story": ["Cobalt Strike"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1055"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The following analytic identifies DLLHost.exe with no command line arguments. It is unusual for DLLHost.exe to execute with no command line arguments present. This particular behavior is common with malicious software, including Cobalt Strike. During investigation, identify any network connections and parallel processes. Identify any suspicious module loads related to credential dumping or file writes. DLLHost.exe is natively found in C:\Windows\system32 and C:\Windows\syswow64. +action.notable.param.rule_title = Suspicious DLLHost no Command Line Arguments +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -10248,6 +12244,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Suspicious Email - UBA Anomaly - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious Emails"], "cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1566"], "nist": ["PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This detection looks for emails that are suspicious because of their sender, domain rareness, or behavior differences. This is an anomaly generated by Splunk User Behavior Analytics (UBA). +action.notable.param.rule_title = Suspicious Email - UBA Anomaly +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -10284,6 +12286,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Suspicious Email Attachment Extensions - Rule action.correlationsearch.annotations = {"analytic_story": ["Emotet Malware DHS Report TA18-201A ", "Suspicious Emails"], "cis20": ["CIS 3", "CIS 7", "CIS 12"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1566.001"], "nist": ["DE.AE", "PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search looks for emails that have attachments with suspicious file extensions. +action.notable.param.rule_title = Suspicious Email Attachment Extensions +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -10318,6 +12325,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Suspicious File Write - Rule action.correlationsearch.annotations = {"analytic_story": ["Hidden Cobra Malware"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The search looks for files created with names that have been linked to malicious activity. +action.notable.param.rule_title = Suspicious File Write +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -10352,6 +12365,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Suspicious GPUpdate no Command Line Arguments - Rule action.correlationsearch.annotations = {"analytic_story": ["Cobalt Strike"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1055"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The following analytic identifies gpupdate.exe with no command line arguments. It is unusual for gpupdate.exe to execute with no command line arguments present. This particular behavior is common with malicious software, including Cobalt Strike. During investigation, identify any network connections and parallel processes. Identify any suspicious module loads related to credential dumping or file writes. gpupdate.exe is natively found in C:\Windows\system32 and C:\Windows\syswow64. +action.notable.param.rule_title = Suspicious GPUpdate no Command Line Arguments +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -10386,6 +12405,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Suspicious Java Classes - Rule action.correlationsearch.annotations = {"analytic_story": ["Apache Struts Vulnerability"], "cis20": ["CIS 7", "CIS 12"], "kill_chain_phases": ["Exploitation"], "nist": ["DE.AE"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest', 'src'] +action.notable.param.rule_description = This search looks for suspicious Java classes that are often used to exploit remote command execution in common Java frameworks, such as Apache Struts. +action.notable.param.rule_title = Suspicious Java Classes +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -10420,6 +12445,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Suspicious MSBuild Rename - Rule action.correlationsearch.annotations = {"analytic_story": ["Trusted Developer Utilities Proxy Execution MSBuild", "Cobalt Strike"], "cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1127.001", "T1036.003"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The following analytic identifies renamed instances of msbuild.exe executing. Msbuild.exe is natively found in C:\Windows\Microsoft.NET\Framework\v4.0.30319 and C:\Windows\Microsoft.NET\Framework64\v4.0.30319. During investigation, identify the code executed and what is executing a renamed instance of MSBuild. +action.notable.param.rule_title = Suspicious MSBuild Rename +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -10454,6 +12485,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Suspicious MSBuild Spawn - Rule action.correlationsearch.annotations = {"analytic_story": ["Trusted Developer Utilities Proxy Execution MSBuild"], "cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1127.001"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The following analytic identifies wmiprvse.exe spawning msbuild.exe. This behavior is indicative of a COM object being utilized to spawn msbuild from wmiprvse.exe. It is common for MSBuild.exe to be spawned from devenv.exe while using Visual Studio. In this instance, there will be command line arguments and file paths. In a malicious instance, MSBuild.exe will spawn from non-standard processes and have no command line arguments. For example, MSBuild.exe spawning from explorer.exe, powershell.exe is far less common and should be investigated. +action.notable.param.rule_title = Suspicious MSBuild Spawn +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -10502,6 +12539,19 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Suspicious PlistBuddy Usage - Rule action.correlationsearch.annotations = {"analytic_story": ["Silver Sparrow"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1543.001"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The following analytic identifies the use of a native MacOS utility, PlistBuddy, creating or modifying a properly list (.plist) file. In the instance of Silver Sparrow, the following commands were executed:\ +- PlistBuddy -c "Add :Label string init_verx" ~/Library/Launchagents/init_verx.plist \ +- PlistBuddy -c "Add :RunAtLoad bool true" ~/Library/Launchagents/init_verx.plist \ +- PlistBuddy -c "Add :StartInterval integer 3600" ~/Library/Launchagents/init_verx.plist \ +- PlistBuddy -c "Add :ProgramArguments array" ~/Library/Launchagents/init_verx.plist \ +- PlistBuddy -c "Add :ProgramArguments:0 string /bin/sh" ~/Library/Launchagents/init_verx.plist \ +- PlistBuddy -c "Add :ProgramArguments:1 string -c" ~/Library/Launchagents/init_verx.plist \ +Upon triage, capture the property list file being written to disk and review for further indicators. Contain the endpoint and triage further. +action.notable.param.rule_title = Suspicious PlistBuddy Usage +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -10550,6 +12600,18 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Suspicious PlistBuddy Usage via OSquery - Rule action.correlationsearch.annotations = {"analytic_story": ["Silver Sparrow"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1543.001"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = The following analytic identifies the use of a native MacOS utility, PlistBuddy, creating or modifying a properly list (.plist) file. In the instance of Silver Sparrow, the following commands were executed:\ +- PlistBuddy -c "Add :Label string init_verx" ~/Library/Launchagents/init_verx.plist \ +- PlistBuddy -c "Add :RunAtLoad bool true" ~/Library/Launchagents/init_verx.plist \ +- PlistBuddy -c "Add :StartInterval integer 3600" ~/Library/Launchagents/init_verx.plist \ +- PlistBuddy -c "Add :ProgramArguments array" ~/Library/Launchagents/init_verx.plist \ +- PlistBuddy -c "Add :ProgramArguments:0 string /bin/sh" ~/Library/Launchagents/init_verx.plist \ +- PlistBuddy -c "Add :ProgramArguments:1 string -c" ~/Library/Launchagents/init_verx.plist \ +Upon triage, capture the property list file being written to disk and review for further indicators. Contain the endpoint and triage further. +action.notable.param.rule_title = Suspicious PlistBuddy Usage via OSquery +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -10584,6 +12646,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Suspicious Reg exe Process - Rule action.correlationsearch.annotations = {"analytic_story": ["Windows Defense Evasion Tactics", "Disabling Security Tools", "DHS Report TA18-074A"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1112"], "nist": ["DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for reg.exe being launched from a command prompt not started by the user. When a user launches cmd.exe, the parent process is usually explorer.exe. This search filters out those instances. +action.notable.param.rule_title = Suspicious Reg exe Process +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -10618,6 +12686,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Suspicious Regsvr32 Register Suspicious Path - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious Regsvr32 Activity"], "cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1218.010"], "nist": ["DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = Adversaries may abuse Regsvr32.exe to proxy execution of malicious code by using non-standard file extensions to load malciious DLLs. Upon investigating, look for network connections to remote destinations (internal or external). Review additional parrallel processes and child processes for additional activity. +action.notable.param.rule_title = Suspicious Regsvr32 Register Suspicious Path +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -10652,6 +12726,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Suspicious Rundll32 Rename - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious Rundll32 Activity"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1218.011", "T1036.003"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The following analytic identifies renamed instances of rundll32.exe executing. rundll32.exe is natively found in C:\Windows\system32 and C:\Windows\syswow64. During investigation, validate it is the legitimate rundll32.exe executing and what script content it is loading. This query relies on the OriginalFileName from Sysmon, or internal name from the PE meta data. Expand the query as needed by looking for specific command line arguments outlined in other analytics. +action.notable.param.rule_title = Suspicious Rundll32 Rename +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -10686,6 +12766,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Suspicious Rundll32 StartW - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious Rundll32 Activity", "Cobalt Strike"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1218.011"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The following analytic identifies rundll32.exe executing a DLL function name, Start and StartW, on the command line that is commonly observed with Cobalt Strike x86 and x64 DLL payloads. Rundll32.exe is natively found in C:\Windows\system32 and C:\Windows\syswow64. Typically, the DLL will be written and loaded from a world writeable path or user location. In most instances it will not have a valid certificate (Unsigned). During investigation, review the parent process and other parallel application execution. Capture and triage the DLL in question. In the instance of Cobalt Strike, rundll32.exe is the default process it opens and injects shellcode into. This default process can be changed, but typically is not. +action.notable.param.rule_title = Suspicious Rundll32 StartW +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -10720,6 +12806,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Suspicious Rundll32 dllregisterserver - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious Rundll32 Activity"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1218.011"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The following analytic identifies rundll32.exe using dllregisterserver on the command line to load a DLL. When a DLL is registered, the DllRegisterServer method entry point in the DLL is invoked. This is typically seen when a DLL is being registered on the system. Not every instance is considered malicious, but it will capture malicious use of it. During investigation, review the parent process and parrellel processes executing. Capture the DLL being loaded and inspect further. Rundll32.exe is natively found in C:\Windows\system32 and C:\Windows\syswow64. +action.notable.param.rule_title = Suspicious Rundll32 dllregisterserver +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -10754,6 +12846,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Suspicious Rundll32 no Command Line Arguments - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious Rundll32 Activity", "Cobalt Strike"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1218.011"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The following analytic identifies rundll32.exe with no command line arguments. It is unusual for rundll32.exe to execute with no command line arguments present. This particular behavior is common with malicious software, including Cobalt Strike. During investigation, identify any network connections and parallel processes. Identify any suspicious module loads related to credential dumping or file writes. Rundll32.exe is natively found in C:\Windows\system32 and C:\Windows\syswow64. +action.notable.param.rule_title = Suspicious Rundll32 no Command Line Arguments +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -10788,6 +12886,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Suspicious SQLite3 LSQuarantine Behavior - Rule action.correlationsearch.annotations = {"analytic_story": ["Silver Sparrow"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1074"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The following analytic identifies the use of a SQLite3 querying the MacOS preferences to identify the original URL the pkg was downloaded from. This particular behavior is common with MacOS adware-malicious software. Upon triage, review other processes in parallel for suspicious activity. Identify any recent package installations. +action.notable.param.rule_title = Suspicious SQLite3 LSQuarantine Behavior +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -10822,6 +12926,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Suspicious Scheduled Task from Public Directory - Rule action.correlationsearch.annotations = {"analytic_story": ["Ransomware", "Ryuk Ransomware", "Windows Persistence Techniques"], "kill_chain_phases": ["Exploitation", "Privilege Escalation"], "mitre_attack": ["T1053.005"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The following detection identifies Scheduled Tasks registering (creating a new task) a binary or script to run from a public directory which includes users\public, \programdata\ and \windows\temp. Upon triage, review the binary or script in the command line for legitimacy, whether an approved binary/script or not. In addition, capture the binary or script in question and analyze for further behaviors. Identify the source and contain the endpoint. +action.notable.param.rule_title = Suspicious Scheduled Task from Public Directory +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -10856,6 +12966,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Suspicious SearchProtocolHost no Command Line Arguments - Rule action.correlationsearch.annotations = {"analytic_story": ["Cobalt Strike"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1055"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The following analytic identifies searchprotocolhost.exe with no command line arguments. It is unusual for searchprotocolhost.exe to execute with no command line arguments present. This particular behavior is common with malicious software, including Cobalt Strike. During investigation, identify any network connections and parallel processes. Identify any suspicious module loads related to credential dumping or file writes. searchprotocolhost.exe is natively found in C:\Windows\system32 and C:\Windows\syswow64. +action.notable.param.rule_title = Suspicious SearchProtocolHost no Command Line Arguments +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -10890,6 +13006,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Suspicious microsoft workflow compiler rename - Rule action.correlationsearch.annotations = {"analytic_story": ["Trusted Developer Utilities Proxy Execution", "Cobalt Strike"], "cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1127", "T1036.003"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The following analytic identifies a renamed instance of microsoft.workflow.compiler.exe. Microsoft.workflow.compiler.exe is natively found in C:\Windows\Microsoft.NET\Framework64\v4.0.30319 and is rarely utilized. When investigating, identify the executed code on disk and review. A spawned child process from microsoft.workflow.compiler.exe is uncommon. In any instance, microsoft.workflow.compiler.exe spawning from an Office product or any living off the land binary is highly suspect. +action.notable.param.rule_title = Suspicious microsoft workflow compiler rename +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -10924,6 +13046,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Suspicious microsoft workflow compiler usage - Rule action.correlationsearch.annotations = {"analytic_story": ["Trusted Developer Utilities Proxy Execution"], "cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1127"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The following analytic identifies microsoft.workflow.compiler.exe usage. microsoft.workflow.compiler.exe is natively found in C:\Windows\Microsoft.NET\Framework64\v4.0.30319 and is rarely utilized. When investigating, identify the executed code on disk and review. It is not a commonly used process by many applications. +action.notable.param.rule_title = Suspicious microsoft workflow compiler usage +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -10958,6 +13086,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Suspicious msbuild path - Rule action.correlationsearch.annotations = {"analytic_story": ["Trusted Developer Utilities Proxy Execution MSBuild", "Cobalt Strike"], "cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1127.001", "T1036.003"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The following analytic identifies msbuild.exe executing from a non-standard path. Msbuild.exe is natively found in C:\Windows\Microsoft.NET\Framework\v4.0.30319 and C:\Windows\Microsoft.NET\Framework64\v4.0.30319. Instances of Visual Studio will run a copy of msbuild.exe. A moved instance of MSBuild is suspicious, however there are instances of build applications that will move or use a copy of MSBuild. +action.notable.param.rule_title = Suspicious msbuild path +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -10992,6 +13126,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Suspicious mshta child process - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious MSHTA Activity"], "cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1218.005"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The following analytic identifies child processes spawning from "mshta.exe". The search will return the first time and last time these command-line arguments were used for these executions, as well as the target system, the user, parent process "mshta.exe" and its child process. +action.notable.param.rule_title = Suspicious mshta child process +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -11026,6 +13166,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Suspicious mshta spawn - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious MSHTA Activity"], "cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1218.005"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The following analytic identifies wmiprvse.exe spawning mshta.exe. This behavior is indicative of a DCOM object being utilized to spawn mshta from wmiprvse.exe or svchost.exe. In this instance, adversaries may use LethalHTA that will spawn mshta.exe from svchost.exe. +action.notable.param.rule_title = Suspicious mshta spawn +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -11060,6 +13206,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Suspicious wevtutil Usage - Rule action.correlationsearch.annotations = {"analytic_story": ["Windows Log Manipulation", "Ransomware", "Clop Ransomware"], "cis20": ["CIS 3", "CIS 5", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070.001"], "nist": ["DE.DP", "PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.AE"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The wevtutil.exe application is the windows event log utility. This searches for wevtutil.exe with parameters for clearing the application, security, setup, or system event logs. +action.notable.param.rule_title = Suspicious wevtutil Usage +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -11094,6 +13246,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Suspicious writes to System Volume Information - Rule action.correlationsearch.annotations = {"analytic_story": ["Collection and Staging"], "cis20": ["CIS 8"], "mitre_attack": ["T1036"], "nist": ["DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search detects writes to the 'System Volume Information' folder by something other than the System process. +action.notable.param.rule_title = Suspicious writes to System Volume Information +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -11128,6 +13285,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Suspicious writes to windows Recycle Bin - Rule action.correlationsearch.annotations = {"analytic_story": ["Collection and Staging"], "cis20": ["CIS 8"], "mitre_attack": ["T1036"], "nist": ["DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search detects writes to the recycle bin by a process other than explorer.exe. +action.notable.param.rule_title = Suspicious writes to windows Recycle Bin +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -11162,6 +13325,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - System Information Discovery Detection - Rule action.correlationsearch.annotations = {"analytic_story": ["Discovery Techniques"], "cis20": ["CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1082"], "nist": ["DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = Detect system information discovery techniques used by attackers to understand configurations of the system to further exploit it. +action.notable.param.rule_title = System Information Discovery Detection +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -11196,6 +13365,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - System Processes Run From Unexpected Locations - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious Command-Line Executions", "Unusual Processes", "Ransomware"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1036.003"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for system processes that normally run out of C:\Windows\System32\ or C:\Windows\SysWOW64 that are not run from that location. This can indicate a malicious process that is trying to hide as a legitimate process. +action.notable.param.rule_title = System Processes Run From Unexpected Locations +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -11230,6 +13405,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - TOR Traffic - Rule action.correlationsearch.annotations = {"analytic_story": ["Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "Command and Control", "NOBELIUM Group"], "cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1071.001"], "nist": ["DE.AE"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search looks for network traffic identified as The Onion Router (TOR), a benign anonymity network which can be abused for a variety of nefarious purposes. +action.notable.param.rule_title = TOR Traffic +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -11264,6 +13444,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - USN Journal Deletion - Rule action.correlationsearch.annotations = {"analytic_story": ["Windows Log Manipulation", "Ransomware"], "cis20": ["CIS 6", "CIS 8", "CIS 10"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.CM", "PR.PT", "DE.AE", "DE.DP", "PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The fsutil.exe application is a legitimate Windows utility used to perform tasks related to the file allocation table (FAT) and NTFS file systems. The update sequence number (USN) change journal provides a log of all changes made to the files on the disk. This search looks for fsutil.exe deleting the USN journal. +action.notable.param.rule_title = USN Journal Deletion +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -11298,6 +13484,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Uncommon Processes On Endpoint - Rule action.correlationsearch.annotations = {"analytic_story": ["Windows Privilege Escalation", "Unusual Processes"], "cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1204.002"], "nist": ["ID.AM", "PR.DS"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for applications on the endpoint that you have marked as uncommon. +action.notable.param.rule_title = Uncommon Processes On Endpoint +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -11332,6 +13524,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Unified Messaging Service Spawning a Process - Rule action.correlationsearch.annotations = {"analytic_story": ["HAFNIUM Group"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1190"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This detection identifies Microsoft Exchange Server's Unified Messaging services, umworkerprocess.exe and umservice.exe, spawning a child process, indicating possible exploitation of CVE-2021-26857 vulnerability. The query filters out werfault.exe and wermgr.exe mostly due to potential false positives, however, if there is an excessive amount of "wermgr.exe" or "WerFault.exe" failures, it may be due to the active exploitation. During triage, identify any additional suspicious parallel processes. Identify any recent out of place file modifications. Review Exchange logs following Microsofts guide. To contain, perform egress filtering or restrict public access to Exchange. In final, patch the vulnerablity and monitor. +action.notable.param.rule_title = Unified Messaging Service Spawning a Process +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -11366,6 +13564,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Unload Sysmon Filter Driver - Rule action.correlationsearch.annotations = {"analytic_story": ["Disabling Security Tools"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1562.001"], "nist": ["DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = Attackers often disable security tools to avoid detection. This search looks for the usage of process `fltMC.exe` to unload a Sysmon Driver that will stop sysmon from collecting the data. +action.notable.param.rule_title = Unload Sysmon Filter Driver +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -11394,7 +13598,7 @@ action.escu.product = ["Splunk Enterprise", "Splunk Enterprise Security", "Splun action.escu.providing_technologies = [] action.escu.analytic_story = ["Credential Dumping"] cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m +dispatch.earliest_time = -40m@m dispatch.latest_time = -10m@m action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Unsigned Image Loaded by LSASS - Rule @@ -11434,6 +13638,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Unsuccessful Netbackup backups - Rule action.correlationsearch.annotations = {"analytic_story": ["Monitor Backup Solution"], "cis20": ["CIS 10"], "nist": ["PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search gives you the hosts where a backup was attempted and then failed. +action.notable.param.rule_title = Unsuccessful Netbackup backups +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -11468,6 +13677,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Unusually Long Command Line - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious Command-Line Executions", "Unusual Processes", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Ransomware"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = Command lines that are extremely long may be indicative of malicious activity on your hosts. +action.notable.param.rule_title = Unusually Long Command Line +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -11502,6 +13717,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Unusually Long Command Line - MLTK - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious Command-Line Executions", "Unusual Processes", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Ransomware"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = Command lines that are extremely long may be indicative of malicious activity on your hosts. This search leverages the Machine Learning Toolkit (MLTK) to help identify command lines with lengths that are unusual for a given user. +action.notable.param.rule_title = Unusually Long Command Line - MLTK +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -11536,6 +13757,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Unusually Long Content-Type Length - Rule action.correlationsearch.annotations = {"analytic_story": ["Apache Struts Vulnerability"], "cis20": ["CIS 3", "CIS 4", "CIS 18", "CIS 12"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "RS.MI", "PR.PT", "PR.IP", "DE.AE", "PR.MA", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search looks for unusually long strings in the Content-Type http header that the client sends the server. +action.notable.param.rule_title = Unusually Long Content-Type Length +action.notable.param.security_domain = network +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -11570,6 +13796,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - W3WP Spawning Shell - Rule action.correlationsearch.annotations = {"analytic_story": ["HAFNIUM Group"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1505.003"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This query identifies a shell, PowerShell.exe or Cmd.exe, spawning from W3WP.exe, or IIS. In addition to IIS logs, this behavior with an EDR product will capture potential webshell activity, similar to the HAFNIUM Group abusing CVEs, on publicly available Exchange mail servers. During triage, review the parent process and child process of the shell being spawned. Review the command-line arguments and any file modifications that may occur. Identify additional parallel process, child processes, that may highlight further commands executed. After triaging, work to contain the threat and patch the system that is vulnerable. +action.notable.param.rule_title = W3WP Spawning Shell +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -11604,6 +13836,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - WBAdmin Delete System Backups - Rule action.correlationsearch.annotations = {"analytic_story": ["Ryuk Ransomware", "Ransomware"], "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1490"], "nist": ["PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for flags passed to wbadmin.exe (Windows Backup Administrator Tool) that delete backup files. This is typically used by ransomware to prevent recovery. +action.notable.param.rule_title = WBAdmin Delete System Backups +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -11638,6 +13876,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - WMI Permanent Event Subscription - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious WMI Use"], "cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search looks for the creation of WMI permanent event subscriptions. +action.notable.param.rule_title = WMI Permanent Event Subscription +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -11672,6 +13916,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - WMI Permanent Event Subscription - Sysmon - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious WMI Use"], "cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1546.003"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search looks for the creation of WMI permanent event subscriptions. +action.notable.param.rule_title = WMI Permanent Event Subscription - Sysmon +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -11706,6 +13956,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - WMI Temporary Event Subscription - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious WMI Use"], "cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search looks for the creation of WMI temporary event subscriptions. +action.notable.param.rule_title = WMI Temporary Event Subscription +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -11740,6 +13995,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Web Fraud - Account Harvesting - Rule action.correlationsearch.annotations = {"analytic_story": ["Web Fraud Detection"], "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1136"], "nist": ["DE.CM", "DE.DP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search is used to identify the creation of multiple user accounts using the same email domain name. +action.notable.param.rule_title = Web Fraud - Account Harvesting +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -11774,6 +14035,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Web Fraud - Anomalous User Clickspeed - Rule action.correlationsearch.annotations = {"analytic_story": ["Web Fraud Detection"], "cis20": ["CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078"], "nist": ["DE.AE", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search is used to examine web sessions to identify those where the clicks are occurring too quickly for a human or are occurring with a near-perfect cadence (high periodicity or low standard deviation), resembling a script driven session. +action.notable.param.rule_title = Web Fraud - Anomalous User Clickspeed +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -11808,6 +14074,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Web Fraud - Password Sharing Across Accounts - Rule action.correlationsearch.annotations = {"analytic_story": ["Web Fraud Detection"], "cis20": ["CIS 16"], "nist": ["DE.DP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search is used to identify user accounts that share a common password. +action.notable.param.rule_title = Web Fraud - Password Sharing Across Accounts +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -11842,6 +14114,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Web Servers Executing Suspicious Processes - Rule action.correlationsearch.annotations = {"analytic_story": ["Apache Struts Vulnerability"], "cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1082"], "nist": ["PR.IP"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search looks for suspicious processes on all systems labeled as web servers. +action.notable.param.rule_title = Web Servers Executing Suspicious Processes +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -11868,14 +14146,20 @@ action.escu.full_search_name = ESCU - Windows AdFind Exe - Rule action.escu.search_type = detection action.escu.product = ["Splunk Enterprise", "Splunk Enterprise Security", "Splunk Cloud"] action.escu.providing_technologies = [] -action.escu.analytic_story = ["NOBELIUM Group"] +action.escu.analytic_story = ["NOBELIUM Group", "Domain Trust Discovery"] cron_schedule = 0 * * * * dispatch.earliest_time = -70m@m dispatch.latest_time = -10m@m action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Windows AdFind Exe - Rule -action.correlationsearch.annotations = {"analytic_story": ["NOBELIUM Group"], "cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1018"], "nist": ["PR.PT", "DE.CM"]} +action.correlationsearch.annotations = {"analytic_story": ["NOBELIUM Group", "Domain Trust Discovery"], "cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1018"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for the execution of `adfind.exe` with command-line arguments that it uses by default. Specifically the filter or search functions. It also considers the arguments necessary like objectcategory, see readme for more details: https://www.joeware.net/freetools/tools/adfind/usage.htm. This has been seen used before by Wizard Spider, FIN6 and actors whom also launched SUNBURST. AdFind.exe is usually used a recon tool to enumare a domain controller. +action.notable.param.rule_title = Windows AdFind Exe +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -11910,6 +14194,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Windows DisableAntiSpyware Registry - Rule action.correlationsearch.annotations = {"analytic_story": ["Ryuk Ransomware", "Windows Defense Evasion Tactics"], "cis20": ["CIS 8"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1562.001"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The search looks for the Registry Key DisableAntiSpyware set to disable. This is consistent with Ryuk infections across a fleet of endpoints. This particular behavior is typically executed when an ransomware actor gains access to an endpoint and beings to perform execution. Usually, a batch (.bat) will be executed and multiple registry and scheduled task modifications will occur. During triage, review parallel processes and identify any further file modifications. Endpoint should be isolated. +action.notable.param.rule_title = Windows DisableAntiSpyware Registry +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -11944,6 +14234,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Windows Event Log Cleared - Rule action.correlationsearch.annotations = {"analytic_story": ["Windows Log Manipulation", "Ransomware", "Clop Ransomware"], "cis20": ["CIS 3", "CIS 5", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070.001"], "nist": ["DE.DP", "PR.IP", "PR.AC", "PR.AT", "DE.AE"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search looks for Windows events that indicate one of the Windows event logs has been purged. +action.notable.param.rule_title = Windows Event Log Cleared +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -11978,6 +14274,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Windows Security Account Manager Stopped - Rule action.correlationsearch.annotations = {"analytic_story": ["Ryuk Ransomware"], "cis20": ["CIS 8"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1489"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = The search looks for a Windows Security Account Manager (SAM) was stopped via command-line. This is consistent with Ryuk infections across a fleet of endpoints. +action.notable.param.rule_title = Windows Security Account Manager Stopped +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -12012,6 +14313,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Windows connhost exe started forcefully - Rule action.correlationsearch.annotations = {"analytic_story": ["Ryuk Ransomware"], "cis20": ["CIS 8"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1059.003"], "nist": ["PR.PT", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The search looks for the Console Window Host process (connhost.exe) executed using the force flag -ForceV1. This is not regular behavior in the Windows OS and is often seen executed by the Ryuk Ransomware. DEPRECATED This event is actually seen in the windows 10 client of attack_range_local. After further testing we realized this is not specific to Ryuk. +action.notable.param.rule_title = Windows connhost exe started forcefully +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -12046,6 +14353,12 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Windows hosts file modification - Rule action.correlationsearch.annotations = {"analytic_story": ["Host Redirection"], "cis20": ["CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "nist": ["PR.IP", "PR.PT", "PR.AC", "DE.AE", "DE.CM"]} schedule_window = auto +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The search looks for modifications to the hosts file on all Windows endpoints across your environment. +action.notable.param.rule_title = Windows hosts file modification +action.notable.param.security_domain = endpoint +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -12080,6 +14393,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - aws detect attach to role policy - Rule action.correlationsearch.annotations = {"analytic_story": ["AWS Cross Account Activity"], "kill_chain_phases": ["Lateral Movement"], "mitre_attack": ["T1078"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search provides detection of an user attaching itself to a different role trust policy. This can be used for lateral movement and escalation of privileges. +action.notable.param.rule_title = aws detect attach to role policy +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -12114,6 +14432,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - aws detect permanent key creation - Rule action.correlationsearch.annotations = {"analytic_story": ["AWS Cross Account Activity"], "kill_chain_phases": ["Lateral Movement"], "mitre_attack": ["T1078"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search provides detection of accounts creating permanent keys. Permanent keys are not created by default and they are only needed for programmatic calls. Creation of Permanent key is an important event to monitor. +action.notable.param.rule_title = aws detect permanent key creation +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -12148,6 +14471,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - aws detect role creation - Rule action.correlationsearch.annotations = {"analytic_story": ["AWS Cross Account Activity"], "kill_chain_phases": ["Lateral Movement"], "mitre_attack": ["T1078"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search provides detection of role creation by IAM users. Role creation is an event by itself if user is creating a new role with trust policies different than the available in AWS and it can be used for lateral movement and escalation of privileges. +action.notable.param.rule_title = aws detect role creation +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -12182,6 +14510,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - aws detect sts assume role abuse - Rule action.correlationsearch.annotations = {"analytic_story": ["AWS Cross Account Activity"], "kill_chain_phases": ["Lateral Movement"], "mitre_attack": ["T1078"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search provides detection of suspicious use of sts:AssumeRole. These tokens can be created on the go and used by attackers to move laterally and escalate privileges. +action.notable.param.rule_title = aws detect sts assume role abuse +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -12216,6 +14549,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - aws detect sts get session token abuse - Rule action.correlationsearch.annotations = {"analytic_story": ["AWS Cross Account Activity"], "kill_chain_phases": ["Lateral Movement"], "mitre_attack": ["T1550"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search provides detection of suspicious use of sts:GetSessionToken. These tokens can be created on the go and used by attackers to move laterally and escalate privileges. +action.notable.param.rule_title = aws detect sts get session token abuse +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 @@ -12250,6 +14588,11 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - gcp detect oauth token abuse - Rule action.correlationsearch.annotations = {"analytic_story": ["GCP Cross Account Activity"], "kill_chain_phases": ["Lateral Movement"], "mitre_attack": ["T1078"]} schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search provides detection of possible GCP Oauth token abuse. GCP Oauth token without time limit can be exfiltrated and reused for keeping access sessions alive without further control of authentication, allowing attackers to access and move laterally. +action.notable.param.rule_title = gcp detect oauth token abuse +action.notable.param.security_domain = threat +action.notable.param.severity = high alert.digest_mode = 1 disabled = true enableSched = 1 diff --git a/dist/escu/default/transforms.conf b/dist/escu/default/transforms.conf index 28ead2c03a..eb0e2b6a83 100644 --- a/dist/escu/default/transforms.conf +++ b/dist/escu/default/transforms.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security_content -# On Date: 2021-03-29T18:33:55 UTC +# On Date: 2021-04-14T19:13:35 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/dist/escu/default/use_case_library.conf b/dist/escu/default/use_case_library.conf index 18dbb595b6..e2b44f2883 100644 --- a/dist/escu/default/use_case_library.conf +++ b/dist/escu/default/use_case_library.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security_content -# On Date: 2021-03-29T18:33:55 UTC +# On Date: 2021-04-14T19:13:35 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -14,7 +14,7 @@ version = 1 references = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] maintainers = [{"company": "Splunk", "email": "-", "name": "David Dorsey"}] spec_version = 3 -searches = ["ESCU - aws detect sts get session token abuse - Rule", "ESCU - aws detect attach to role policy - Rule", "ESCU - aws detect role creation - Rule", "ESCU - aws detect permanent key creation - Rule", "ESCU - aws detect sts assume role abuse - Rule", "ESCU - Get Notable History - Response Task", "ESCU - AWS Investigate User Activities By AccessKeyId - Response Task"] +searches = ["ESCU - aws detect sts assume role abuse - Rule", "ESCU - aws detect sts get session token abuse - Rule", "ESCU - aws detect role creation - Rule", "ESCU - aws detect attach to role policy - Rule", "ESCU - aws detect permanent key creation - Rule", "ESCU - AWS Investigate User Activities By AccessKeyId - Response Task", "ESCU - Get Notable History - Response Task"] description = Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity. narrative = Amazon Web Services (AWS) admins manage access to AWS resources and services across the enterprise using AWS's Identity and Access Management (IAM) functionality. IAM provides the ability to create and manage AWS users, groups, and roles-each with their own unique set of privileges and defined access to specific resources (such as EC2 instances, the AWS Management Console, API, or the command-line interface). Unlike conventional (human) users, IAM roles are assumable by anyone in the organization. They provide users with dynamically created temporary security credentials that expire within a set time period.\ Herein lies the rub. In between the time between when the temporary credentials are issued and when they expire is a period of opportunity, where a user could leverage the temporary credentials to wreak havoc-spin up or remove instances, create new users, elevate privileges, and other malicious activities-throughout the environment.\ @@ -27,7 +27,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = [{"company": "Splunk", "email": "-", "name": "David Dorsey"}] spec_version = 3 -searches = ["ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - Get Notable History - Response Task", "ESCU - Investigate AWS activities via region name - Response Task", "ESCU - Get EC2 Launch Details - Response Task", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Get EC2 Instance Details by instanceId - Response Task"] +searches = ["ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Investigate AWS activities via region name - Response Task", "ESCU - Get EC2 Launch Details - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get EC2 Instance Details by instanceId - Response Task"] description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS). It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -41,7 +41,7 @@ version = 1 references = ["https://rhinosecuritylabs.com/aws/aws-privilege-escalation-methods-mitigation/", "https://www.cyberark.com/resources/threat-research-blog/the-cloud-shadow-admin-threat-10-permissions-to-protect", "https://labs.bishopfox.com/tech-blog/privilege-escalation-in-aws"] maintainers = [{"company": "Splunk", "email": "-", "name": "Bhavin Patel"}] spec_version = 3 -searches = ["ESCU - AWS CreateAccessKey - Rule", "ESCU - AWS SetDefaultPolicyVersion - Rule", "ESCU - AWS CreateLoginProfile - Rule", "ESCU - AWS Create Policy Version to allow all resources - Rule", "ESCU - AWS UpdateLoginProfile - Rule"] +searches = ["ESCU - AWS UpdateLoginProfile - Rule", "ESCU - AWS Create Policy Version to allow all resources - Rule", "ESCU - AWS CreateAccessKey - Rule", "ESCU - AWS CreateLoginProfile - Rule", "ESCU - AWS SetDefaultPolicyVersion - Rule"] description = This analytic story contains detections that query your AWS Cloudtrail for activities related to privilege escalation. narrative = Amazon Web Services provides a neat feature called Identity and Access Management (IAM) that enables organizations to manage various AWS services and resources in a secure way. All IAM users have roles, groups and policies associated with them which governs and sets permissions to allow a user to access specific restrictions.\ However, if these IAM policies are misconfigured and have specific combinations of weak permissions; it can allow attackers to escalate their privileges and further compromise the organization. Rhino Security Labs have published comprehensive blogs detailing various AWS Escalation methods. By using this as an inspiration, Splunk’s research team wants to highlight how these attack vectors look in AWS Cloudtrail logs and provide you with detection queries to uncover these potentially malicious events via this Analytic Story. \ @@ -53,7 +53,7 @@ version = 2 references = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] maintainers = [{"company": "Splunk", "email": "-", "name": "Bhavin Patel"}] spec_version = 3 -searches = ["ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Get DNS Server History for a host - Response Task", "ESCU - AWS Network Interface details via resourceId - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Process Responsible For The DNS Traffic - Response Task", "ESCU - Get Process Info - Response Task", "ESCU - Get DNS traffic ratio - Response Task", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Get Process Information For Port Activity - Response Task", "ESCU - AWS Network ACL Details from ID - Response Task", "ESCU - Get All AWS Activity From IP Address - Response Task"] +searches = ["ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Get Process Info - Response Task", "ESCU - AWS Network Interface details via resourceId - Response Task", "ESCU - Get DNS Server History for a host - Response Task", "ESCU - Get Process Information For Port Activity - Response Task", "ESCU - Get All AWS Activity From IP Address - Response Task", "ESCU - Get DNS traffic ratio - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Process Responsible For The DNS Traffic - Response Task", "ESCU - AWS Network ACL Details from ID - Response Task"] description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and operational/risk auditing of your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Management Console, AWS Command Line Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable to attacks. This analytic story contains detection searches that leverage CloudTrail logs from AWS to check for bad configurations and malicious activity in your AWS network access controls. @@ -64,7 +64,7 @@ version = 1 references = ["https://aws.amazon.com/security-hub/features/"] maintainers = [{"company": "Splunk", "email": "-", "name": "Bhavin Patel"}] spec_version = 3 -searches = ["ESCU - Detect Spike in AWS Security Hub Alerts for User - Rule", "ESCU - Detect Spike in AWS Security Hub Alerts for EC2 Instance - Rule", "ESCU - Get EC2 Launch Details - Response Task", "ESCU - Get EC2 Instance Details by instanceId - Response Task", "ESCU - AWS Investigate User Activities By ARN - Response Task"] +searches = ["ESCU - Detect Spike in AWS Security Hub Alerts for EC2 Instance - Rule", "ESCU - Detect Spike in AWS Security Hub Alerts for User - Rule", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Get EC2 Instance Details by instanceId - Response Task", "ESCU - Get EC2 Launch Details - Response Task"] description = This story is focused around detecting Security Hub alerts generated from AWS narrative = AWS Security Hub collects and consolidates findings from AWS security services enabled in your environment, such as intrusion detection findings from Amazon GuardDuty, vulnerability scans from Amazon Inspector, S3 bucket policy findings from Amazon Macie, publicly accessible and cross-account resources from IAM Access Analyzer, and resources lacking WAF coverage from AWS Firewall Manager. @@ -75,7 +75,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = [{"company": "Splunk", "email": "-", "name": "David Dorsey"}] spec_version = 3 -searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - Get All AWS Activity From Country - Response Task", "ESCU - Get All AWS Activity From Region - Response Task", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Get All AWS Activity From City - Response Task", "ESCU - Get All AWS Activity From IP Address - Response Task", "ESCU - AWS Investigate Security Hub alerts by dest - Response Task"] +searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Get All AWS Activity From City - Response Task", "ESCU - AWS Investigate Security Hub alerts by dest - Response Task", "ESCU - Get All AWS Activity From IP Address - Response Task", "ESCU - Get All AWS Activity From Country - Response Task", "ESCU - Get All AWS Activity From Region - Response Task"] description = Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. narrative = Because most enterprise AWS activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where it is impossible to add specific IPs to an allow list because they vary. \ This Analytic Story was designed to provide you with flexibility in the precision you employ in specifying legitimate geographic regions. It can be as specific as an IP address or a city, or as broad as a region (think state) or an entire country. By determining how precise you want your geographical locations to be and monitoring for new locations that haven't previously accessed your environment, you can detect adversaries as they begin to probe your environment. Since there are legitimate reasons for activities from unfamiliar locations, this is not a standalone indicator. Nevertheless, location can be a relevant piece of information that you may wish to investigate further. @@ -87,7 +87,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] maintainers = [{"company": "Splunk", "email": "-", "name": "Bhavin Patel"}] spec_version = 3 -searches = ["ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Investigate AWS User Activities by user field - Response Task", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - Detect new API calls from user roles - Rule", "ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - AWS Excessive Security Scanning - Rule", "ESCU - Investigate AWS User Activities by user field - Response Task", "ESCU - Get Notable History - Response Task"] description = Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. narrative = It seems obvious that it is critical to monitor and control the users who have access to your cloud infrastructure. Nevertheless, it's all too common for enterprises to lose track of ad-hoc accounts, leaving their servers vulnerable to attack. In fact, this was the very oversight that led to Tesla's cryptojacking attack in February, 2018.\ In addition to compromising the security of your data, when bad actors leverage your compute resources, it can incur monumental costs, since you will be billed for any new EC2 instances and increased bandwidth usage. \ @@ -101,7 +101,7 @@ version = 1 references = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] maintainers = [{"company": "Splunk", "email": "-", "name": "Rico Valdez"}] spec_version = 3 -searches = ["ESCU - Suspicious Java Classes - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Investigate Suspicious Strings in HTTP Header - Response Task", "ESCU - Investigate Web POSTs From src - Response Task", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Suspicious Java Classes - Rule", "ESCU - Investigate Web POSTs From src - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Investigate Suspicious Strings in HTTP Header - Response Task"] description = Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. narrative = In March of 2017, a remote code-execution vulnerability in the Jakarta Multipart parser in Apache Struts, a widely used open-source framework for creating Java web applications, was disclosed and assigned to CVE-2017-5638. About two months later, hackers exploited the flaw to carry out the world's 5th largest data breach. The target, credit giant Equifax, told investigators that it had become aware of the vulnerability two months before the attack. \ The exploit involved manipulating the `Content-Type HTTP` header to execute commands embedded in the header.\ @@ -125,10 +125,21 @@ version = 1 references = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] maintainers = [{"company": "Splunk", "email": "-", "name": "Bhavin Patel"}] spec_version = 3 -searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule", "ESCU - Get Notable History - Response Task", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address - Response Task"] +searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address - Response Task", "ESCU - Get Notable History - Response Task"] description = Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further. narrative = This Analytic Story is designed to help you develop a better understanding of what authorized and unauthorized devices are part of your enterprise. This story can help you better categorize and classify assets, providing critical business context and awareness of their assets during an incident. Information derived from this Analytic Story can be used to better inform and support other analytic stories. For successful detection, you will need to leverage the Assets and Identity Framework from Enterprise Security to populate your known assets. +[analytic_story://BITS Jobs] +category = Adversary Tactics +last_updated = 2021-03-26 +version = 1 +references = ["https://attack.mitre.org/techniques/T1197/", "https://docs.microsoft.com/en-us/windows/win32/bits/bitsadmin-tool"] +maintainers = [{"company": "Splunk", "email": "-", "name": "Michael Haag"}] +spec_version = 3 +searches = ["ESCU - PowerShell Start-BitsTransfer - Rule", "ESCU - BITSAdmin Download File - Rule", "ESCU - BITS Job Persistence - Rule"] +description = Adversaries may abuse BITS jobs to persistently execute or clean up after malicious payloads. +narrative = Windows Background Intelligent Transfer Service (BITS) is a low-bandwidth, asynchronous file transfer mechanism exposed through Component Object Model (COM). BITS is commonly used by updaters, messengers, and other applications preferred to operate in the background (using available idle bandwidth) without interrupting other networked applications. File transfer tasks are implemented as BITS jobs, which contain a queue of one or more file operations. The interface to create and manage BITS jobs is accessible through PowerShell and the BITSAdmin tool. Adversaries may abuse BITS to download, execute, and even clean up after running malicious code. BITS tasks are self-contained in the BITS job database, without new files or registry modifications, and often permitted by host firewalls. BITS enabled execution may also enable persistence by creating long-standing jobs (the default maximum lifetime is 90 days and extendable) or invoking an arbitrary program when a job completes or errors (including after system reboots). + [analytic_story://Baron Samedit CVE-2021-3156] category = Adversary Tactics last_updated = 2021-01-27 @@ -136,7 +147,7 @@ version = 1 references = ["https://blog.qualys.com/vulnerabilities-research/2021/01/26/cve-2021-3156-heap-based-buffer-overflow-in-sudo-baron-samedit"] maintainers = [{"company": "Splunk", "email": "-", "name": "Shannon Davis"}] spec_version = 3 -searches = ["ESCU - Detect Baron Samedit CVE-2021-3156 Segfault - Rule", "ESCU - Detect Baron Samedit CVE-2021-3156 - Rule", "ESCU - Detect Baron Samedit CVE-2021-3156 via OSQuery - Rule"] +searches = ["ESCU - Detect Baron Samedit CVE-2021-3156 - Rule", "ESCU - Detect Baron Samedit CVE-2021-3156 via OSQuery - Rule", "ESCU - Detect Baron Samedit CVE-2021-3156 Segfault - Rule"] description = Uncover activity consistent with CVE-2021-3156. Discovered by the Qualys Research Team, this vulnerability has been found to affect sudo across multiple Linux distributions (Ubuntu 20.04 and prior, Debian 10 and prior, Fedora 33 and prior). As this vulnerability was committed to code in July 2011, there will be many distributions affected. Successful exploitation of this vulnerability allows any unprivileged user to gain root privileges on the vulnerable host. narrative = A non-privledged user is able to execute the sudoedit command to trigger a buffer overflow. After the successful buffer overflow, they are then able to gain root privileges on the affected host. The conditions needed to be run are a trailing "\" along with shell and edit flags. Monitoring the /var/log directory on Linux hosts using the Splunk Universal Forwarder will allow you to pick up this behavior when using the provided detection. @@ -147,7 +158,7 @@ version = 1 references = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] maintainers = [{"company": "Splunk", "email": "-", "name": "David Dorsey"}] spec_version = 3 -searches = ["ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Get Emails From Specific Sender - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Email Info - Response Task", "ESCU - Get Process Responsible For The DNS Traffic - Response Task"] +searches = ["ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Get Notable History - Response Task", "ESCU - Get Emails From Specific Sender - Response Task", "ESCU - Get Email Info - Response Task", "ESCU - Get Process Responsible For The DNS Traffic - Response Task"] description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. narrative = While you can educate your users and customers about the risks and threats posed by typosquatting, phishing, and corporate espionage, human error is a persistent fact of life. Of course, your adversaries are all too aware of this reality and will happily leverage it for nefarious purposes whenever possible3phishing with lookalike addresses, embedding faux command-and-control domains in malware, and hosting malicious content on domains that closely mimic your corporate servers. This is where brand monitoring comes in.\ You can use our adaptation of `DNSTwist`, together with the support searches in this Analytic Story, to generate permutations of specified brands and external domains. Splunk can monitor email, DNS requests, and web traffic for these permutations and provide you with early warnings and situational awareness--powerful elements of an effective defense.\ @@ -160,7 +171,7 @@ version = 1 references = ["https://www.hhs.gov/sites/default/files/analyst-note-cl0p-tlp-white.pdf", "https://securityaffairs.co/wordpress/115250/data-breach/qualys-clop-ransomware.html", "https://www.darkreading.com/attacks-breaches/qualys-is-the-latest-victim-of-accellion-data-breach/d/d-id/1340323"] maintainers = [{"company": "Teoderick Contreras, Splunk", "email": "-", "name": "Rod Soto"}] spec_version = 3 -searches = ["ESCU - High File Deletion Frequency - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Create Service In Suspicious File Path - Rule", "ESCU - Process Deleting Its Process File Path - Rule", "ESCU - Resize ShadowStorage volume - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Clop Ransomware Known Service Name - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Clop Common Exec Parameter - Rule", "ESCU - Ransomware Notes bulk creation - Rule", "ESCU - High Process Termination Frequency - Rule", "ESCU - Common Ransomware Extensions - Rule"] +searches = ["ESCU - High File Deletion Frequency - Rule", "ESCU - Process Deleting Its Process File Path - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - High Process Termination Frequency - Rule", "ESCU - Create Service In Suspicious File Path - Rule", "ESCU - Resize ShadowStorage volume - Rule", "ESCU - Ransomware Notes bulk creation - Rule", "ESCU - Clop Ransomware Known Service Name - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Clop Common Exec Parameter - Rule"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the Clop ransomware, including looking for file writes associated with Clope, encrypting network shares, deleting and resizing shadow volume storage, registry key modification, deleting of security logs, and more. narrative = Clop ransomware campaigns targeting healthcare and other vertical sectors, involve the use of ransomware payloads along with exfiltration of data per HHS bulletin. Malicious actors demand payment for ransome of data and threaten deletion and exposure of exfiltrated data. @@ -171,7 +182,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = [{"company": "Splunk", "email": "-", "name": "David Dorsey"}] spec_version = 3 -searches = ["ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Abnormally High Number Of Cloud Instances Launched - Rule", "ESCU - Cloud Compute Instance Created In Previously Unused Region - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Get Notable History - Response Task", "ESCU - AWS Investigate Security Hub alerts by dest - Response Task", "ESCU - Investigate AWS activities via region name - Response Task", "ESCU - Get EC2 Launch Details - Response Task", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Get EC2 Instance Details by instanceId - Response Task"] +searches = ["ESCU - Abnormally High Number Of Cloud Instances Launched - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created In Previously Unused Region - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Investigate AWS activities via region name - Response Task", "ESCU - Get EC2 Launch Details - Response Task", "ESCU - AWS Investigate Security Hub alerts by dest - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get EC2 Instance Details by instanceId - Response Task"] description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Azure. It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -185,7 +196,7 @@ version = 1 references = ["https://www.cyberark.com/resources/threat-research-blog/golden-saml-newly-discovered-attack-technique-forges-authentication-to-cloud-apps", "https://www.fireeye.com/content/dam/fireeye-www/blog/pdfs/wp-m-unc2452-2021-000343-01.pdf", "https://us-cert.cisa.gov/ncas/alerts/aa21-008a"] maintainers = [{"company": "Splunk", "email": "-", "name": "Rod Soto"}] spec_version = 3 -searches = ["ESCU - O365 Excessive SSO logon errors - Rule", "ESCU - O365 Added Service Principal - Rule", "ESCU - O365 Add App Role Assignment Grant User - Rule", "ESCU - O365 New Federated Domain Added - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - AWS SAML Access by Provider User and Principal - Rule", "ESCU - AWS SAML Update identity provider - Rule", "ESCU - Detect Mimikatz Via PowerShell And EventCode 4703 - Rule", "ESCU - Certutil exe certificate extraction - Rule", "ESCU - Detect Rare Executables - Rule"] +searches = ["ESCU - Detect Mimikatz Via PowerShell And EventCode 4703 - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - AWS SAML Update identity provider - Rule", "ESCU - Certutil exe certificate extraction - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - O365 Add App Role Assignment Grant User - Rule", "ESCU - O365 Excessive SSO logon errors - Rule", "ESCU - O365 Added Service Principal - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - O365 New Federated Domain Added - Rule", "ESCU - AWS SAML Access by Provider User and Principal - Rule"] description = This analytical story addresses events that indicate abuse of cloud federated credentials. These credentials are usually extracted from endpoint desktop or servers specially those servers that provide federation services such as Windows Active Directory Federation Services. Identity Federation relies on objects such as Oauth2 tokens, cookies or SAML assertions in order to provide seamless access between cloud and perimeter environments. If these objects are either hijacked or forged then attackers will be able to pivot into victim's cloud environements. narrative = This story is composed of detection searches based on endpoint that addresses the use of Mimikatz, Escalation of Privileges and Abnormal processes that may indicate the extraction of Federated directory objects such as passwords, Oauth2 tokens, certificates and keys. Cloud environment (AWS, Azure) related events are also addressed in specific cloud environment detection searches. @@ -196,7 +207,7 @@ version = 1 references = ["https://www.cobaltstrike.com/", "https://www.infocyte.com/blog/2020/09/02/cobalt-strike-the-new-favorite-among-thieves/", "https://bluescreenofjeff.com/2017-01-24-how-to-write-malleable-c2-profiles-for-cobalt-strike/", "https://blog.talosintelligence.com/2020/09/coverage-strikes-back-cobalt-strike-paper.html", "https://www.fireeye.com/blog/threat-research/2020/12/unauthorized-access-of-fireeye-red-team-tools.html", "https://github.com/MichaelKoczwara/Awesome-CobaltStrike-Defence", "https://github.com/zer0yu/Awesome-CobaltStrike"] maintainers = [{"company": "Splunk", "email": "-", "name": "Michael Haag"}] spec_version = 3 -searches = ["ESCU - Suspicious Rundll32 StartW - Rule", "ESCU - Suspicious microsoft workflow compiler rename - Rule", "ESCU - Suspicious Rundll32 no Command Line Arguments - Rule", "ESCU - Suspicious msbuild path - Rule", "ESCU - Cobalt Strike Named Pipes - Rule", "ESCU - Suspicious GPUpdate no Command Line Arguments - Rule", "ESCU - Suspicious DLLHost no Command Line Arguments - Rule", "ESCU - Suspicious MSBuild Rename - Rule", "ESCU - Suspicious SearchProtocolHost no Command Line Arguments - Rule", "ESCU - Detect Regsvr32 Application Control Bypass - Rule"] +searches = ["ESCU - Suspicious DLLHost no Command Line Arguments - Rule", "ESCU - Suspicious msbuild path - Rule", "ESCU - Suspicious MSBuild Rename - Rule", "ESCU - Suspicious Rundll32 no Command Line Arguments - Rule", "ESCU - Suspicious SearchProtocolHost no Command Line Arguments - Rule", "ESCU - Cobalt Strike Named Pipes - Rule", "ESCU - Suspicious GPUpdate no Command Line Arguments - Rule", "ESCU - Suspicious Rundll32 StartW - Rule", "ESCU - Suspicious microsoft workflow compiler rename - Rule", "ESCU - Detect Regsvr32 Application Control Bypass - Rule"] description = Cobalt Strike is threat emulation software. Red teams and penetration testers use Cobalt Strike to demonstrate the risk of a breach and evaluate mature security programs. Most recently, Cobalt Strike has become the choice tool by threat groups due to its ease of use and extensibility. narrative = This Analytic Story supports you to detect Tactics, Techniques and Procedures (TTPs) from Cobalt Strike. Cobalt Strike has many ways to be enhanced by using aggressor scripts, malleable C2 profiles, default attack packages, and much more. For endpoint behavior, Cobalt Strike is most commonly identified via named pipes, spawn to processes, and DLL function names. Many additional variables are provided for in memory operation of the beacon implant. On the network, depending on the malleable C2 profile used, it is near infinite in the amount of ways to conceal the C2 traffic with Cobalt Strike. Not every query may be specific to Cobalt Strike the tool, but the methodologies and techniques used by it.\ Splunk Threat Research reviewed all publicly available instances of Malleabe C2 Profiles and generated a list of the most commonly used spawnto and pipenames.\ @@ -216,7 +227,7 @@ version = 1 references = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] maintainers = [{"company": "Splunk", "email": "-", "name": "Jose Hernandez"}] spec_version = 3 -searches = ["ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Investigate Network Traffic From src ip - Response Task", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Get Notable History - Response Task", "ESCU - Investigate Network Traffic From src ip - Response Task"] description = Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. narrative = Conventional wisdom holds that Apple's MacOS operating system is significantly less vulnerable to attack than Windows machines. While that point is debatable, it is true that attacks against MacOS systems are much less common. However, this fact does not mean that Macs are impervious to breaches. To the contrary, research has shown that that Mac malware is increasing at an alarming rate. According to AV-test, in 2018, there were 86,865 new MacOS malware variants, up from 27,338 the year before—a 31% increase. In contrast, the independent research firm found that new Windows malware had increased from 65.17M to 76.86M during that same period, less than half the rate of growth. The bottom line is that while the numbers look a lot smaller than Windows, it's definitely time to take Mac security more seriously.\ This Analytic Story addresses the ColdRoot remote access trojan (RAT), which was uploaded to Github in 2016, but was still escaping detection by the first quarter of 2018, when a new, more feature-rich variant was discovered masquerading as an Apple audio driver. Among other capabilities, the Pascal-based ColdRoot can heist passwords from users' keychains and remotely control infected machines without detection. In the initial report of his findings, Patrick Wardle, Chief Research Officer for Digita Security, explained that the new ColdRoot RAT could start and kill processes on the breached system, spawn new remote-desktop sessions, take screen captures and assemble them into a live stream of the victim's desktop, and more.\ @@ -229,7 +240,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] maintainers = [{"company": "Splunk", "email": "-", "name": "Rico Valdez"}] spec_version = 3 -searches = ["ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Parent Process Info - Response Task"] description = Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. narrative = A common adversary goal is to identify and exfiltrate data of value from a target organization. This data may include email conversations and addresses, confidential company information, links to network design/infrastructure, important dates, and so on.\ Attacks are composed of three activities: identification, collection, and staging data for exfiltration. Identification typically involves scanning systems and observing user activity. Collection can involve the transfer of large amounts of data from various repositories. Staging/preparation includes moving data to a central location and compressing (and optionally encoding and/or encrypting) it. All of these activities provide opportunities for defenders to identify their presence. \ @@ -242,7 +253,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] maintainers = [{"company": "Splunk", "email": "-", "name": "Rico Valdez"}] spec_version = 3 -searches = ["ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Get DNS Server History for a host - Response Task", "ESCU - AWS Network Interface details via resourceId - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Process Responsible For The DNS Traffic - Response Task", "ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get DNS traffic ratio - Response Task", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Get Process Information For Port Activity - Response Task", "ESCU - AWS Network ACL Details from ID - Response Task", "ESCU - Get All AWS Activity From IP Address - Response Task"] +searches = ["ESCU - Excessive DNS Failures - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - TOR Traffic - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Get Process Info - Response Task", "ESCU - AWS Network Interface details via resourceId - Response Task", "ESCU - Get DNS Server History for a host - Response Task", "ESCU - Get Process Information For Port Activity - Response Task", "ESCU - Get All AWS Activity From IP Address - Response Task", "ESCU - Get DNS traffic ratio - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Process Responsible For The DNS Traffic - Response Task", "ESCU - AWS Network ACL Details from ID - Response Task", "ESCU - Get Parent Process Info - Response Task"] description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. narrative = Threat actors typically architect and implement an infrastructure to use in various ways during the course of their attack campaigns. In some cases, they leverage this infrastructure for scanning and performing reconnaissance activities. In others, they may use this infrastructure to launch actual attacks. One of the most important functions of this infrastructure is to establish servers that will communicate with implants on compromised endpoints. These servers establish a command and control channel that is used to proxy data between the compromised endpoint and the attacker. These channels relay commands from the attacker to the compromised endpoint and the output of those commands back to the attacker.\ Because this communication is so critical for an adversary, they often use techniques designed to hide the true nature of the communications. There are many different techniques used to establish and communicate over these channels. This Analytic Story provides searches that look for a variety of the techniques used for these channels, as well as indications that these channels are active, by examining logs associated with border control devices and network-access control lists. @@ -277,7 +288,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] maintainers = [{"company": "Splunk", "email": "-", "name": "Rico Valdez"}] spec_version = 3 -searches = ["ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Dump LSASS via procdump - Rule", "ESCU - Dump LSASS via procdump Rename - Rule", "ESCU - Ntdsutil Export NTDS - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Creation of lsass Dump with Taskmgr - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Investigate Pass the Ticket Attempts - Response Task", "ESCU - Investigate Previous Unseen User - Response Task", "ESCU - Investigate Pass the Hash Attempts - Response Task", "ESCU - Investigate Failed Logins for Multiple Destinations - Response Task"] +searches = ["ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Dump LSASS via procdump Rename - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Ntdsutil Export NTDS - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Creation of lsass Dump with Taskmgr - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Dump LSASS via procdump - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Investigate Pass the Hash Attempts - Response Task", "ESCU - Investigate Previous Unseen User - Response Task", "ESCU - Investigate Failed Logins for Multiple Destinations - Response Task", "ESCU - Investigate Pass the Ticket Attempts - Response Task"] description = Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. narrative = Credential dumping—gathering credentials from a target system, often hashed or encrypted—is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking it offline, on their own systems. The threat actors target a variety of sources to extract them, including the Security Accounts Manager (SAM), Local Security Authority (LSA), NTDS from Domain Controllers, or the Group Policy Preference (GPP) files.\ Once attackers obtain valid credentials, they use them to move throughout a target network with ease, discovering new systems and identifying assets of interest. Credentials obtained in this manner typically include those of privileged users, which may provide access to more sensitive information and system operations.\ @@ -290,7 +301,7 @@ version = 2 references = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] maintainers = [{"company": "Splunk", "email": "-", "name": "Rico Valdez"}] spec_version = 3 -searches = ["ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Scheduled Task Deleted Or Created via CMD - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Get Process File Activity - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Process Information For Port Activity - Response Task"] +searches = ["ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Scheduled Task Deleted Or Created via CMD - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Process Information For Port Activity - Response Task", "ESCU - Get Process File Activity - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Parent Process Info - Response Task"] description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. narrative = The frequency of nation-state cyber attacks has increased significantly over the last decade. Employing numerous tactics and techniques, these attacks continue to escalate in complexity. \ There is a wide range of motivations for these state-sponsored hacks, including stealing valuable corporate, military, or diplomatic dataѿall of which could confer advantages in various arenas. They may also target critical infrastructure. \ @@ -316,7 +327,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = [{"company": "Splunk", "email": "-", "name": "Bhavin Patel"}] spec_version = 3 -searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS record changed - Rule", "ESCU - Get DNS Server History for a host - Response Task", "ESCU - DNS Hijack Enrichment - Response Task"] +searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - DNS record changed - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Hijack Enrichment - Response Task", "ESCU - Get DNS Server History for a host - Response Task"] description = Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records. narrative = Dubbed the Achilles heel of the Internet (see https://www.f5.com/labs/articles/threat-intelligence/dns-is-still-the-achilles-heel-of-the-internet-25613), DNS plays a critical role in routing web traffic but is notoriously vulnerable to attack. One reason is its distributed nature. It relies on unstructured connections between millions of clients and servers over inherently insecure protocols.\ The gravity and extent of the importance of securing DNS from attacks is undeniable. The fallout of compromised DNS can be disastrous. Not only can hackers bring down an entire business, they can intercept confidential information, emails, and login credentials, as well. \ @@ -346,7 +357,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] maintainers = [{"company": "Splunk", "email": "-", "name": "Bhavin Patel"}] spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect USB device insertion - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Get Notable History - Response Task", "ESCU - Get DNS Server History for a host - Response Task", "ESCU - Get Process Responsible For The DNS Traffic - Response Task", "ESCU - Get Process Info - Response Task", "ESCU - Get DNS traffic ratio - Response Task"] +searches = ["ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get DNS Server History for a host - Response Task", "ESCU - Get DNS traffic ratio - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Process Responsible For The DNS Traffic - Response Task"] description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. narrative = Attackers can leverage a variety of resources to compromise or exfiltrate enterprise data. Common exfiltration techniques include remote-access channels via low-risk, high-payoff active-collections operations and close-access operations using insiders and removable media. While this Analytic Story is not a comprehensive listing of all the methods by which attackers can exfiltrate data, it provides a useful starting point. @@ -368,7 +379,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Technique/T1003", "https://github.com/SecuraBV/CVE-2020-1472", "https://www.secura.com/blog/zero-logon", "https://nvd.nist.gov/vuln/detail/CVE-2020-1472"] maintainers = [{"company": "Jose Hernandez, Stan Miskowicz, David Dorsey, Shannon Davis Splunk", "email": "-", "name": "Rod Soto"}] spec_version = 3 -searches = ["ESCU - Detect Zerologon via Zeek - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Detect Computer Changed with Anonymous Account - Rule", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Detect Computer Changed with Anonymous Account - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Detect Zerologon via Zeek - Rule", "ESCU - Get Notable History - Response Task"] description = Uncover activity related to the execution of Zerologon CVE-2020-11472, a technique wherein attackers target a Microsoft Windows Domain Controller to reset its computer account password. The result from this attack is attackers can now provide themselves high privileges and take over Domain Controller. The included searches in this Analytic Story are designed to identify attempts to reset Domain Controller Computer Account via exploit code remotely or via the use of tool Mimikatz as payload carrier. narrative = This attack is a privilege escalation technique, where attacker targets a Netlogon secure channel connection to a domain controller, using Netlogon Remote Protocol (MS-NRPC). This vulnerability exposes vulnerable Windows Domain Controllers to be targeted via unaunthenticated RPC calls which eventually reset Domain Contoller computer account ($) providing the attacker the opportunity to exfil domain controller credential secrets and assign themselve high privileges that can lead to domain controller and potentially complete network takeover. The detection searches in this Analytic Story use Windows Event viewer events and Sysmon events to detect attack execution, these searches monitor access to the Local Security Authority Subsystem Service (LSASS) process which is an indicator of the use of Mimikatz tool which has bee updated to carry this attack payload. @@ -379,10 +390,21 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] maintainers = [{"company": "Splunk", "email": "-", "name": "Rico Valdez"}] spec_version = 3 -searches = ["ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Parent Process Info - Response Task"] description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. narrative = Attackers employ a variety of tactics in order to avoid detection and operate without barriers. This often involves modifying the configuration of security tools to get around them or explicitly disabling them to prevent them from running. This Analytic Story includes searches that look for activity consistent with attackers attempting to disable various security mechanisms. Such activity may involve monitoring for suspicious registry activity, as this is where much of the configuration for Windows and various other programs reside, or explicitly attempting to shut down security-related services. Other times, attackers attempt various tricks to prevent specific programs from running, such as adding the certificates with which the security tools are signed to a block list (which would prevent them from running). +[analytic_story://Domain Trust Discovery] +category = Adversary Tactics +last_updated = 2021-03-25 +version = 1 +references = ["https://attack.mitre.org/techniques/T1482/"] +maintainers = [{"company": "Splunk", "email": "-", "name": "Michael Haag"}] +spec_version = 3 +searches = ["ESCU - Windows AdFind Exe - Rule", "ESCU - NLTest Domain Trust Discovery - Rule", "ESCU - DSQuery Domain Discovery - Rule"] +description = Adversaries may attempt to gather information on domain trust relationships that may be used to identify lateral movement opportunities in Windows multi-domain/forest environments. +narrative = Domain trusts provide a mechanism for a domain to allow access to resources based on the authentication procedures of another domain. Domain trusts allow the users of the trusted domain to access resources in the trusting domain. The information discovered may help the adversary conduct SID-History Injection, Pass the Ticket, and Kerberoasting. Domain trusts can be enumerated using the DSEnumerateDomainTrusts() Win32 API call, .NET methods, and LDAP. The Windows utility Nltest is known to be used by adversaries to enumerate domain trusts. + [analytic_story://Dynamic DNS] category = Malware last_updated = 2018-09-06 @@ -390,7 +412,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = [{"company": "Splunk", "email": "-", "name": "Bhavin Patel"}] spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Get Notable History - Response Task", "ESCU - Get DNS traffic ratio - Response Task", "ESCU - Get DNS Server History for a host - Response Task", "ESCU - Get Process Responsible For The DNS Traffic - Response Task"] +searches = ["ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get Process Responsible For The DNS Traffic - Response Task", "ESCU - Get DNS traffic ratio - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get DNS Server History for a host - Response Task"] description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and deny lists. narrative = Dynamic DNS services (DDNS) are legitimate low-cost or free services that allow users to rapidly update domain resolutions to IP infrastructure. While their usage can be benign, malicious actors can abuse DDNS to host harmful payloads or interactive-command-and-control infrastructure. These attackers will manually update or automate domain resolution changes by routing dynamic domains to IP addresses that circumvent firewall blocks and deny lists and frustrate a network defender's analytic and investigative processes. These searches will look for DNS queries made from within your infrastructure to suspicious dynamic domains and then investigate more deeply, when appropriate. While this list of top-level dynamic domains is not exhaustive, it can be dynamically updated as new suspicious dynamic domains are identified. @@ -401,7 +423,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] maintainers = [{"company": "Splunk", "email": "-", "name": "Bhavin Patel"}] spec_version = 3 -searches = ["ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Get History Of Email Sources - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Process Information For Port Activity - Response Task"] +searches = ["ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Process Information For Port Activity - Response Task", "ESCU - Get History Of Email Sources - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Parent Process Info - Response Task"] description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. narrative = The trojan downloader known as Emotet first surfaced in 2014, when it was discovered targeting the banking industry to steal credentials. However, according to a joint technical alert (TA) issued by three government agencies (https://www.us-cert.gov/ncas/alerts/TA18-201A), Emotet has evolved far beyond those beginnings to become what a ThreatPost article called a threat-delivery service(see https://threatpost.com/emotet-malware-evolves-beyond-banking-to-threat-delivery-service/134342/). For example, in early 2018, Emotet was found to be using its loader function to spread the Quakbot and Ransomware variants. \ According to the TA, the the malware continues to be among the most costly and destructive malware affecting the private and public sectors. Researchers have linked it to the threat group Mealybug, which has also been on the security communitys radar since 2014.\ @@ -425,7 +447,7 @@ version = 1 references = ["https://cloud.google.com/iam/docs/understanding-service-accounts"] maintainers = [{"company": "Splunk", "email": "-", "name": "Rod Soto"}] spec_version = 3 -searches = ["ESCU - GCP Detect accounts with high risk roles by project - Rule", "ESCU - GCP Detect high risk permissions by resource and account - Rule", "ESCU - GCP Detect gcploit framework - Rule", "ESCU - gcp detect oauth token abuse - Rule", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - GCP Detect high risk permissions by resource and account - Rule", "ESCU - GCP Detect accounts with high risk roles by project - Rule", "ESCU - GCP Detect gcploit framework - Rule", "ESCU - gcp detect oauth token abuse - Rule", "ESCU - Get Notable History - Response Task"] description = Track when a user assumes an IAM role in another GCP account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity. narrative = Google Cloud Platform (GCP) admins manage access to GCP resources and services across the enterprise using GCP Identity and Access Management (IAM) functionality. IAM provides the ability to create and manage GCP users, groups, and roles-each with their own unique set of privileges and defined access to specific resources (such as Compute instances, the GCP Management Console, API, or the command-line interface). Unlike conventional (human) users, IAM roles are potentially assumable by anyone in the organization. They provide users with dynamically created temporary security credentials that expire within a set time period.\ In between the time between when the temporary credentials are issued and when they expire is a period of opportunity, where a user could leverage the temporary credentials to wreak havoc-spin up or remove instances, create new users, elevate privileges, and other malicious activities-throughout the environment.\ @@ -438,7 +460,7 @@ version = 1 references = ["https://www.splunk.com/en_us/blog/security/detecting-hafnium-exchange-server-zero-day-activity-in-splunk.html", "https://www.volexity.com/blog/2021/03/02/active-exploitation-of-microsoft-exchange-zero-day-vulnerabilities/", "https://www.microsoft.com/security/blog/2021/03/02/hafnium-targeting-exchange-servers/", "https://blog.rapid7.com/2021/03/03/rapid7s-insightidr-enables-detection-and-response-to-microsoft-exchange-0-day/"] maintainers = [{"company": "Splunk", "email": "-", "name": "Michael Haag"}] spec_version = 3 -searches = ["ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Detect Exchange Web Shell - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Nishang PowershellTCPOneLine - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Any Powershell DownloadString - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Dump LSASS via procdump Rename - Rule", "ESCU - Ntdsutil Export NTDS - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Dump LSASS via procdump - Rule", "ESCU - Unified Messaging Service Spawning a Process - Rule", "ESCU - W3WP Spawning Shell - Rule"] +searches = ["ESCU - Nishang PowershellTCPOneLine - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Dump LSASS via procdump Rename - Rule", "ESCU - Any Powershell DownloadString - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Ntdsutil Export NTDS - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - W3WP Spawning Shell - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Detect Exchange Web Shell - Rule", "ESCU - Dump LSASS via procdump - Rule", "ESCU - Unified Messaging Service Spawning a Process - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule"] description = HAFNIUM group was identified by Microsoft as exploiting 4 Microsoft Exchange CVEs in the wild - CVE-2021-26855, CVE-2021-26857, CVE-2021-26858 and CVE-2021-27065. narrative = On Tuesday, March 2, 2021, Microsoft released a set of security patches for its mail server, Microsoft Exchange. These patches respond to a group of vulnerabilities known to impact Exchange 2013, 2016, and 2019. It is important to note that an Exchange 2010 security update has also been issued, though the CVEs do not reference that version as being vulnerable.\ While the CVEs do not shed much light on the specifics of the vulnerabilities or exploits, the first vulnerability (CVE-2021-26855) has a remote network attack vector that allows the attacker, a group Microsoft named HAFNIUM, to authenticate as the Exchange server. Three additional vulnerabilities (CVE-2021-26857, CVE-2021-26858, and CVE-2021-27065) were also identified as part of this activity. When chained together along with CVE-2021-26855 for initial access, the attacker would have complete control over the Exchange server. This includes the ability to run code as SYSTEM and write to any path on the server.\ @@ -451,7 +473,7 @@ version = 2 references = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] maintainers = [{"company": "Splunk", "email": "-", "name": "Rico Valdez"}] spec_version = 3 -searches = ["ESCU - Remote Desktop Process Running On System - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - Get History Of Email Sources - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get DNS Server History for a host - Response Task", "ESCU - Get Process Responsible For The DNS Traffic - Response Task", "ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get DNS traffic ratio - Response Task", "ESCU - Get Process Information For Port Activity - Response Task", "ESCU - Get Outbound Emails to Hidden Cobra Threat Actors - Response Task", "ESCU - Investigate Successful Remote Desktop Authentications - Response Task"] +searches = ["ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get DNS Server History for a host - Response Task", "ESCU - Get Process Information For Port Activity - Response Task", "ESCU - Get History Of Email Sources - Response Task", "ESCU - Get DNS traffic ratio - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Process Responsible For The DNS Traffic - Response Task", "ESCU - Investigate Successful Remote Desktop Authentications - Response Task", "ESCU - Get Outbound Emails to Hidden Cobra Threat Actors - Response Task", "ESCU - Get Parent Process Info - Response Task"] description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. narrative = North Korea's government-sponsored "cyber army" has been slowly building momentum and gaining sophistication over the last 15 years or so. As a result, the group's activity, which the US government refers to as "Hidden Cobra," has surreptitiously crept onto the collective radar as a preeminent global threat.\ These state-sponsored actors are thought to be responsible for everything from a hack on a South Korean nuclear plant to an attack on Sony in anticipation of its release of the movie "The Interview" at the end of 2014. They're also notorious for cyberespionage. In recent years, the group seems to be focused on financial crimes, such as cryptojacking.\ @@ -476,7 +498,7 @@ version = 1 references = ["https://attack.mitre.org/techniques/T1105/"] maintainers = [{"company": "Splunk", "email": "-", "name": "Michael Haag"}] spec_version = 3 -searches = ["ESCU - CertUtil Download With URLCache and Split Arguments - Rule", "ESCU - CertUtil Download With VerifyCtl and Split Arguments - Rule", "ESCU - Suspicious Curl Network Connection - Rule"] +searches = ["ESCU - Suspicious Curl Network Connection - Rule", "ESCU - Any Powershell DownloadFile - Rule", "ESCU - Any Powershell DownloadString - Rule", "ESCU - CertUtil Download With VerifyCtl and Split Arguments - Rule", "ESCU - CertUtil Download With URLCache and Split Arguments - Rule", "ESCU - BITSAdmin Download File - Rule"] description = Adversaries may transfer tools or other files from an external system into a compromised environment. Files may be copied from an external adversary controlled system through the command and control channel to bring tools into the victim network or through alternate protocols with another tool such as FTP. narrative = Ingress tool transfer is a Technique under tactic Command and Control. Behaviors will include the use of living off the land binaries to download implants or binaries over alternate communication ports. It is imperative to baseline applications on endpoints to understand what generates network activity, to where, and what is its native behavior. These utilities, when abused, will write files to disk in world writeable paths.\ During triage, review the reputation of the remote public destination IP or domain. Capture any files written to disk and perform analysis. Review other parrallel processes for additional behaviors. @@ -487,7 +509,7 @@ version = 1 references = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] maintainers = [{"company": "Splunk", "email": "-", "name": "Bhavin Patel"}] spec_version = 3 -searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Get Notable History - Response Task"] description = In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. narrative = This Analytic Story looks for probing and exploitation attempts targeting JBoss application servers. While the vulnerabilities associated with this story are rather dated, they were leveraged in a spring 2016 campaign in connection with the Samsam ransomware variant. Incidents involving this ransomware are unique, in that they begin with attacks against vulnerable services, rather than the phishing or drive-by attacks more common with ransomware. In this case, vulnerable JBoss applications appear to be the target of choice.\ It is helpful to understand how often a notable event generated by this story occurs, as well as the commonalities between some of these events, both of which may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. It may also help to understand whether the issue is restricted to a single user/system or whether it is broader in scope.\ @@ -512,7 +534,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = [{"company": "Splunk", "email": "-", "name": "Rod Soto"}] spec_version = 3 -searches = ["ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Kubernetes Azure pod scan fingerprint - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes cluster pod scan detection - Rule", "ESCU - Kubernetes Azure scan fingerprint - Rule", "ESCU - Get Notable History - Response Task", "ESCU - Amazon EKS Kubernetes activity by src ip - Response Task", "ESCU - GCP Kubernetes activity by src ip - Response Task"] +searches = ["ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - Kubernetes Azure scan fingerprint - Rule", "ESCU - GCP Kubernetes cluster pod scan detection - Rule", "ESCU - Kubernetes Azure pod scan fingerprint - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - GCP Kubernetes activity by src ip - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Amazon EKS Kubernetes activity by src ip - Response Task"] description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. narrative = Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitve information and management priviledges of production workloads, microservices and applications. These searches allow operator to detect suspicious unauthenticated requests from the internet to kubernetes cluster. @@ -523,7 +545,7 @@ version = 1 references = ["https://www.splunk.com/en_us/blog/security/approaching-kubernetes-security-detecting-kubernetes-scan-with-splunk.html"] maintainers = [{"company": "Splunk", "email": "-", "name": "Rod Soto"}] spec_version = 3 -searches = ["ESCU - Kubernetes GCP detect sensitive object access - Rule", "ESCU - AWS EKS Kubernetes cluster sensitive object access - Rule", "ESCU - Kubernetes GCP detect suspicious kubectl calls - Rule", "ESCU - Kubernetes AWS detect service accounts forbidden failure access - Rule", "ESCU - Kubernetes GCP detect service accounts forbidden failure access - Rule", "ESCU - Kubernetes Azure detect service accounts forbidden failure access - Rule", "ESCU - Kubernetes AWS detect suspicious kubectl calls - Rule", "ESCU - Kubernetes Azure detect sensitive object access - Rule", "ESCU - Kubernetes Azure detect suspicious kubectl calls - Rule", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - Kubernetes GCP detect service accounts forbidden failure access - Rule", "ESCU - Kubernetes GCP detect suspicious kubectl calls - Rule", "ESCU - Kubernetes Azure detect service accounts forbidden failure access - Rule", "ESCU - Kubernetes Azure detect suspicious kubectl calls - Rule", "ESCU - Kubernetes AWS detect suspicious kubectl calls - Rule", "ESCU - Kubernetes Azure detect sensitive object access - Rule", "ESCU - Kubernetes GCP detect sensitive object access - Rule", "ESCU - AWS EKS Kubernetes cluster sensitive object access - Rule", "ESCU - Kubernetes AWS detect service accounts forbidden failure access - Rule", "ESCU - Get Notable History - Response Task"] description = This story addresses detection and response of accounts acccesing Kubernetes cluster sensitive objects such as configmaps or secrets providing information on items such as user user, group. object, namespace and authorization reason. narrative = Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitive objects within its architecture, specifically configmaps and secrets, if accessed by an attacker can lead to further compromise. These searches allow operator to detect suspicious requests against Kubernetes sensitive objects. @@ -534,7 +556,7 @@ version = 1 references = ["https://www.splunk.com/en_us/blog/security/approaching-kubernetes-security-detecting-kubernetes-scan-with-splunk.html"] maintainers = [{"company": "Splunk", "email": "-", "name": "Rod Soto"}] spec_version = 3 -searches = ["ESCU - Kubernetes Azure detect RBAC authorization by account - Rule", "ESCU - Kubernetes AWS detect sensitive role access - Rule", "ESCU - Kubernetes GCP detect most active service accounts by pod - Rule", "ESCU - Kubernetes AWS detect RBAC authorization by account - Rule", "ESCU - Kubernetes GCP detect sensitive role access - Rule", "ESCU - Kubernetes GCP detect RBAC authorizations by account - Rule", "ESCU - Kubernetes Azure detect sensitive role access - Rule", "ESCU - Kubernetes Azure detect most active service accounts by pod namespace - Rule", "ESCU - Kubernetes AWS detect most active service accounts by pod - Rule", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - Kubernetes GCP detect RBAC authorizations by account - Rule", "ESCU - Kubernetes GCP detect most active service accounts by pod - Rule", "ESCU - Kubernetes Azure detect sensitive role access - Rule", "ESCU - Kubernetes Azure detect RBAC authorization by account - Rule", "ESCU - Kubernetes AWS detect sensitive role access - Rule", "ESCU - Kubernetes AWS detect most active service accounts by pod - Rule", "ESCU - Kubernetes AWS detect RBAC authorization by account - Rule", "ESCU - Kubernetes GCP detect sensitive role access - Rule", "ESCU - Kubernetes Azure detect most active service accounts by pod namespace - Rule", "ESCU - Get Notable History - Response Task"] description = This story addresses detection and response around Sensitive Role usage within a Kubernetes clusters against cluster resources and namespaces. narrative = Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitive roles within its architecture, specifically configmaps and secrets, if accessed by an attacker can lead to further compromise. These searches allow operator to detect suspicious requests against Kubernetes role activities @@ -545,7 +567,7 @@ version = 2 references = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] maintainers = [{"company": "Splunk", "email": "-", "name": "David Dorsey"}] spec_version = 3 -searches = ["ESCU - Kerberoasting spn request with RC4 encryption - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Get History Of Email Sources - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Process Information For Port Activity - Response Task", "ESCU - Investigate Successful Remote Desktop Authentications - Response Task"] +searches = ["ESCU - Kerberoasting spn request with RC4 encryption - Rule", "ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Process Information For Port Activity - Response Task", "ESCU - Get History Of Email Sources - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Investigate Successful Remote Desktop Authentications - Response Task", "ESCU - Get Parent Process Info - Response Task"] description = Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. narrative = Once attackers gain a foothold within an enterprise, they will seek to expand their accesses and leverage techniques that facilitate lateral movement. Attackers will often spend quite a bit of time and effort moving laterally. Because lateral movement renders an attacker the most vulnerable to detection, it's an excellent focus for detection and investigation.\ Indications of lateral movement can include the abuse of system utilities (such as `psexec.exe`), unauthorized use of remote desktop services, `file/admin$` shares, WMI, PowerShell, pass-the-hash, or the abuse of scheduled tasks. Organizations must be extra vigilant in detecting lateral movement techniques and look for suspicious activity in and around high-value strategic network assets, such as Active Directory, which are often considered the primary target or "crown jewels" to a persistent threat actor.\ @@ -560,7 +582,7 @@ version = 4 references = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = [{"company": "Splunk", "email": "-", "name": "David Dorsey"}] spec_version = 3 -searches = ["ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Any Powershell DownloadString - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Any Powershell DownloadFile - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get History Of Email Sources - Response Task", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - Any Powershell DownloadFile - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Any Powershell DownloadString - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get History Of Email Sources - Response Task", "ESCU - Get Parent Process Info - Response Task"] description = Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. narrative = The searches in this Analytic Story monitor for parameters often used for malicious purposes. It is helpful to understand how often the notable events generated by this story occur, as well as the commonalities between some of these events. These factors may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. Likewise, it is important to determine whether the issue is restricted to a single user/system or is broader in scope.\ The following factors may assist you in determining whether the event is malicious: \ @@ -580,7 +602,7 @@ version = 1 references = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] maintainers = [{"company": "Splunk", "email": "-", "name": "David Dorsey"}] spec_version = 3 -searches = ["ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Get Notable History - Response Task", "ESCU - All backup logs for host - Response Task"] +searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - Get Notable History - Response Task", "ESCU - All backup logs for host - Response Task"] description = Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. narrative = Having backups is a standard best practice that helps ensure continuity of business operations. Having mature backup processes can also help you reduce the risks of many security-related incidents and streamline your response processes. The detection searches in this Analytic Story will help you identify systems that have backup failures, as well as systems that have not been backed up for an extended period of time. The story will also return the notable event history and all of the backup logs for an endpoint. @@ -591,7 +613,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = [{"company": "Splunk", "email": "-", "name": "David Dorsey"}] spec_version = 3 -searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Parent Process Info - Response Task"] description = Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. narrative = It is critical to identify unauthorized software and processes running on enterprise endpoints and determine whether they are likely to be malicious. This Analytic Story requires the user to populate the Interesting Processes table within Enterprise Security with prohibited processes. An included support search will augment this data, adding information on processes thought to be malicious. This search requires data from endpoint detection-and-response solutions, endpoint data sources (such as Sysmon), or Windows Event Logs--assuming that the Active Directory administrator has enabled process tracking within the System Event Audit Logs.\ It is important to investigate any software identified as suspicious, in order to understand how it was installed or executed. Analyzing authentication logs or any historic notable events might elicit additional investigative leads of interest. For best results, schedule the search to run every two weeks. @@ -616,7 +638,7 @@ version = 2 references = ["https://www.microsoft.com/security/blog/2021/03/04/goldmax-goldfinder-sibot-analyzing-nobelium-malware/", "https://www.fireeye.com/blog/threat-research/2020/12/evasive-attacker-leverages-solarwinds-supply-chain-compromises-with-sunburst-backdoor.html", "https://msrc-blog.microsoft.com/2020/12/13/customer-guidance-on-recent-nation-state-cyber-attacks/"] maintainers = [{"company": "Michael Haag, Splunk", "email": "-", "name": "Patrick Bareiss"}] spec_version = 3 -searches = ["ESCU - Sunburst Correlation DLL and Network Event - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Supernova Webshell - Rule", "ESCU - Detect Rundll32 Inline HTA Execution - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Windows AdFind Exe - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Scheduled Task Deleted Or Created via CMD - Rule", "ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] +searches = ["ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Supernova Webshell - Rule", "ESCU - Windows AdFind Exe - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect Rundll32 Inline HTA Execution - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Sunburst Correlation DLL and Network Event - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Scheduled Task Deleted Or Created via CMD - Rule", "ESCU - Schtasks scheduling job on remote system - Rule"] description = Sunburst is a trojanized updates to SolarWinds Orion IT monitoring and management software. It was discovered by FireEye in December 2020. The actors behind this campaign gained access to numerous public and private organizations around the world. narrative = This Analytic Story supports you to detect Tactics, Techniques and Procedures (TTPs) of the NOBELIUM Group. The threat actor behind sunburst compromised the SolarWinds.Orion.Core.BusinessLayer.dll, is a SolarWinds digitally-signed component of the Orion software framework that contains a backdoor that communicates via HTTP to third party servers. The detections in this Analytic Story are focusing on the dll loading events, file create events and network events to detect This malware. @@ -627,7 +649,7 @@ version = 1 references = ["https://docs.microsoft.com/en-us/previous-versions/tn-archive/bb490939(v=technet.10)", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] maintainers = [{"company": "Splunk", "email": "-", "name": "Bhavin Patel"}] spec_version = 3 -searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Parent Process Info - Response Task"] description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. narrative = It is a common practice for attackers of all types to leverage native Windows tools and functionality to execute commands for malicious reasons. One such tool on Windows OS is `netsh.exe`,a command-line scripting utility that allows you to--either locally or remotely--display or modify the network configuration of a computer that is currently running. `Netsh.exe` can be used to discover and disable local firewall settings. It can also be used to set up a remote connection to a host from an infected system.\ To get started, run the detection search to identify parent processes of `netsh.exe`. @@ -639,7 +661,7 @@ version = 1 references = ["https://i.blackhat.com/USA-20/Thursday/us-20-Bienstock-My-Cloud-Is-APTs-Cloud-Investigating-And-Defending-Office-365.pdf"] maintainers = [{"company": "Splunk", "email": "-", "name": "Patrick Bareiss"}] spec_version = 3 -searches = ["ESCU - O365 Disable MFA - Rule", "ESCU - O365 Added Service Principal - Rule", "ESCU - O365 Suspicious Rights Delegation - Rule", "ESCU - O365 Add App Role Assignment Grant User - Rule", "ESCU - O365 New Federated Domain Added - Rule", "ESCU - O365 Suspicious User Email Forwarding - Rule", "ESCU - O365 Bypass MFA via Trusted IP - Rule", "ESCU - O365 PST export alert - Rule", "ESCU - O365 Excessive Authentication Failures Alert - Rule", "ESCU - High Number of Login Failures from a single source - Rule", "ESCU - O365 Suspicious Admin Email Forwarding - Rule", "ESCU - O365 Excessive SSO logon errors - Rule"] +searches = ["ESCU - O365 Suspicious Admin Email Forwarding - Rule", "ESCU - O365 Bypass MFA via Trusted IP - Rule", "ESCU - O365 Suspicious Rights Delegation - Rule", "ESCU - O365 Excessive SSO logon errors - Rule", "ESCU - O365 Added Service Principal - Rule", "ESCU - High Number of Login Failures from a single source - Rule", "ESCU - O365 Excessive Authentication Failures Alert - Rule", "ESCU - O365 New Federated Domain Added - Rule", "ESCU - O365 PST export alert - Rule", "ESCU - O365 Disable MFA - Rule", "ESCU - O365 Add App Role Assignment Grant User - Rule", "ESCU - O365 Suspicious User Email Forwarding - Rule"] description = This story is focused around detecting Office 365 Attacks. narrative = More and more companies are using Microsofts Office 365 cloud offering. Therefore, we see more and more attacks against Office 365. This story provides various detections for Office 365 attacks. @@ -650,7 +672,7 @@ version = 2 references = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] maintainers = [{"company": "Splunk", "email": "-", "name": "David Dorsey"}] spec_version = 3 -searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get History Of Email Sources - Response Task", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get History Of Email Sources - Response Task", "ESCU - Get Parent Process Info - Response Task"] description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. narrative = In May of 2018, the attack group Orangeworm was implicated for installing a custom backdoor called Trojan.Kwampirs within large international healthcare corporations in the United States, Europe, and Asia. This malware provides the attackers with remote access to the target system, decrypting and extracting a copy of its main DLL payload from its resource section. Before writing the payload to disk, it inserts a randomly generated string into the middle of the decrypted payload in an attempt to evade hash-based detections.\ Awareness of the Orangeworm group first surfaced in January, 2015. It has conducted targeted attacks against related industries, as well, such as pharmaceuticals and healthcare IT solution providers.\ @@ -682,7 +704,7 @@ version = 1 references = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] maintainers = [{"company": "iDefense", "email": "-", "name": "iDefense Cyber Espionage Team"}] spec_version = 3 -searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get History Of Email Sources - Response Task", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get History Of Email Sources - Response Task", "ESCU - Get Parent Process Info - Response Task"] description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. narrative = This story was created as a joint effort between iDefense and Splunk.\ iDefense analysts have recently discovered a Windows executable file that, upon execution, spoofs a decryption tool and then drops a file that appears to be the custom-built javascript backdoor, "Orz," which is associated with the threat actors known as MUDCARP (as well as "temp.Periscope" and "Leviathan"). The file is executed using Wscript.\ @@ -720,7 +742,7 @@ version = 1 references = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] maintainers = [{"company": "Splunk", "email": "-", "name": "Rico Valdez"}] spec_version = 3 -searches = ["ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Get Notable History - Response Task", "ESCU - Get DNS Server History for a host - Response Task", "ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Process Information For Port Activity - Response Task"] +searches = ["ESCU - TOR Traffic - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Process Information For Port Activity - Response Task", "ESCU - Get DNS Server History for a host - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Parent Process Info - Response Task"] description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. narrative = A traditional security best practice is to control the ports, protocols, and services allowed within your environment. By limiting the services and protocols to those explicitly approved by policy, administrators can minimize the attack surface. The combined effect allows both network defenders and security controls to focus and not be mired in superfluous traffic or data types. Looking for deviations to policy can identify attacker activity that abuses services and protocols to run on alternate or non-standard ports in the attempt to avoid detection or frustrate forensic analysts. @@ -731,7 +753,7 @@ version = 1 references = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] maintainers = [{"company": "Splunk", "email": "-", "name": "David Dorsey"}] spec_version = 3 -searches = ["ESCU - BCDEdit Failure Recovery Modification - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - WBAdmin Delete System Backups - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious Scheduled Task from Public Directory - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - TOR Traffic - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Get History Of Email Sources - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Sysmon WMI Activity for Host - Response Task", "ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Process Information For Port Activity - Response Task", "ESCU - Get Backup Logs For Endpoint - Response Task"] +searches = ["ESCU - Windows Event Log Cleared - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - BCDEdit Failure Recovery Modification - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious Scheduled Task from Public Directory - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - WBAdmin Delete System Backups - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Process Information For Port Activity - Response Task", "ESCU - Get Sysmon WMI Activity for Host - Response Task", "ESCU - Get Backup Logs For Endpoint - Response Task", "ESCU - Get History Of Email Sources - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Parent Process Info - Response Task"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. narrative = Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise. Attackers can deploy ransomware to enterprises through spearphishing campaigns and driveby downloads, as well as through traditional remote service-based exploitation. In the case of the WannaCry campaign, there was self-propagating wormable functionality that was used to maximize infection. Fortunately, organizations can apply several techniques--such as those in this Analytic Story--to detect and or mitigate the effects of ransomware. @@ -742,7 +764,7 @@ version = 1 references = ["https://rhinosecuritylabs.com/aws/s3-ransomware-part-1-attack-vector/", "https://github.com/d1vious/git-wild-hunt", "https://www.youtube.com/watch?v=PgzNib37g0M"] maintainers = [{"company": "David Dorsey, Splunk", "email": "-", "name": "Rod Soto"}] spec_version = 3 -searches = ["ESCU - AWS Detect Users creating keys with encrypt policy without MFA - Rule", "ESCU - AWS Detect Users with KMS keys performing encryption S3 - Rule", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - AWS Detect Users with KMS keys performing encryption S3 - Rule", "ESCU - AWS Detect Users creating keys with encrypt policy without MFA - Rule", "ESCU - Get Notable History - Response Task"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware. These searches include cloud related objects that may be targeted by malicious actors via cloud providers own encryption features. narrative = Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise.Cloud ransomware can be deployed by obtaining high privilege credentials from targeted users or resources. @@ -753,7 +775,7 @@ version = 1 references = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] maintainers = [{"company": "Splunk", "email": "-", "name": "Bhavin Patel"}] spec_version = 3 -searches = ["ESCU - Detect Port Security Violation - Rule", "ESCU - Detect Rogue DHCP Server - Rule", "ESCU - Detect Software Download To Network Device - Rule", "ESCU - Detect IPv6 Network Infrastructure Threats - Rule", "ESCU - Detect Traffic Mirroring - Rule", "ESCU - Detect ARP Poisoning - Rule", "ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - Detect Rogue DHCP Server - Rule", "ESCU - Detect Port Security Violation - Rule", "ESCU - Detect Traffic Mirroring - Rule", "ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Detect ARP Poisoning - Rule", "ESCU - Detect IPv6 Network Infrastructure Threats - Rule", "ESCU - Detect Software Download To Network Device - Rule", "ESCU - Get Notable History - Response Task"] description = Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. narrative = Networking devices, such as routers and switches, are often overlooked as resources that attackers will leverage to subvert an enterprise. Advanced threats actors have shown a proclivity to target these critical assets as a means to siphon and redirect network traffic, flash backdoored operating systems, and implement cryptographic weakened algorithms to more easily decrypt network traffic.\ This Analytic Story helps you gain a better understanding of how your network devices are interacting with your hosts. By compromising your network devices, attackers can obtain direct access to the company's internal infrastructure— effectively increasing the attack surface and accessing private services/data. @@ -765,7 +787,7 @@ version = 1 references = ["https://www.splunk.com/en_us/blog/security/detecting-ryuk-using-splunk-attack-range.html", "https://www.crowdstrike.com/blog/big-game-hunting-with-ryuk-another-lucrative-targeted-ransomware/", "https://us-cert.cisa.gov/ncas/alerts/aa20-302a"] maintainers = [{"company": "Splunk", "email": "-", "name": "Jose Hernandez"}] spec_version = 3 -searches = ["ESCU - BCDEdit Failure Recovery Modification - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - WBAdmin Delete System Backups - Rule", "ESCU - Windows DisableAntiSpyware Registry - Rule", "ESCU - Ryuk Wake on LAN Command - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - NLTest Domain Trust Discovery - Rule", "ESCU - Suspicious Scheduled Task from Public Directory - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Windows Security Account Manager Stopped - Rule", "ESCU - Windows connhost exe started forcefully - Rule", "ESCU - Ryuk Test Files Detected - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - Windows Security Account Manager Stopped - Rule", "ESCU - Windows connhost exe started forcefully - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - WBAdmin Delete System Backups - Rule", "ESCU - Windows DisableAntiSpyware Registry - Rule", "ESCU - Ryuk Wake on LAN Command - Rule", "ESCU - BCDEdit Failure Recovery Modification - Rule", "ESCU - Ryuk Test Files Detected - Rule", "ESCU - NLTest Domain Trust Discovery - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Suspicious Scheduled Task from Public Directory - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Get Notable History - Response Task"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the Ryuk ransomware, including looking for file writes associated with Ryuk, Stopping Security Access Manager, DisableAntiSpyware registry key modification, suspicious psexec use, and more. narrative = Cybersecurity Infrastructure Security Agency (CISA) released Alert (AA20-302A) on October 28th called “Ransomware Activity Targeting the Healthcare and Public Health Sector.” This alert details TTPs associated with ongoing and possible imminent attacks against the Healthcare sector, and is a joint advisory in coordination with other U.S. Government agencies. The objective of these malicious campaigns is to infiltrate targets in named sectors and to drop ransomware payloads, which will likely cause disruption of service and increase risk of actual harm to the health and safety of patients at hospitals, even with the aggravant of an ongoing COVID-19 pandemic. This document specifically refers to several crimeware exploitation frameworks, emphasizing the use of Ryuk ransomware as payload. The Ryuk ransomware payload is not new. It has been well documented and identified in multiple variants. Payloads need a carrier, and for Ryuk it has often been exploitation frameworks such as Cobalt Strike, or popular crimeware frameworks such as Emotet or Trickbot. @@ -788,7 +810,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] maintainers = [{"company": "Splunk", "email": "-", "name": "Rico Valdez"}] spec_version = 3 -searches = ["ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Batch File Write to System32 - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Get History Of Email Sources - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Process Information For Port Activity - Response Task", "ESCU - Get Backup Logs For Endpoint - Response Task", "ESCU - Investigate Successful Remote Desktop Authentications - Response Task"] +searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Batch File Write to System32 - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Process Information For Port Activity - Response Task", "ESCU - Get Backup Logs For Endpoint - Response Task", "ESCU - Get History Of Email Sources - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Investigate Successful Remote Desktop Authentications - Response Task", "ESCU - Get Parent Process Info - Response Task"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. narrative = The first version of the SamSam ransomware (a.k.a. Samas or SamsamCrypt) was launched in 2015 by a group of Iranian threat actors. The malicious software has affected and continues to affect thousands of victims and has raised almost $6M in ransom.\ Although categorized under the heading of ransomware, SamSam campaigns have some importance distinguishing characteristics. Most notable is the fact that conventional ransomware is a numbers game. Perpetrators use a "spray-and-pray" approach with phishing campaigns or other mechanisms, charging a small ransom (typically under $1,000). The goal is to find a large number of victims willing to pay these mini-ransoms, adding up to a lucrative payday. They use relatively simple methods for infecting systems.\ @@ -804,7 +826,7 @@ version = 1 references = ["https://redcanary.com/blog/clipping-silver-sparrows-wings/", "https://www.sentinelone.com/blog/5-things-you-need-to-know-about-silver-sparrow/"] maintainers = [{"company": "Splunk", "email": "-", "name": "Michael Haag"}] spec_version = 3 -searches = ["ESCU - Suspicious SQLite3 LSQuarantine Behavior - Rule", "ESCU - Suspicious PlistBuddy Usage via OSquery - Rule", "ESCU - Suspicious PlistBuddy Usage - Rule", "ESCU - Suspicious Curl Network Connection - Rule"] +searches = ["ESCU - Suspicious SQLite3 LSQuarantine Behavior - Rule", "ESCU - Suspicious Curl Network Connection - Rule", "ESCU - Suspicious PlistBuddy Usage - Rule", "ESCU - Suspicious PlistBuddy Usage via OSquery - Rule"] description = Silver Sparrow, identified by Red Canary Intelligence, is a new forward looking MacOS (Intel and M1) malicious software downloader utilizing JavaScript for execution and a launchAgent to establish persistence. narrative = Silver Sparrow works is a dropper and uses typical persistence mechanisms on a Mac. It is cross platform, covering both Intel and Apple M1 architecture. To this date, no implant has been downloaded for malicious purposes. During installation of the update.pkg or updater.pkg file, the malicious software utilizes JavaScript to generate files and scripts on disk for persistence.These files later download a implant from an S3 bucket every hour. This analytic assists with identifying different types of macOS malware families establishing LaunchAgent persistence. Per SentinelOne source, it is predicted that Silver Sparrow is likely selling itself as a mechanism to 3rd party “affiliates” or pay-per-install (PPI) partners, typically seen as commodity adware/malware. Additional indicators and behaviors may be found within the references. @@ -846,7 +868,7 @@ version = 1 references = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] maintainers = [{"company": "Splunk", "email": "-", "name": "David Dorsey"}] spec_version = 3 -searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Investigate Network Traffic From src ip - Response Task", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Get Notable History - Response Task", "ESCU - Investigate Network Traffic From src ip - Response Task"] description = Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. narrative = Although there have been no reports of it being exploited, Splunk Enterprise versions through 7.0.1 reportedly have a vulnerability that may expose information through a REST endpoint (read more here: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings). NIST has included it in its vulnerability database (read more here: https://nvd.nist.gov/vuln/detail/CVE-2018-11409). The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Customers should upgrade to the latest version to reduce the risk of this vulnerability.\ Splunk Enterprise exposes partial information about the host operating system, hardware, and Splunk license. Splunk Enterprise before 6.6.0 exposes this information without authentication. Splunk Enterprise 6.6.0 and later exposes this information only to authenticated Splunk users. Based on the information exposure, Splunk characterizes this issue as a low severity impact.\ @@ -860,7 +882,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = [{"company": "Splunk", "email": "-", "name": "Bhavin Patel"}] spec_version = 3 -searches = ["ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Get Notable History - Response Task", "ESCU - AWS Investigate Security Hub alerts by dest - Response Task", "ESCU - Investigate AWS activities via region name - Response Task", "ESCU - Get EC2 Launch Details - Response Task", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Get EC2 Instance Details by instanceId - Response Task"] +searches = ["ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Investigate AWS activities via region name - Response Task", "ESCU - Get EC2 Launch Details - Response Task", "ESCU - AWS Investigate Security Hub alerts by dest - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get EC2 Instance Details by instanceId - Response Task"] description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and risk auditing within your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Console, AWS command-line interface, and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your AWS EC2 instances and helps you respond and investigate those activities. @@ -871,7 +893,7 @@ version = 1 references = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] maintainers = [{"company": "Splunk", "email": "-", "name": "Bhavin Patel"}] spec_version = 3 -searches = ["ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - Detect new user AWS Console Login - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - AWS Investigate User Activities By ARN - Response Task"] +searches = ["ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - Detect new user AWS Console Login - Rule", "ESCU - AWS Investigate User Activities By ARN - Response Task"] description = Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. narrative = It is important to monitor and control who has access to your AWS infrastructure. Detecting suspicious logins to your AWS infrastructure will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any EC2 instances created by the attacker. @@ -882,7 +904,7 @@ version = 2 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] maintainers = [{"company": "Splunk", "email": "-", "name": "Bhavin Patel"}] spec_version = 3 -searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - Detect New Open S3 Buckets over AWS CLI - Rule", "ESCU - Get Notable History - Response Task", "ESCU - Investigate AWS activities via region name - Response Task", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - AWS S3 Bucket details via bucketName - Response Task", "ESCU - Get All AWS Activity From IP Address - Response Task"] +searches = ["ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect New Open S3 Buckets over AWS CLI - Rule", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Investigate AWS activities via region name - Response Task", "ESCU - Get All AWS Activity From IP Address - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - AWS S3 Bucket details via bucketName - Response Task"] description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. narrative = As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\ Amazon's "shared responsibility" model dictates that the company has responsibility for the environment outside of the VM and the customer is responsible for the security inside of the S3 container. As such, it's important to stay vigilant for activities that may belie suspicious behavior inside of your environment.\ @@ -895,7 +917,7 @@ version = 1 references = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] maintainers = [{"company": "Splunk", "email": "-", "name": "Bhavin Patel"}] spec_version = 3 -searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Get DNS Server History for a host - Response Task", "ESCU - AWS Network Interface details via resourceId - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Process Responsible For The DNS Traffic - Response Task", "ESCU - Get Process Info - Response Task", "ESCU - Get DNS traffic ratio - Response Task", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Get Process Information For Port Activity - Response Task", "ESCU - AWS Network ACL Details from ID - Response Task", "ESCU - Get All AWS Activity From IP Address - Response Task"] +searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Get Process Info - Response Task", "ESCU - AWS Network Interface details via resourceId - Response Task", "ESCU - Get DNS Server History for a host - Response Task", "ESCU - Get Process Information For Port Activity - Response Task", "ESCU - Get All AWS Activity From IP Address - Response Task", "ESCU - Get DNS traffic ratio - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Process Responsible For The DNS Traffic - Response Task", "ESCU - AWS Network ACL Details from ID - Response Task"] description = Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). narrative = A virtual private cloud (VPC) is an on-demand managed cloud-computing service that isolates computing resources for each client. Inside the VPC container, the environment resembles a physical network. \ Amazon's VPC service enables you to launch EC2 instances and leverage other Amazon resources. The traffic that flows in and out of this VPC can be controlled via network access-control rules and security groups. Amazon also has a feature called VPC Flow Logs that enables you to log IP traffic going to and from the network interfaces in your VPC. This data is stored using Amazon CloudWatch Logs.\ @@ -909,7 +931,7 @@ version = 1 references = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/", "https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] maintainers = [{"company": "Splunk", "email": "-", "name": "Rico Valdez"}] spec_version = 3 -searches = ["ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - Detect AWS Console Login by New User - Rule", "ESCU - Investigate AWS User Activities by user field - Response Task", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - Detect AWS Console Login by New User - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Investigate AWS User Activities by user field - Response Task", "ESCU - Get Notable History - Response Task"] description = Monitor your cloud authentication events. Searches within this Analytic Story leverage the recent cloud updates to the Authentication data model to help you stay aware of and investigate suspicious login activity. narrative = It is important to monitor and control who has access to your cloud infrastructure. Detecting suspicious logins will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any compute activity whether legitimate or otherwise.\ This Analytic Story has data model versions of cloud searches leveraging Authentication data, including those looking for suspicious login activity, and cross-account activity for AWS. @@ -921,7 +943,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = [{"company": "Splunk", "email": "-", "name": "David Dorsey"}] spec_version = 3 -searches = ["ESCU - Cloud Instance Modified By Previously Unseen User - Rule", "ESCU - Abnormally High Number Of Cloud Instances Launched - Rule", "ESCU - Abnormally High Number Of Cloud Instances Destroyed - Rule", "ESCU - Get All AWS Activity From IP Address - Response Task", "ESCU - AWS Investigate User Activities By ARN - Response Task"] +searches = ["ESCU - Abnormally High Number Of Cloud Instances Launched - Rule", "ESCU - Abnormally High Number Of Cloud Instances Destroyed - Rule", "ESCU - Cloud Instance Modified By Previously Unseen User - Rule", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Get All AWS Activity From IP Address - Response Task"] description = Monitor your cloud infrastructure provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your cloud environment. narrative = Monitoring your cloud infrastructure logs allows you enable governance, compliance, and risk auditing. It is crucial for a company to monitor events and actions taken in the their cloud environments to ensure that your instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your cloud compute instances and helps you respond and investigate those activities. @@ -932,7 +954,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = [{"company": "Splunk", "email": "-", "name": "David Dorsey"}] spec_version = 3 -searches = ["ESCU - Cloud Provisioning Activity From Previously Unseen IP Address - Rule", "ESCU - Cloud Provisioning Activity From Previously Unseen Country - Rule", "ESCU - Cloud Provisioning Activity From Previously Unseen Region - Rule", "ESCU - Cloud Provisioning Activity From Previously Unseen City - Rule", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - Cloud Provisioning Activity From Previously Unseen City - Rule", "ESCU - Cloud Provisioning Activity From Previously Unseen IP Address - Rule", "ESCU - Cloud Provisioning Activity From Previously Unseen Region - Rule", "ESCU - Cloud Provisioning Activity From Previously Unseen Country - Rule", "ESCU - Get Notable History - Response Task"] description = Monitor your cloud infrastructure provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your cloud environment. narrative = Because most enterprise cloud infrastructure activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where it is impossible to add specific IPs to an allow list because they vary.\ This Analytic Story was designed to provide you with flexibility in the precision you employ in specifying legitimate geographic regions. It can be as specific as an IP address or a city, or as broad as a region (think state) or an entire country. By determining how precise you want your geographical locations to be and monitoring for new locations that haven't previously accessed your environment, you can detect adversaries as they begin to probe your environment. Since there are legitimate reasons for activities from unfamiliar locations, this is not a standalone indicator. Nevertheless, location can be a relevant piece of information that you may wish to investigate further. @@ -956,7 +978,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] maintainers = [{"company": "Splunk", "email": "-", "name": "Bhavin Patel"}] spec_version = 3 -searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Parent Process Info - Response Task"] description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. narrative = The ability to execute arbitrary commands via the Windows CLI is a primary goal for the adversary. With access to the shell, an attacker can easily run scripts and interact with the target system. Often, attackers may only have limited access to the shell or may obtain access in unusual ways. In addition, malware may execute and interact with the CLI in ways that would be considered unusual and inconsistent with typical user activity. This provides defenders with opportunities to identify suspicious use and investigate, as appropriate. This Analytic Story contains various searches to help identify this suspicious activity, as well as others to aid you in deeper investigation. @@ -967,7 +989,7 @@ version = 1 references = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] maintainers = [{"company": "Splunk", "email": "-", "name": "Rico Valdez"}] spec_version = 3 -searches = ["ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Get Notable History - Response Task", "ESCU - Get DNS Server History for a host - Response Task", "ESCU - Get Process Responsible For The DNS Traffic - Response Task", "ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get DNS traffic ratio - Response Task"] +searches = ["ESCU - Excessive DNS Failures - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get DNS Server History for a host - Response Task", "ESCU - Get DNS traffic ratio - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Process Responsible For The DNS Traffic - Response Task", "ESCU - Get Parent Process Info - Response Task"] description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. narrative = Although DNS is one of the fundamental underlying protocols that make the Internet work, it is often ignored (perhaps because of its complexity and effectiveness). However, attackers have discovered ways to abuse the protocol to meet their objectives. One potential abuse involves manipulating DNS to hijack traffic and redirect it to an IP address under the attacker's control. This could inadvertently send users intending to visit google.com, for example, to an unrelated malicious website. Another technique involves using the DNS protocol for command-and-control activities with the attacker's malicious code or to covertly exfiltrate data. The searches within this Analytic Story look for these types of abuses. @@ -978,7 +1000,7 @@ version = 1 references = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] maintainers = [{"company": "Splunk", "email": "-", "name": "Bhavin Patel"}] spec_version = 3 -searches = ["ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Get Emails From Specific Sender - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Email Info - Response Task"] +searches = ["ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Get Notable History - Response Task", "ESCU - Get Emails From Specific Sender - Response Task", "ESCU - Get Email Info - Response Task"] description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. narrative = It is a common practice for attackers of all types to leverage targeted spearphishing campaigns and mass mailers to deliver weaponized email messages and attachments. Fortunately, there are a number of ways to monitor email data in Splunk to detect suspicious content.\ Once a phishing message has been detected, the next steps are to answer the following questions: \ @@ -1004,7 +1026,7 @@ version = 2 references = ["https://redcanary.com/blog/introducing-atomictestharnesses/", "https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/techniques/T1218/005/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5"] maintainers = [{"company": "Michael Haag, Splunk", "email": "-", "name": "Bhavin Patel"}] spec_version = 3 -searches = ["ESCU - Detect MSHTA Url in Command Line - Rule", "ESCU - Detect mshta inline hta execution - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Suspicious mshta spawn - Rule", "ESCU - Detect mshta renamed - Rule", "ESCU - Detect Rundll32 Inline HTA Execution - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Suspicious mshta child process - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - Suspicious mshta child process - Rule", "ESCU - Detect mshta renamed - Rule", "ESCU - Suspicious mshta spawn - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect Rundll32 Inline HTA Execution - Rule", "ESCU - Detect MSHTA Url in Command Line - Rule", "ESCU - Detect mshta inline hta execution - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Parent Process Info - Response Task"] description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. narrative = One common adversary tactic is to bypass application control solutions via the mshta.exe process, which loads Microsoft HTML applications (mshtml.dll) with the .hta suffix. In these cases, attackers use the trusted Windows utility to proxy execution of malicious files, whether an .hta application, javascript, or VBScript.\ The searches in this story help you detect and investigate suspicious activity that may indicate that an attacker is leveraging mshta.exe to execute malicious code.\ @@ -1027,7 +1049,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] maintainers = [{"company": "Splunk", "email": "-", "name": "Rico Valdez"}] spec_version = 3 -searches = ["ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Multiple Okta Users With Invalid Credentials From The Same IP - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Investigate User Activities In Okta - Response Task", "ESCU - Investigate Okta Activity by app - Response Task", "ESCU - Investigate Okta Activity by IP Address - Response Task"] +searches = ["ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Multiple Okta Users With Invalid Credentials From The Same IP - Rule", "ESCU - Investigate User Activities In Okta - Response Task", "ESCU - Investigate Okta Activity by IP Address - Response Task", "ESCU - Investigate Okta Activity by app - Response Task"] description = Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. Okta is a popular tool to manage multiple users and the web-based applications they need to stay productive. The searches in this story will help monitor your Okta environment for suspicious activities and associated user behaviors. narrative = Okta is the leading single sign on (SSO) provider, allowing users to authenticate once to Okta, and from there access a variety of web-based applications. These applications are assigned to users and allow administrators to centrally manage which users are allowed to access which applications. It also provides centralized logging to help understand how the applications are used and by whom. \ While SSO is a major convenience for users, it also provides attackers with an opportunity. If the attacker can gain access to Okta, they can access a variety of applications. As such monitoring the environment is important. \ @@ -1051,7 +1073,7 @@ version = 1 references = ["https://attack.mitre.org/techniques/T1218/011/", "https://github.com/redcanaryco/atomic-red-team/blob/master/atomics/T1218.011/T1218.011.md", "https://lolbas-project.github.io/lolbas/Binaries/Rundll32"] maintainers = [{"company": "Splunk", "email": "-", "name": "Michael Haag"}] spec_version = 3 -searches = ["ESCU - Suspicious Rundll32 StartW - Rule", "ESCU - Suspicious Rundll32 no Command Line Arguments - Rule", "ESCU - Detect Rundll32 Application Control Bypass - setupapi - Rule", "ESCU - Detect Rundll32 Application Control Bypass - advpack - Rule", "ESCU - Suspicious Rundll32 dllregisterserver - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Suspicious Rundll32 Rename - Rule", "ESCU - Detect Rundll32 Application Control Bypass - syssetup - Rule"] +searches = ["ESCU - Detect Rundll32 Application Control Bypass - advpack - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Suspicious Rundll32 no Command Line Arguments - Rule", "ESCU - Suspicious Rundll32 Rename - Rule", "ESCU - Detect Rundll32 Application Control Bypass - setupapi - Rule", "ESCU - Suspicious Rundll32 dllregisterserver - Rule", "ESCU - Suspicious Rundll32 StartW - Rule", "ESCU - Detect Rundll32 Application Control Bypass - syssetup - Rule"] description = Monitor and detect techniques used by attackers who leverage rundll32.exe to execute arbitrary malicious code. narrative = One common adversary tactic is to bypass application control solutions via the rundll32.exe process. Natively, rundll32.exe will load DLLs and is a great example of a Living off the Land Binary. Rundll32.exe may load malicious DLLs by ordinals, function names or directly. The queries in this story focus on loading default DLLs, syssetup.dll, ieadvpack.dll, advpack.dll and setupapi.dll from disk that may be abused by adversaries. Additionally, two analytics developed to assist with identifying DLLRegisterServer, Start and StartW functions being called. The searches in this story help you detect and investigate suspicious activity that may indicate that an adversary is leveraging rundll32.exe to execute malicious code. @@ -1062,7 +1084,7 @@ version = 2 references = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] maintainers = [{"company": "Splunk", "email": "-", "name": "Rico Valdez"}] spec_version = 3 -searches = ["ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - Process Execution via WMI - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - WMI Temporary Event Subscription - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Sysmon WMI Activity for Host - Response Task", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - Process Execution via WMI - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - WMI Temporary Event Subscription - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Sysmon WMI Activity for Host - Response Task", "ESCU - Get Parent Process Info - Response Task"] description = Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. narrative = WMI is a Microsoft infrastructure for management data and operations on Windows operating systems. It includes of a set of utilities that can be leveraged to manage both local and remote Windows systems. Attackers are increasingly turning to WMI abuse in their efforts to conduct nefarious tasks, such as reconnaissance, detection of antivirus and virtual machines, code execution, lateral movement, persistence, and data exfiltration. \ The detection searches included in this Analytic Story are used to look for suspicious use of WMI commands that attackers may leverage to interact with remote systems. The searches specifically look for the use of WMI to run processes on remote systems.\ @@ -1075,7 +1097,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] maintainers = [{"company": "Splunk", "email": "-", "name": "Bhavin Patel"}] spec_version = 3 -searches = ["ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Parent Process Info - Response Task"] description = Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. narrative = Attackers are developing increasingly sophisticated techniques for hijacking target servers, while evading detection. One such technique that has become progressively more common is registry modification.\ The registry is a key component of the Windows operating system. It has a hierarchical database called "registry" that contains settings, options, and values for executables. Once the threat actor gains access to a machine, they can use reg.exe to modify their account to obtain administrator-level privileges, maintain persistence, and move laterally within the environment.\ @@ -1088,7 +1110,7 @@ version = 1 references = ["https://blog.rapid7.com/2020/04/02/dispelling-zoom-bugbears-what-you-need-to-know-about-the-latest-zoom-vulnerabilities/", "https://threatpost.com/two-zoom-zero-day-flaws-uncovered/154337/"] maintainers = [{"company": "Splunk", "email": "-", "name": "David Dorsey"}] spec_version = 3 -searches = ["ESCU - First Time Seen Child Process of Zoom - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Get Process File Activity - Response Task"] +searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - First Time Seen Child Process of Zoom - Rule", "ESCU - Get Process File Activity - Response Task"] description = Attackers are using Zoom as an vector to increase privileges on a sytems. This story detects new child processes of zoom and provides investigative actions for this detection. narrative = Zoom is a leader in modern enterprise video communications and its usage has increased dramatically with a large amount of the population under stay-at-home orders due to the COVID-19 pandemic. With increased usage has come increased scrutiny and several security flaws have been found with this application on both Windows and macOS systems.\ Current detections focus on finding new child processes of this application on a per host basis. Investigative searches are included to gather information needed during an investigation. @@ -1100,7 +1122,7 @@ version = 1 references = ["https://attack.mitre.org/techniques/T1127/", "https://github.com/redcanaryco/atomic-red-team/blob/master/atomics/T1218/T1218.md", "https://lolbas-project.github.io/lolbas/Binaries/Microsoft.Workflow.Compiler/"] maintainers = [{"company": "Splunk", "email": "-", "name": "Michael Haag"}] spec_version = 3 -searches = ["ESCU - Suspicious microsoft workflow compiler usage - Rule", "ESCU - Suspicious microsoft workflow compiler rename - Rule"] +searches = ["ESCU - Suspicious microsoft workflow compiler rename - Rule", "ESCU - Suspicious microsoft workflow compiler usage - Rule"] description = Monitor and detect behaviors used by attackers who leverage trusted developer utilities to execute malicious code. narrative = Adversaries may take advantage of trusted developer utilities to proxy execution of malicious payloads. There are many utilities used for software development related tasks that can be used to execute code in various forms to assist in development, debugging, and reverse engineering. These utilities may often be signed with legitimate certificates that allow them to execute on a system and proxy execution of malicious code through a trusted process that effectively bypasses application control solutions.\ The searches in this story help you detect and investigate suspicious activity that may indicate that an adversary is leveraging microsoft.workflow.compiler.exe to execute malicious code. @@ -1112,7 +1134,7 @@ version = 1 references = ["https://attack.mitre.org/techniques/T1127/001/", "https://github.com/redcanaryco/atomic-red-team/blob/master/atomics/T1127.001/T1127.001.md", "https://github.com/infosecn1nja/MaliciousMacroMSBuild", "https://github.com/xorrior/RandomPS-Scripts/blob/master/Invoke-ExecuteMSBuild.ps1", "https://lolbas-project.github.io/lolbas/Binaries/Msbuild/", "https://github.com/MHaggis/CBR-Queries/blob/master/msbuild.md"] maintainers = [{"company": "Splunk", "email": "-", "name": "Michael Haag"}] spec_version = 3 -searches = ["ESCU - Suspicious MSBuild Spawn - Rule", "ESCU - Suspicious MSBuild Rename - Rule", "ESCU - Suspicious msbuild path - Rule"] +searches = ["ESCU - Suspicious msbuild path - Rule", "ESCU - Suspicious MSBuild Rename - Rule", "ESCU - Suspicious MSBuild Spawn - Rule"] description = Monitor and detect techniques used by attackers who leverage the msbuild.exe process to execute malicious code. narrative = Adversaries may use MSBuild to proxy execution of code through a trusted Windows utility. MSBuild.exe (Microsoft Build Engine) is a software build platform used by Visual Studio and is native to Windows. It handles XML formatted project files that define requirements for loading and building various platforms and configurations.\ The inline task capability of MSBuild that was introduced in .NET version 4 allows for C# code to be inserted into an XML project file. MSBuild will compile and execute the inline task. MSBuild.exe is a signed Microsoft binary, so when it is used this way it can execute arbitrary code and bypass application control defenses that are configured to allow MSBuild.exe execution.\ @@ -1136,7 +1158,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = [{"company": "Splunk", "email": "-", "name": "David Dorsey"}] spec_version = 3 -searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - Get Notable History - Response Task", "ESCU - Get EC2 Instance Details by instanceId - Response Task", "ESCU - AWS Investigate User Activities By ARN - Response Task"] +searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get EC2 Instance Details by instanceId - Response Task"] description = Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. narrative = A common attack technique is to infiltrate a cloud instance and make modifications. The adversary can then secure access to your infrastructure or hide their activities. So it's important to stay alert to changes that may indicate that your environment has been compromised. \ Searches within this Analytic Story can help you detect the presence of a threat by monitoring for EC2 instances that have been created or changed--either by users that have never previously performed these activities or by known users who modify or create instances in a way that have not been done before. This story also provides investigative searches that help you go deeper once you detect suspicious behavior. @@ -1148,7 +1170,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] maintainers = [{"company": "Splunk", "email": "-", "name": "Bhavin Patel"}] spec_version = 3 -searches = ["ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Parent Process Info - Response Task"] description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. narrative = Being able to profile a host's processes within your environment can help you more quickly identify processes that seem out of place when compared to the rest of the population of hosts or asset types.\ This Analytic Story lets you identify processes that are either a) not typically seen running or b) have some sort of suspicious command-line arguments associated with them. This Analytic Story will also help you identify the user running these processes and the associated process activity on the host.\ @@ -1172,7 +1194,7 @@ version = 1 references = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] maintainers = [{"company": "Splunk", "email": "-", "name": "Jim Apger"}] spec_version = 3 -searches = ["ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Get Emails From Specific Sender - Response Task", "ESCU - Get Web Session Information via session id - Response Task", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Get Emails From Specific Sender - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Web Session Information via session id - Response Task"] description = Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. narrative = The Federal Bureau of Investigations (FBI) defines Internet fraud as the use of Internet services or software with Internet access to defraud victims or to otherwise take advantage of them. According to the Bureau, Internet crime schemes are used to steal millions of dollars each year from victims and continue to plague the Internet through various methods. The agency includes phishing scams, data breaches, Denial of Service (DOS) attacks, email account compromise, malware, spoofing, and ransomware in this category.\ These crimes are not the fraud itself, but rather the attack techniques commonly employed by fraudsters in their pursuit of data that enables them to commit malicious actssuch as obtaining and using stolen credit cards. They represent a serious problem that is steadily increasing and not likely to go away anytime soon.\ @@ -1188,7 +1210,7 @@ version = 1 references = ["https://research.checkpoint.com/2020/resolving-your-way-into-domain-admin-exploiting-a-17-year-old-bug-in-windows-dns-servers/", "https://support.microsoft.com/en-au/help/4569509/windows-dns-server-remote-code-execution-vulnerability"] maintainers = [{"company": "Splunk", "email": "-", "name": "Shannon Davis"}] spec_version = 3 -searches = ["ESCU - Detect Windows DNS SIGRed via Splunk Stream - Rule", "ESCU - Detect Windows DNS SIGRed via Zeek - Rule", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - Detect Windows DNS SIGRed via Zeek - Rule", "ESCU - Detect Windows DNS SIGRed via Splunk Stream - Rule", "ESCU - Get Notable History - Response Task"] description = Uncover activity consistent with CVE-2020-1350, or SIGRed. Discovered by Checkpoint researchers, this vulnerability affects Windows 2003 to 2019, and is triggered by a malicious DNS response (only affects DNS over TCP). An attacker can use the malicious payload to cause a buffer overflow on the vulnerable system, leading to compromise. The included searches in this Analytic Story are designed to identify the large response payload for SIG and KEY DNS records which can be used for the exploit. narrative = When a client requests a DNS record for a particular domain, that request gets routed first through the client's locally configured DNS server, then to any DNS server(s) configured as forwarders, and then onto the target domain's own DNS server(s). If a attacker wanted to, they could host a malicious DNS server that responds to the initial request with a specially crafted large response (~65KB). This response would flow through to the client's local DNS server, which if not patched for CVE-2020-1350, would cause the buffer overflow. The detection searches in this Analytic Story use wire data to detect the malicious behavior. Searches for Splunk Stream and Zeek are included. The Splunk Stream search correlates across stream:dns and stream:tcp, while the Zeek search correlates across bro:dns:json and bro:conn:json. These correlations are required to pick up both the DNS record types (SIG and KEY) along with the payload size (>65KB). @@ -1199,7 +1221,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Defense_Evasion"] maintainers = [{"company": "Splunk", "email": "-", "name": "David Dorsey"}] spec_version = 3 -searches = ["ESCU - Windows DisableAntiSpyware Registry - Rule", "ESCU - Eventvwr UAC Bypass - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - FodHelper UAC Bypass - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - FodHelper UAC Bypass - Rule", "ESCU - Disabling CMD Application - Rule", "ESCU - Disable Windows SmartScreen Protection - Rule", "ESCU - Eventvwr UAC Bypass - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Disabling Task Manager - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Disabling NoRun Windows App - Rule", "ESCU - Disabling SystemRestore In Registry - Rule", "ESCU - Disable Windows Behavior Monitoring - Rule", "ESCU - Disabling ControlPanel - Rule", "ESCU - Windows DisableAntiSpyware Registry - Rule", "ESCU - Disabling FolderOptions Windows Feature - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Disabling Firewall with Netsh - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Disable Registry Tool - Rule", "ESCU - Disable Show Hidden Files - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Parent Process Info - Response Task"] description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others narrative = Defense evasion is a tactic--identified in the MITRE ATT&CK framework--that adversaries employ in a variety of ways to bypass or defeat defensive security measures. There are many techniques enumerated by the MITRE ATT&CK framework that are applicable in this context. This Analytic Story includes searches designed to identify the use of such techniques on Windows platforms. @@ -1210,7 +1232,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] maintainers = [{"company": "Splunk", "email": "-", "name": "Rico Valdez"}] spec_version = 3 -searches = ["ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Parent Process Info - Response Task"] description = Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. narrative = Attackers use a variety of techniques to entice users to run malicious code or to persist on an endpoint. One way to accomplish these goals is to leverage file extensions and the mechanism Windows uses to associate files with specific applications. \ Since its earliest days, Windows has used extensions to identify file types. Users have become familiar with these extensions and their application associations. For example, if users see that a file ends in `.doc` or `.docx`, they will assume that it is a Microsoft Word document and expect that double-clicking will open it using `winword.exe`. The user will typically also presume that the `.docx` file is safe. \ @@ -1225,7 +1247,7 @@ version = 2 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] maintainers = [{"company": "Splunk", "email": "-", "name": "Rico Valdez"}] spec_version = 3 -searches = ["ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - Windows Event Log Cleared - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Parent Process Info - Response Task"] description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. narrative = Because attackers often modify system logs to cover their tracks and/or to thwart the investigative process, log monitoring is an industry-recognized best practice. While there are legitimate reasons to manipulate system logs, it is still worthwhile to keep track of who manipulated the logs, when they manipulated them, and in what way they manipulated them (determining which accesses, tools, or utilities were employed). Even if no malicious activity is detected, the knowledge of an attempt to manipulate system logs may be indicative of a broader security risk that should be thoroughly investigated.\ The Analytic Story gives users two different ways to detect manipulation of Windows Event Logs and one way to detect deletion of the Update Sequence Number (USN) Change Journal. The story helps determine the history of the host and the users who have accessed it. Finally, the story aides in investigation by retrieving all the information on the process that caused these events (if the process has been identified). @@ -1237,7 +1259,7 @@ version = 2 references = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] maintainers = [{"company": "Splunk", "email": "-", "name": "Bhavin Patel"}] spec_version = 3 -searches = ["ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Suspicious Scheduled Task from Public Directory - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Certutil exe certificate extraction - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Certutil exe certificate extraction - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Suspicious Scheduled Task from Public Directory - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Parent Process Info - Response Task"] description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. narrative = Maintaining persistence is one of the first steps taken by attackers after the initial compromise. Attackers leverage various custom and built-in tools to ensure survivability and persistent access within a compromised enterprise. This Analytic Story provides searches to help you identify various behaviors used by attackers to maintain persistent access to a Windows environment. @@ -1248,7 +1270,7 @@ version = 2 references = ["https://attack.mitre.org/tactics/TA0004/"] maintainers = [{"company": "Splunk", "email": "-", "name": "David Dorsey"}] spec_version = 3 -searches = ["ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Parent Process Info - Response Task"] description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. narrative = Privilege escalation is a "land-and-expand" technique, wherein an adversary gains an initial foothold on a host and then exploits its weaknesses to increase his privileges. The motivation is simple: certain actions on a Windows machine--such as installing software--may require higher-level privileges than those the attacker initially acquired. By increasing his privilege level, the attacker can gain the control required to carry out his malicious ends. This Analytic Story provides searches to detect and investigate behaviors that attackers may use to elevate their privileges in your environment. @@ -1259,7 +1281,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] maintainers = [{"company": "Splunk", "email": "-", "name": "Rico Valdez"}] spec_version = 3 -searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Parent Process Info - Response Task", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - Get Parent Process Info - Response Task"] description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. narrative = The Windows operating system uses a services architecture to allow for running code in the background, similar to a UNIX daemon. Attackers will often leverage Windows services for persistence, hiding in plain sight, seeking the ability to run privileged code that can interact with the kernel. In many cases, attackers will create a new service to host their malicious code. Attackers have also been observed modifying unnecessary or unused services to point to their own code, as opposed to what was intended. In these cases, attackers often use tools to create or modify services in ways that are not typical for most environments, providing opportunities for detection. @@ -1381,6 +1403,16 @@ annotations = {"kill_chain_phases": ["Lateral Movement"]} known_false_positives = Sensitive object access is not necessarily malicious but user and object context can provide guidance for detection. providing_technologies = [] +[savedsearch://ESCU - AWS Excessive Security Scanning - Rule] +type = detection +asset_type = AWS Account +confidence = medium +explanation = This search looks for CloudTrail events and analyse the amount of eventNames which starts with Describe by a single user. This indicates that this user scans the configuration of your AWS cloud environment. +how_to_implement = You must install splunk AWS add on and Splunk App for AWS. This search works with cloudtrail logs. +annotations = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1526"], "nist": ["PR.DS", "PR.AC", "DE.CM"]} +known_false_positives = While this search has no known false positives. +providing_technologies = [] + [savedsearch://ESCU - AWS Network Access Control List Created with All Open Ports - Rule] type = detection asset_type = AWS Instance @@ -1621,6 +1653,26 @@ annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives" known_false_positives = Administrators may modify the boot configuration. providing_technologies = [] +[savedsearch://ESCU - BITS Job Persistence - Rule] +type = detection +asset_type = +confidence = medium +explanation = The following query identifies Microsoft Background Intelligent Transfer Service utility `bitsadmin.exe` scheduling a BITS job to persist on an endpoint. The query identifies the parameters used to create, resume or add a file to a BITS job. Typically seen combined in a oneliner or ran in sequence. If identified, review the BITS job created and capture any files written to disk. It is possible for BITS to be used to upload files and this may require further network data analysis to identify. You can use `bitsadmin /list /verbose` to list out the jobs during investigation. +how_to_implement = To successfully implement this search you need to be ingesting information on process that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` node. +annotations = {"kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1197"]} +known_false_positives = Limited false positives will be present. Typically, applications will use `BitsAdmin.exe`. Any filtering should be done based on command-line arguments (legitimate applications) or parent process. +providing_technologies = [] + +[savedsearch://ESCU - BITSAdmin Download File - Rule] +type = detection +asset_type = +confidence = medium +explanation = The following query identifies Microsoft Background Intelligent Transfer Service utility `bitsadmin.exe` using the `transfer` parameter to download a remote object. In addition, look for `download` or `upload` on the command-line, the switches are not required to perform a transfer. Capture any files downloaded. Review the reputation of the IP or domain used. Typically once executed, a follow on command will be used to execute the dropped file. Note that the network connection or file modification events related will not spawn or create from `bitsadmin.exe`, but the artifacts will appear in a parallel process of `svchost.exe` with a command-line similar to `svchost.exe -k netsvcs -s BITS`. It's important to review all parallel and child processes to capture any behaviors and artifacts. In some suspicious and malicious instances, BITS jobs will be created. You can use `bitsadmin /list /verbose` to list out the jobs during investigation. +how_to_implement = To successfully implement this search you need to be ingesting information on process that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` node. +annotations = {"kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1197", "T1105"]} +known_false_positives = Limited false positives, however it may be required to filter based on parent process name or network connection. +providing_technologies = [] + [savedsearch://ESCU - Batch File Write to System32 - Rule] type = detection asset_type = Endpoint @@ -2002,6 +2054,21 @@ annotations = {"cis20": ["CIS 1", "CIS 3", "CIS 8", "CIS 12"], "kill_chain_phase known_false_positives = Legitimate DNS changes can be detected in this search. Investigate, verify and update the list of provided current answers for the domains in question as appropriate. providing_technologies = [] +[savedsearch://ESCU - DSQuery Domain Discovery - Rule] +type = detection +asset_type = +confidence = medium +explanation = The following analytic identifies "dsquery.exe" execution with arguments looking for `TrustedDomain` query directly on the command-line. This is typically indicative of an Administrator or adversary perform domain trust discovery. Note that this query does not identify any other variations of "Dsquery.exe" usage.\ +Within this detection, it is assumed `dsquery.exe` is not moved or renamed.\ +The search will return the first time and last time these command-line arguments were used for these executions, as well as the target system, the user, process "dsquery.exe" and its parent process.\ +DSQuery.exe is natively found in `C:\Windows\system32` and `C:\Windows\syswow64` and only on Server operating system.\ +The following DLL(s) are loaded when DSQuery.exe is launched `dsquery.dll`. If found loaded by another process, it is possible dsquery is running within that process context in memory.\ +In addition to trust discovery, review parallel processes for additional behaviors performed. Identify the parent process and capture any files (batch files, for example) being used. +how_to_implement = To successfully implement this search you need to be ingesting information on process that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` node. +annotations = {"kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1482"]} +known_false_positives = Limited false positives. If there is a true false positive, filter based on command-line or parent process. +providing_technologies = [] + [savedsearch://ESCU - Deleting Shadow Copies - Rule] type = detection asset_type = Endpoint @@ -2857,6 +2924,96 @@ annotations = {"cis20": ["CIS 3"], "kill_chain_phases": ["Installation", "Action known_false_positives = While legitimate, these NirSoft tools are prone to abuse. You should verfiy that the tool was used for a legitimate purpose. providing_technologies = [] +[savedsearch://ESCU - Disable Registry Tool - Rule] +type = detection +asset_type = +confidence = medium +explanation = This search is to identifies modification of registry to disable the regedit or registry tools of windows operating system. Since registry tool is a swiss knife in analyzing registry, malware such as RAT or trojan Spy disable this application to prevent the removal of their registry entry such as persistence, file less components and defense evasion. +how_to_implement = To successfully implement this search you need to be ingesting information on process that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Registry` node. Also make sure that this registry was included in your config files ex. sysmon config to be monitored. +annotations = {"kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1562.001"]} +known_false_positives = admin may disable this application for non technical user. +providing_technologies = [] + +[savedsearch://ESCU - Disable Show Hidden Files - Rule] +type = detection +asset_type = +confidence = medium +explanation = The following search is to idetifies a modification in registry to prevent the user seeing all the files with hidden attributes. This event or techniques are known on some worm and trojan spy malware that will drop hidden files on the infected machine. +how_to_implement = To successfully implement this search you need to be ingesting information on process that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Registry` node. Also make sure that this registry was included in your config files ex. sysmon config to be monitored. +annotations = {"kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1564.001", "T1562.001"]} +known_false_positives = unknown +providing_technologies = [] + +[savedsearch://ESCU - Disable Windows Behavior Monitoring - Rule] +type = detection +asset_type = +confidence = medium +explanation = This search is to identifies a modification in registry to disable the windows denfender real time behavior monitoring. This event or technique is commonly seen in RAT, bot, or Trojan to disable AV to evade detections. +how_to_implement = To successfully implement this search you need to be ingesting information on process that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Registry` node. Also make sure that this registry was included in your config files ex. sysmon config to be monitored. +annotations = {"kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1562.001"]} +known_false_positives = admin or user may choose to disable this windows features. +providing_technologies = [] + +[savedsearch://ESCU - Disable Windows SmartScreen Protection - Rule] +type = detection +asset_type = +confidence = medium +explanation = The following search identifies a modification of registry to disable the smartscreen protection of windows machine. This is windows feature provide an early warning system against website that might engage in phishing attack or malware distribution. This modification are seen in RAT malware to cover their tracks upon downloading other of its component or other payload. +how_to_implement = To successfully implement this search you need to be ingesting information on process that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Registry` node. Also make sure that this registry was included in your config files ex. sysmon config to be monitored. +annotations = {"kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1562.001"]} +known_false_positives = admin or user may choose to disable this windows features. +providing_technologies = [] + +[savedsearch://ESCU - Disabling CMD Application - Rule] +type = detection +asset_type = +confidence = medium +explanation = this search is to identify modification in registry to disable cmd prompt application. This technique is commonly seen in RAT, Trojan or WORM to prevent triaging or deleting there samples through cmd application which is one of the tool of analyst to traverse on directory and files. +how_to_implement = To successfully implement this search you need to be ingesting information on process that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Registry` node. Also make sure that this registry was included in your config files ex. sysmon config to be monitored. +annotations = {"kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1562.001"]} +known_false_positives = admin may disable this application for non technical user. +providing_technologies = [] + +[savedsearch://ESCU - Disabling ControlPanel - Rule] +type = detection +asset_type = +confidence = medium +explanation = this search is to identify registry modification to disable control panel window. This technique is commonly seen in malware to prevent their artifacts , persistence removed on the infected machine. +how_to_implement = To successfully implement this search you need to be ingesting information on process that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Registry` node. Also make sure that this registry was included in your config files ex. sysmon config to be monitored. +annotations = {"kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1562.001"]} +known_false_positives = admin may disable this application for non technical user. +providing_technologies = [] + +[savedsearch://ESCU - Disabling Firewall with Netsh - Rule] +type = detection +asset_type = +confidence = medium +explanation = This search is to identifies suspicious firewall disabling using netsh application. this technique is commonly seen in malware that tries to communicate or download its component or other payload to its C2 server. +how_to_implement = You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. +annotations = {"kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1562.001"]} +known_false_positives = admin may disable firewall during testing or fixing network problem. +providing_technologies = [] + +[savedsearch://ESCU - Disabling FolderOptions Windows Feature - Rule] +type = detection +asset_type = +confidence = medium +explanation = This search is to identify registry modification to disable folder options feature of windows to show hidden files, file extension and etc. This technique used by malware in combination if disabling show hidden files feature to hide their files and also to hide the file extension to lure the user base on file icons or fake file extensions. +how_to_implement = To successfully implement this search you need to be ingesting information on process that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Registry` node. Also make sure that this registry was included in your config files ex. sysmon config to be monitored. +annotations = {"kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1562.001"]} +known_false_positives = admin may disable this application for non technical user. +providing_technologies = [] + +[savedsearch://ESCU - Disabling NoRun Windows App - Rule] +type = detection +asset_type = +confidence = medium +explanation = This search is to identify modification of registry to disable run application in window start menu. this application is known to be a helpful shortcut to windows OS user to run known application and also to execute some reg or batch script. This technique is used malware to make cleaning of its infection more harder by preventing known application run easily through run shortcut. +how_to_implement = To successfully implement this search you need to be ingesting information on process that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Registry` node. Also make sure that this registry was included in your config files ex. sysmon config to be monitored. +annotations = {"kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1562.001"]} +known_false_positives = admin may disable this application for non technical user. +providing_technologies = [] + [savedsearch://ESCU - Disabling Remote User Account Control - Rule] type = detection asset_type = Endpoint @@ -2867,6 +3024,26 @@ annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives" known_false_positives = This registry key may be modified via administrators to implement a change in system policy. This type of change should be a very rare occurrence. providing_technologies = [] +[savedsearch://ESCU - Disabling SystemRestore In Registry - Rule] +type = detection +asset_type = +confidence = medium +explanation = The following search identifies the modification of registry related in disabling the system restore of a machine. This event or behavior are seen in some RAT malware to make the restore of the infected machine difficult and keep their infection on the box. +how_to_implement = To successfully implement this search you need to be ingesting information on process that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Registry` node. Also make sure that this registry was included in your config files ex. sysmon config to be monitored. +annotations = {"kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1562.001"]} +known_false_positives = in some cases admin can disable systemrestore on a machine. +providing_technologies = [] + +[savedsearch://ESCU - Disabling Task Manager - Rule] +type = detection +asset_type = +confidence = medium +explanation = This search is to identifies modification of registry to disable the task manager of windows operating system. this event or technique are commonly seen in malware such as RAT, Trojan, TrojanSpy or worm to prevent the user to terminate their process. +how_to_implement = To successfully implement this search you need to be ingesting information on process that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Registry` node. Also make sure that this registry was included in your config files ex. sysmon config to be monitored. +annotations = {"kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1562.001"]} +known_false_positives = admin may disable this application for non technical user. +providing_technologies = [] + [savedsearch://ESCU - Dump LSASS via comsvcs DLL - Rule] type = detection asset_type = Endpoint @@ -3475,6 +3652,16 @@ annotations = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Comm known_false_positives = These characters might be legitimately on the command-line, but it is not common. providing_technologies = [] +[savedsearch://ESCU - Malicious Powershell Executed As A Service - Rule] +type = detection +asset_type = +confidence = medium +explanation = This detection is to identify the abuse the Windows SC.exe to execute malicious commands or payloads via PowerShell. +how_to_implement = To successfully implement this search, you need to be ingesting Windows System logs with the Service name, Service File Name Service Start type, and Service Type from your endpoints. +annotations = {"kill_chain_phases": ["Privilege Escalation"], "mitre_attack": ["T1569.002"]} +known_false_positives = Creating a hidden powershell service is rare and could key off of those instances. +providing_technologies = [] + [savedsearch://ESCU - Monitor DNS For Brand Abuse - Rule] type = detection asset_type = Endpoint @@ -3747,6 +3934,16 @@ annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives" known_false_positives = Microsoft may provide updates to these binaries. Verify that these changes do not correspond with your normal software update cycle. providing_technologies = [] +[savedsearch://ESCU - PowerShell Start-BitsTransfer - Rule] +type = detection +asset_type = +confidence = medium +explanation = Start-BitsTransfer is the PowerShell "version" of BitsAdmin.exe. Similar functionality is present. This technique variation is not as commonly used by adversaries, but has been abused in the past. Lesser known uses include the ability to set the `-TransferType` to `Upload` for exfiltration of files. In an instance where `Upload` is used, it is highly possible files will be archived. During triage, review parallel processes and process lineage. Capture any files on disk and review. For the remote domain or IP, what is the reputation? +how_to_implement = To successfully implement this search you need to be ingesting information on process that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` node. +annotations = {"kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1197"]} +known_false_positives = Limited false positives. It is possible administrators will utilize Start-BitsTransfer for administrative tasks, otherwise filter based parent process or command-line arguments. +providing_technologies = [] + [savedsearch://ESCU - Process Creating LNK file in Suspicious Location - Rule] type = detection asset_type = Endpoint diff --git a/dist/escu/lookups/mitre_enrichment.csv b/dist/escu/lookups/mitre_enrichment.csv index 0717cbc6ba..49fac5e18b 100644 --- a/dist/escu/lookups/mitre_enrichment.csv +++ b/dist/escu/lookups/mitre_enrichment.csv @@ -1,5 +1,107 @@ mitre_id,technique,tactics,groups -T1205.001,Port Knocking,Defense Evasion|Persistence|Command And Control,no +T1484.002,Domain Trust Modification,Defense Evasion|Privilege Escalation,UNC2452 +T1484.001,Group Policy Modification,Defense Evasion|Privilege Escalation,no +T1606.002,SAML Tokens,Credential Access,UNC2452 +T1606.001,Web Cookies,Credential Access,UNC2452 +T1606,Forge Web Credentials,Credential Access,no +T1059.008,Network Device CLI,Execution,no +T1602.002,Network Device Configuration Dump,Collection,no +T1542.005,TFTP Boot,Defense Evasion|Persistence,no +T1542.004,ROMMONkit,Defense Evasion|Persistence,no +T1602.001,SNMP (MIB Dump),Collection,no +T1602,Data from Configuration Repository,Collection,no +T1601.002,Downgrade System Image,Defense Evasion,no +T1601.001,Patch System Image,Defense Evasion,no +T1601,Modify System Image,Defense Evasion,no +T1600.002,Disable Crypto Hardware,Defense Evasion,no +T1600.001,Reduce Key Space,Defense Evasion,no +T1600,Weaken Encryption,Defense Evasion,no +T1556.004,Network Device Authentication,Credential Access|Defense Evasion,no +T1599.001,Network Address Translation Traversal,Defense Evasion,no +T1599,Network Boundary Bridging,Defense Evasion,no +T1020.001,Traffic Duplication,Exfiltration,no +T1557.002,ARP Cache Poisoning,Credential Access|Collection,Cleaver +T1588.006,Vulnerabilities,Resource Development,no +T1053.006,Systemd Timers,Execution|Persistence|Privilege Escalation,no +T1562.008,Disable Cloud Logs,Defense Evasion,no +T1547.012,Print Processors,Persistence|Privilege Escalation,no +T1598.003,Spearphishing Link,Reconnaissance,no +T1598.002,Spearphishing Attachment,Reconnaissance,no +T1598.001,Spearphishing Service,Reconnaissance,no +T1598,Phishing for Information,Reconnaissance,no +T1597.002,Purchase Technical Data,Reconnaissance,no +T1597.001,Threat Intel Vendors,Reconnaissance,no +T1597,Search Closed Sources,Reconnaissance,no +T1596.005,Scan Databases,Reconnaissance,no +T1596.004,CDNs,Reconnaissance,no +T1596.003,Digital Certificates,Reconnaissance,no +T1596.001,DNS/Passive DNS,Reconnaissance,no +T1596.002,WHOIS,Reconnaissance,no +T1596,Search Open Technical Databases,Reconnaissance,no +T1595.002,Vulnerability Scanning,Reconnaissance,no +T1595.001,Scanning IP Blocks,Reconnaissance,no +T1595,Active Scanning,Reconnaissance,no +T1594,Search Victim-Owned Websites,Reconnaissance,no +T1593.002,Search Engines,Reconnaissance,no +T1593.001,Social Media,Reconnaissance,no +T1593,Search Open Websites/Domains,Reconnaissance,no +T1592.004,Client Configurations,Reconnaissance,no +T1592.003,Firmware,Reconnaissance,no +T1592.002,Software,Reconnaissance,no +T1592.001,Hardware,Reconnaissance,no +T1592,Gather Victim Host Information,Reconnaissance,no +T1591.004,Identify Roles,Reconnaissance,no +T1591.003,Identify Business Tempo,Reconnaissance,no +T1591.001,Determine Physical Locations,Reconnaissance,no +T1591.002,Business Relationships,Reconnaissance,no +T1591,Gather Victim Org Information,Reconnaissance,no +T1590.006,Network Security Appliances,Reconnaissance,no +T1590.005,IP Addresses,Reconnaissance,no +T1590.004,Network Topology,Reconnaissance,no +T1590.003,Network Trust Dependencies,Reconnaissance,no +T1590.002,DNS,Reconnaissance,no +T1590.001,Domain Properties,Reconnaissance,no +T1590,Gather Victim Network Information,Reconnaissance,no +T1589.003,Employee Names,Reconnaissance,no +T1589.002,Email Addresses,Reconnaissance,no +T1589.001,Credentials,Reconnaissance,no +T1589,Gather Victim Identity Information,Reconnaissance,no +T1588.005,Exploits,Resource Development,no +T1588.004,Digital Certificates,Resource Development,no +T1588.003,Code Signing Certificates,Resource Development,Wizard Spider +T1588.002,Tool,Resource Development,no +T1588.001,Malware,Resource Development,Turla|APT1 +T1588,Obtain Capabilities,Resource Development,no +T1587.004,Exploits,Resource Development,no +T1587.003,Digital Certificates,Resource Development,APT29|PROMETHIUM +T1587.002,Code Signing Certificates,Resource Development,PROMETHIUM|Patchwork +T1587.001,Malware,Resource Development,UNC2452|Turla|FIN7|Night Dragon|Cleaver +T1587,Develop Capabilities,Resource Development,no +T1586.002,Email Accounts,Resource Development,no +T1586.001,Social Media Accounts,Resource Development,no +T1586,Compromise Accounts,Resource Development,no +T1585.002,Email Accounts,Resource Development,APT1 +T1585.001,Social Media Accounts,Resource Development,Cleaver +T1585,Establish Accounts,Resource Development,APT17 +T1584.006,Web Services,Resource Development,Turla +T1584.005,Botnet,Resource Development,no +T1584.004,Server,Resource Development,Turla|APT16 +T1584.003,Virtual Private Server,Resource Development,Turla +T1584.002,DNS Server,Resource Development,no +T1584.001,Domains,Resource Development,APT1 +T1583.006,Web Services,Resource Development,APT17|APT29 +T1583.005,Botnet,Resource Development,no +T1583.004,Server,Resource Development,no +T1583.003,Virtual Private Server,Resource Development,TEMP.Veles +T1583.002,DNS Server,Resource Development,no +T1584,Compromise Infrastructure,Resource Development,no +T1583.001,Domains,Resource Development,APT1|APT28 +T1583,Acquire Infrastructure,Resource Development,no +T1564.007,VBA Stomping,Defense Evasion,no +T1558.004,AS-REP Roasting,Credential Access,no +T1580,Cloud Infrastructure Discovery,Discovery,no +T1218.012,Verclsid,Defense Evasion,no +T1205.001,Port Knocking,Defense Evasion|Persistence|Command And Control,PROMETHIUM T1564.006,Run Virtual Instance,Defense Evasion,no T1564.005,Hidden File System,Defense Evasion,Strider|Equation T1556.003,Pluggable Authentication Modules,Credential Access|Defense Evasion,no @@ -7,7 +109,7 @@ T1574.012,COR_PROFILER,Persistence|Privilege Escalation|Defense Evasion,Blue Moc T1562.007,Disable or Modify Cloud Firewall,Defense Evasion,no T1098.004,SSH Authorized Keys,Persistence,no T1480.001,Environmental Keying,Defense Evasion,APT41|Equation -T1059.007,JavaScript/JScript,Execution,APT32|FIN7|Cobalt Group|Molerats|TA505|Silence|Leafminer +T1059.007,JavaScript/JScript,Execution,FIN6|APT32|FIN7|Cobalt Group|Molerats|TA505|Silence|Leafminer T1578.004,Revert Cloud Instance,Defense Evasion,no T1578.003,Delete Cloud Instance,Defense Evasion,no T1578.001,Create Snapshot,Defense Evasion,no @@ -24,31 +126,31 @@ T1546.015,Component Object Model Hijacking,Privilege Escalation|Persistence,APT2 T1071.004,DNS,Command And Control,APT39|Tropic Trooper|OilRig|Ke3chang|Cobalt Group|APT18|APT41|FIN7 T1071.003,Mail Protocols,Command And Control,APT32|SilverTerrier|APT28 T1071.002,File Transfer Protocols,Command And Control,APT41|SilverTerrier|Machete|Honeybee -T1071.001,Web Protocols,Command And Control,Sandworm Team|TA505|Rocke|APT39|Tropic Trooper|MuddyWater|Wizard Spider|Inception|APT41|SilverTerrier|Machete|APT28|WIRTE|APT33|FIN4|Night Dragon|APT18|APT38|Cobalt Group|APT19|Threat Group-3390|Rancor|Orangeworm|APT37|Ke3chang|Dark Caracal|Turla|Lazarus Group|BRONZE BUTLER|APT32|OilRig|Magic Hound|Gamaredon Group|Stealth Falcon +T1071.001,Web Protocols,Command And Control,UNC2452|Sandworm Team|TA505|Rocke|APT39|Tropic Trooper|MuddyWater|Wizard Spider|Inception|APT41|SilverTerrier|Machete|APT28|WIRTE|APT33|FIN4|Night Dragon|APT18|APT38|Threat Group-3390|Ke3chang|Dark Caracal|APT19|Cobalt Group|Rancor|Orangeworm|APT37|Turla|Lazarus Group|APT32|Magic Hound|BRONZE BUTLER|OilRig|Gamaredon Group|Stealth Falcon T1572,Protocol Tunneling,Command And Control,OilRig|Cobalt Group|FIN6 -T1048.003,Exfiltration Over Unencrypted/Obfuscated Non-C2 Protocol,Exfiltration,APT32|APT33|Thrip|FIN8|OilRig|Lazarus Group -T1048.002,Exfiltration Over Asymmetric Encrypted Non-C2 Protocol,Exfiltration,no +T1048.003,Exfiltration Over Unencrypted/Obfuscated Non-C2 Protocol,Exfiltration,Wizard Spider|FIN6|APT32|APT33|Thrip|FIN8|OilRig|Lazarus Group +T1048.002,Exfiltration Over Asymmetric Encrypted Non-C2 Protocol,Exfiltration,UNC2452 T1048.001,Exfiltration Over Symmetric Encrypted Non-C2 Protocol,Exfiltration,no T1001.003,Protocol Impersonation,Command And Control,Lazarus Group -T1001.002,Steganography,Command And Control,Axiom +T1001.002,Steganography,Command And Control,APT29|Axiom T1001.001,Junk Data,Command And Control,APT28 T1132.002,Non-Standard Encoding,Command And Control,no T1132.001,Standard Encoding,Command And Control,Sandworm Team|Tropic Trooper|MuddyWater|APT33|APT19|Lazarus Group|BRONZE BUTLER|Patchwork T1090.004,Domain Fronting,Command And Control,APT29 T1090.003,Multi-hop Proxy,Command And Control,Inception|FIN4|APT29 T1090.002,External Proxy,Command And Control,APT39|Silence|Soft Cell|MuddyWater|APT3|FIN5|Lazarus Group|menuPass|APT28 -T1090.001,Internal Proxy,Command And Control,APT39|Strider +T1090.001,Internal Proxy,Command And Control,UNC2452|APT39|Strider T1102.003,One-Way Communication,Command And Control,Leviathan -T1102.002,Bidirectional Communication,Command And Control,Sandworm Team|APT39|APT12|Turla|FIN7|APT37|Magic Hound|Carbanak +T1102.002,Bidirectional Communication,Command And Control,APT29|Sandworm Team|APT39|APT12|Turla|FIN7|APT37|Magic Hound|Carbanak T1102.001,Dead Drop Resolver,Command And Control,Rocke|APT41|BRONZE BUTLER|RTM|Patchwork T1571,Non-Standard Port,Command And Control,Sandworm Team|Rocke|DarkVishnya|Silence|APT-C-36|Magic Hound|APT33|APT32|TEMP.Veles|Lazarus Group|FIN7 -T1074.002,Remote Data Staging,Collection,Threat Group-3390|menuPass|FIN6|Night Dragon|FIN8 -T1074.001,Local Data Staging,Collection,Machete|Soft Cell|TEMP.Veles|Patchwork|Dragonfly 2.0|Honeybee|Leviathan|APT3|FIN5|menuPass|FIN6|Lazarus Group|Threat Group-3390|APT28 +T1074.002,Remote Data Staging,Collection,UNC2452|Threat Group-3390|menuPass|FIN6|Night Dragon|FIN8 +T1074.001,Local Data Staging,Collection,Machete|Soft Cell|TEMP.Veles|Honeybee|Dragonfly 2.0|Patchwork|Leviathan|APT3|FIN5|menuPass|Lazarus Group|Threat Group-3390|APT28 T1078.004,Cloud Accounts,Defense Evasion|Persistence|Privilege Escalation|Initial Access,APT33 T1564.004,NTFS File Attributes,Defense Evasion,APT32 T1564.003,Hidden Window,Defense Evasion,Gorgon Group|Deep Panda|DarkHydrus|CopyKittens|APT19|APT32|APT28|APT3|Magic Hound -T1078.003,Local Accounts,Defense Evasion|Persistence|Privilege Escalation|Initial Access,Tropic Trooper|FIN10|Stolen Pencil|APT32 -T1078.002,Domain Accounts,Defense Evasion|Persistence|Privilege Escalation|Initial Access,TA505|APT3|Threat Group-1314 +T1078.003,Local Accounts,Defense Evasion|Persistence|Privilege Escalation|Initial Access,PROMETHIUM|Tropic Trooper|FIN10|Stolen Pencil|APT32 +T1078.002,Domain Accounts,Defense Evasion|Persistence|Privilege Escalation|Initial Access,Wizard Spider|APT29|TA505|APT3|Threat Group-1314 T1078.001,Default Accounts,Defense Evasion|Persistence|Privilege Escalation|Initial Access,no T1564.002,Hidden Users,Defense Evasion,no T1574.006,LD_PRELOAD,Persistence|Privilege Escalation|Defense Evasion,Rocke @@ -64,37 +166,37 @@ T1574,Hijack Execution Flow,Persistence|Privilege Escalation|Defense Evasion,no T1069.001,Local Groups,Discovery,Turla|OilRig|admin@338 T1570,Lateral Tool Transfer,Lateral Movement,APT32|Wizard Spider|Turla|FIN10 T1568.003,DNS Calculation,Command And Control,APT12 -T1204.002,Malicious File,Execution,Magic Hound|Windshift|APT33|Sandworm Team|Naikon|Whitefly|Tropic Trooper|Gamaredon Group|Sharpshooter|Molerats|Wizard Spider|Mofang|Frankenstein|RTM|Inception|BlackTech|APT-C-36|Machete|admin@338|APT12|TA505|Silence|The White Company|APT39|FIN4|Darkhotel|Gallmaker|APT19|Dragonfly 2.0|BRONZE BUTLER|Cobalt Group|DarkHydrus|Gorgon Group|Patchwork|OilRig|Dark Caracal|MuddyWater|Lazarus Group|FIN7|APT32|Rancor|APT37|FIN8|APT28|Elderwood|TA459|APT29|Leviathan|menuPass|PLATINUM -T1204.001,Malicious Link,Execution,Patchwork|Windshift|APT32|Molerats|Mofang|BlackTech|TA505|OilRig|Machete|Leviathan|FIN8|FIN4|Elderwood|Dragonfly 2.0|Cobalt Group|APT39|Night Dragon|APT33|Turla +T1204.002,Malicious File,Execution,FIN6|PROMETHIUM|APT30|Magic Hound|Windshift|APT33|Sandworm Team|Naikon|Whitefly|Tropic Trooper|Gamaredon Group|Sharpshooter|Molerats|Wizard Spider|Mofang|Frankenstein|RTM|Inception|BlackTech|APT-C-36|Machete|admin@338|APT12|TA505|Silence|The White Company|APT39|FIN4|Darkhotel|Gallmaker|Dragonfly 2.0|Dark Caracal|FIN7|APT32|Cobalt Group|DarkHydrus|Patchwork|Rancor|MuddyWater|BRONZE BUTLER|APT19|Gorgon Group|OilRig|Lazarus Group|APT29|menuPass|TA459|FIN8|Elderwood|PLATINUM|Leviathan|APT37|APT28 +T1204.001,Malicious Link,Execution,Wizard Spider|Patchwork|Windshift|APT32|Molerats|Mofang|BlackTech|TA505|OilRig|Machete|Leviathan|FIN8|FIN4|Elderwood|Dragonfly 2.0|Cobalt Group|APT39|Night Dragon|APT33|Turla T1195.003,Compromise Hardware Supply Chain,Initial Access,no -T1195.002,Compromise Software Supply Chain,Initial Access,Sandworm Team|APT41 +T1195.002,Compromise Software Supply Chain,Initial Access,UNC2452|GOLD SOUTHFIELD|Dragonfly|Sandworm Team|APT41 T1195.001,Compromise Software Dependencies and Development Tools,Initial Access,no -T1568.001,Fast Flux DNS,Command And Control,TA505 +T1568.001,Fast Flux DNS,Command And Control,Machete|TA505 T1052.001,Exfiltration over USB,Exfiltration,Tropic Trooper -T1569.002,Service Execution,Execution,Blue Mockingbird|APT39|APT41|Silence|FIN6|APT32|Honeybee|Ke3chang +T1569.002,Service Execution,Execution,Wizard Spider|Blue Mockingbird|APT39|APT41|Silence|FIN6|APT32|Ke3chang|Honeybee T1569.001,Launchctl,Execution,no T1569,System Services,Execution,no T1568.002,Domain Generation Algorithms,Command And Control,APT41 -T1568,Dynamic Resolution,Command And Control,no +T1568,Dynamic Resolution,Command And Control,UNC2452 T1011.001,Exfiltration Over Bluetooth,Exfiltration,no T1567.002,Exfiltration to Cloud Storage,Exfiltration,Leviathan|Turla T1567.001,Exfiltration to Code Repository,Exfiltration,no -T1059.006,Python,Execution,Rocke|BRONZE BUTLER|APT39|Dragonfly 2.0|Machete -T1059.005,Visual Basic,Execution,APT33|Sandworm Team|Gamaredon Group|Sharpshooter|Molerats|Frankenstein|Inception|APT-C-36|Rancor|Patchwork|MuddyWater|Honeybee|FIN7|APT37|BRONZE BUTLER|APT32|Turla|TA505|Silence|WIRTE|FIN4|Cobalt Group|Gorgon Group|Leviathan|TA459|Magic Hound +T1059.006,Python,Execution,APT29|Rocke|BRONZE BUTLER|APT39|Dragonfly 2.0|Machete +T1059.005,Visual Basic,Execution,Lazarus Group|APT33|Sandworm Team|Gamaredon Group|Sharpshooter|Molerats|Frankenstein|Inception|APT-C-36|Rancor|Patchwork|MuddyWater|Honeybee|FIN7|APT37|BRONZE BUTLER|APT32|Turla|TA505|Silence|WIRTE|FIN4|Gorgon Group|Cobalt Group|Leviathan|TA459|Magic Hound T1059.004,Unix Shell,Execution,Rocke|APT41 -T1059.003,Windows Command Shell,Execution,TA505|Blue Mockingbird|Tropic Trooper|Frankenstein|OilRig|Lazarus Group|Honeybee|Cobalt Group|FIN7|APT41|Soft Cell|Turla|Silence|APT32|APT39|Darkhotel|MuddyWater|APT18|APT38|Dark Caracal|Gorgon Group|Dragonfly 2.0|Rancor|Ke3chang|APT37|Leviathan|FIN8|APT28|Magic Hound|Sowbug|BRONZE BUTLER|FIN10|Threat Group-3390|menuPass|Gamaredon Group|Suckfly|Patchwork|Threat Group-1314|APT3|admin@338|APT1 +T1059.003,Windows Command Shell,Execution,UNC2452|Wizard Spider|FIN6|TA505|Blue Mockingbird|Tropic Trooper|Frankenstein|OilRig|Lazarus Group|Honeybee|Cobalt Group|FIN7|APT41|Soft Cell|Turla|Silence|APT32|Darkhotel|MuddyWater|APT18|APT38|Gorgon Group|Ke3chang|Dragonfly 2.0|Rancor|Dark Caracal|APT37|APT28|Leviathan|FIN8|Sowbug|Magic Hound|BRONZE BUTLER|menuPass|Threat Group-3390|FIN10|Gamaredon Group|Patchwork|Suckfly|Threat Group-1314|APT3|admin@338|APT1 T1059.002,AppleScript,Execution,no -T1059.001,PowerShell,Execution,Blue Mockingbird|APT39|DarkVishnya|Molerats|Wizard Spider|Frankenstein|Inception|Silence|APT41|Kimsuky|Soft Cell|TA505|WIRTE|TEMP.Veles|APT33|Gallmaker|Turla|APT19|DarkHydrus|APT28|Thrip|Gorgon Group|Cobalt Group|Dragonfly 2.0|Leviathan|TA459|FIN8|MuddyWater|Magic Hound|OilRig|BRONZE BUTLER|CopyKittens|APT32|FIN7|FIN10|Threat Group-3390|menuPass|Patchwork|Stealth Falcon|FIN6|Poseidon Group|APT3|APT29|Deep Panda +T1059.001,PowerShell,Execution,UNC2452|Lazarus Group|Chimera|Blue Mockingbird|APT39|DarkVishnya|Molerats|Wizard Spider|Frankenstein|Inception|Silence|APT41|Kimsuky|Soft Cell|TA505|WIRTE|TEMP.Veles|APT33|Gallmaker|Turla|APT19|DarkHydrus|APT28|Gorgon Group|Thrip|Cobalt Group|Dragonfly 2.0|Leviathan|TA459|MuddyWater|FIN8|Magic Hound|CopyKittens|BRONZE BUTLER|OilRig|FIN10|Threat Group-3390|APT32|FIN7|menuPass|Patchwork|Stealth Falcon|FIN6|Poseidon Group|APT3|APT29|Deep Panda T1567,Exfiltration Over Web Service,Exfiltration,no T1497.003,Time Based Evasion,Defense Evasion|Discovery,no T1497.002,User Activity Based Checks,Defense Evasion|Discovery,FIN7 T1497.001,System Checks,Defense Evasion|Discovery,Frankenstein T1498.002,Reflection Amplification,Impact,no T1498.001,Direct Network Flood,Impact,no -T1566.003,Spearphishing via Service,Initial Access,Magic Hound|Windshift|FIN6|OilRig|Dark Caracal -T1566.002,Spearphishing Link,Initial Access,Windshift|Molerats|Mofang|BlackTech|Machete|Kimsuky|TA505|Stolen Pencil|APT39|FIN4|APT32|Night Dragon|Turla|APT28|Cobalt Group|Dragonfly 2.0|OilRig|APT33|Elderwood|Leviathan|Magic Hound|Patchwork|APT29|FIN8 -T1566.001,Spearphishing Attachment,Initial Access,Magic Hound|Windshift|APT33|Sandworm Team|Naikon|Gamaredon Group|Sharpshooter|Molerats|Mofang|Wizard Spider|RTM|Frankenstein|Inception|BlackTech|APT-C-36|APT41|Machete|admin@338|Kimsuky|APT12|TA505|Silence|The White Company|APT39|FIN4|Darkhotel|Gallmaker|Tropic Trooper|Turla|Gorgon Group|Rancor|DarkHydrus|Cobalt Group|FIN7|OilRig|Lazarus Group|APT19|Dragonfly 2.0|BRONZE BUTLER|APT32|FIN8|MuddyWater|APT28|TA459|Leviathan|Patchwork|PLATINUM|Elderwood|APT29|APT37|menuPass -T1566,Phishing,Initial Access,no +T1566.003,Spearphishing via Service,Initial Access,Lazarus Group|Magic Hound|Windshift|FIN6|OilRig|Dark Caracal +T1566.002,Spearphishing Link,Initial Access,Wizard Spider|APT1|Windshift|Molerats|Mofang|BlackTech|Machete|Kimsuky|TA505|Stolen Pencil|APT39|FIN4|APT32|Night Dragon|APT28|Cobalt Group|Dragonfly 2.0|Turla|OilRig|APT33|Leviathan|Patchwork|Elderwood|APT29|Magic Hound|FIN8 +T1566.001,Spearphishing Attachment,Initial Access,APT1|FIN6|APT30|Magic Hound|Windshift|APT33|Sandworm Team|Naikon|Gamaredon Group|Sharpshooter|Molerats|Mofang|Wizard Spider|RTM|Frankenstein|Inception|BlackTech|APT-C-36|APT41|Machete|admin@338|Kimsuky|APT12|TA505|Silence|The White Company|APT39|FIN4|Darkhotel|Gallmaker|Tropic Trooper|Turla|Lazarus Group|Cobalt Group|FIN7|OilRig|BRONZE BUTLER|APT32|Gorgon Group|Rancor|DarkHydrus|APT19|Dragonfly 2.0|FIN8|PLATINUM|MuddyWater|TA459|Leviathan|Elderwood|APT29|APT37|menuPass|APT28|Patchwork +T1566,Phishing,Initial Access,GOLD SOUTHFIELD|Dragonfly T1565.003,Runtime Data Manipulation,Impact,APT38 T1565.002,Transmitted Data Manipulation,Impact,APT38 T1565.001,Stored Data Manipulation,Impact,FIN4|APT38 @@ -104,18 +206,18 @@ T1564,Hide Artifacts,Defense Evasion,no T1563.002,RDP Hijacking,Lateral Movement,no T1563.001,SSH Hijacking,Lateral Movement,no T1563,Remote Service Session Hijacking,Lateral Movement,no -T1518.001,Security Software Discovery,Discovery,Turla|Rocke|Frankenstein|The White Company|Cobalt Group|Darkhotel|MuddyWater|Tropic Trooper|FIN8|Patchwork|Naikon +T1518.001,Security Software Discovery,Discovery,Wizard Spider|Turla|Rocke|Frankenstein|The White Company|Cobalt Group|Darkhotel|MuddyWater|Tropic Trooper|FIN8|Patchwork|Naikon T1069.003,Cloud Groups,Discovery,no T1069.002,Domain Groups,Discovery,Turla|Wizard Spider|Inception|OilRig|FIN6|Dragonfly 2.0|Ke3chang T1087.004,Cloud Account,Discovery,no T1087.003,Email Account,Discovery,Sandworm Team|TA505 -T1087.002,Domain Account,Discovery,Turla|Sandworm Team|Dragonfly 2.0|OilRig|BRONZE BUTLER|menuPass|FIN6|Poseidon Group|Ke3chang +T1087.002,Domain Account,Discovery,Wizard Spider|Chimera|Turla|Sandworm Team|Dragonfly 2.0|OilRig|BRONZE BUTLER|menuPass|FIN6|Poseidon Group|Ke3chang T1087.001,Local Account,Discovery,Turla|Poseidon Group|OilRig|Ke3chang|APT32|APT1|Threat Group-3390|APT3|admin@338 T1553.004,Install Root Certificate,Defense Evasion,no -T1562.004,Disable or Modify System Firewall,Defense Evasion,Rocke|Lazarus Group|Kimsuky|Dragonfly 2.0|Carbanak -T1562.003,HISTCONTROL,Defense Evasion,no -T1562.002,Disable Windows Event Logging,Defense Evasion,Threat Group-3390 -T1562.001,Disable or Modify Tools,Defense Evasion,Gamaredon Group|BRONZE BUTLER|Rocke|Kimsuky|Turla|Night Dragon|Gorgon Group|Lazarus Group|Putter Panda +T1562.004,Disable or Modify System Firewall,Defense Evasion,UNC2452|Rocke|Lazarus Group|Kimsuky|Dragonfly 2.0|Carbanak +T1562.003,Impair Command History Logging,Defense Evasion,no +T1562.002,Disable Windows Event Logging,Defense Evasion,UNC2452|Threat Group-3390 +T1562.001,Disable or Modify Tools,Defense Evasion,UNC2452|Wizard Spider|FIN6|Gamaredon Group|BRONZE BUTLER|Rocke|Kimsuky|Turla|Night Dragon|Gorgon Group|Lazarus Group|Putter Panda T1562,Impair Defenses,Defense Evasion,no T1003.004,LSA Secrets,Credential Access,OilRig|MuddyWater|menuPass|Leafminer|Ke3chang|Dragonfly 2.0|APT33|Threat Group-3390 T1003.005,Cached Domain Credentials,Credential Access,OilRig|MuddyWater|Leafminer|APT33 @@ -124,8 +226,8 @@ T1561.001,Disk Content Wipe,Impact,Lazarus Group T1561,Disk Wipe,Impact,no T1560.003,Archive via Custom Method,Collection,Lazarus Group|Kimsuky|CopyKittens|FIN6 T1560.002,Archive via Library,Collection,Lazarus Group|Threat Group-3390 -T1560.001,Archive via Utility,Collection,APT41|Soft Cell|Turla|Gallmaker|APT33|APT39|MuddyWater|Magic Hound|FIN8|BRONZE BUTLER|CopyKittens|APT3|Sowbug|menuPass|APT1|Ke3chang -T1560,Archive Collected Data,Collection,menuPass|APT32|Honeybee|Patchwork|APT28|Dragonfly 2.0|FIN6|Lazarus Group|Ke3chang +T1560.001,Archive via Utility,Collection,UNC2452|Chimera|APT41|Soft Cell|Turla|Gallmaker|APT33|APT39|MuddyWater|Magic Hound|FIN8|BRONZE BUTLER|CopyKittens|Sowbug|APT3|menuPass|APT1|Ke3chang +T1560,Archive Collected Data,Collection,menuPass|APT32|Patchwork|APT28|Dragonfly 2.0|Honeybee|FIN6|Lazarus Group|Ke3chang T1499.004,Application or System Exploitation,Impact,no T1499.003,Application Exhaustion Flood,Impact,no T1499.002,Service Exhaustion Flood,Impact,no @@ -133,7 +235,7 @@ T1499.001,OS Exhaustion Flood,Impact,no T1491.002,External Defacement,Impact,no T1491.001,Internal Defacement,Impact,Lazarus Group T1114.003,Email Forwarding Rule,Collection,no -T1114.002,Remote Email Collection,Collection,APT1|FIN4|APT28|Dragonfly 2.0|Ke3chang|Leafminer +T1114.002,Remote Email Collection,Collection,UNC2452|APT1|FIN4|Ke3chang|Leafminer|Dragonfly 2.0|APT28 T1114.001,Local Email Collection,Collection,Magic Hound|APT1 T1134.005,SID-History Injection,Defense Evasion|Privilege Escalation,no T1134.004,Parent PID Spoofing,Defense Evasion|Privilege Escalation,no @@ -142,93 +244,93 @@ T1134.002,Create Process with Token,Defense Evasion|Privilege Escalation,Turla|L T1134.001,Token Impersonation/Theft,Defense Evasion|Privilege Escalation,APT28 T1213.002,Sharepoint,Collection,Ke3chang|APT28 T1213.001,Confluence,Collection,no -T1555.003,Credentials from Web Browsers,Credential Access,Magic Hound|Sandworm Team|Inception|Stealth Falcon|OilRig|Leafminer|APT33|APT3|Kimsuky|TA505|Stolen Pencil|MuddyWater|APT37|Patchwork|Molerats +T1555.003,Credentials from Web Browsers,Credential Access,FIN6|Magic Hound|Sandworm Team|Inception|Stealth Falcon|OilRig|Leafminer|APT33|APT3|Kimsuky|TA505|Stolen Pencil|MuddyWater|APT37|Patchwork|Molerats T1555.002,Securityd Memory,Credential Access,no T1555.001,Keychain,Credential Access,no -T1559.002,Dynamic Data Exchange,Execution,Sharpshooter|TA505|MuddyWater|Gallmaker|Patchwork|Cobalt Group|APT37|APT28|FIN7 +T1559.002,Dynamic Data Exchange,Execution,Sharpshooter|TA505|MuddyWater|Gallmaker|Cobalt Group|Patchwork|APT37|FIN7|APT28 T1559.001,Component Object Model,Execution,Gamaredon Group|MuddyWater T1559,Inter-Process Communication,Execution,no T1558.002,Silver Ticket,Credential Access,no T1558.001,Golden Ticket,Credential Access,Ke3chang T1558,Steal or Forge Kerberos Tickets,Credential Access,no -T1557.001,LLMNR/NBT-NS Poisoning and SMB Relay,Credential Access|Collection,no +T1557.001,LLMNR/NBT-NS Poisoning and SMB Relay,Credential Access|Collection,Wizard Spider T1557,Man-in-the-Middle,Credential Access|Collection,no T1556.002,Password Filter DLL,Credential Access|Defense Evasion,Strider -T1556.001,Domain Controller Authentication,Credential Access|Defense Evasion,no +T1556.001,Domain Controller Authentication,Credential Access|Defense Evasion,Chimera T1556,Modify Authentication Process,Credential Access|Defense Evasion,no T1056.004,Credential API Hooking,Collection|Credential Access,PLATINUM T1056.003,Web Portal Capture,Collection|Credential Access,no T1056.002,GUI Input Capture,Collection|Credential Access,FIN4 -T1056.001,Keylogging,Collection|Credential Access,APT32|Sandworm Team|APT39|APT41|Kimsuky|menuPass|Stolen Pencil|FIN4|APT38|Ke3chang|OilRig|PLATINUM|Sowbug|Magic Hound|Group5|Lazarus Group|Threat Group-3390|APT3|Darkhotel|APT28 -T1555,Credentials from Password Stores,Credential Access,APT39|OilRig|MuddyWater|Leafminer|APT33|Turla|Stealth Falcon +T1056.001,Keylogging,Collection|Credential Access,APT32|Sandworm Team|APT39|APT41|Kimsuky|menuPass|Stolen Pencil|FIN4|APT38|OilRig|Ke3chang|PLATINUM|Sowbug|Magic Hound|Group5|Lazarus Group|Threat Group-3390|APT3|Darkhotel|APT28 +T1555,Credentials from Password Stores,Credential Access,UNC2452|FIN6|APT39|OilRig|MuddyWater|Leafminer|APT33|Turla|Stealth Falcon T1552.005,Cloud Instance Metadata API,Credential Access,no T1003.008,/etc/passwd and /etc/shadow,Credential Access,no T1003.007,Proc Filesystem,Credential Access,no -T1003.006,DCSync,Credential Access,no -T1558.003,Kerberoasting,Credential Access,no +T1003.006,DCSync,Credential Access,UNC2452 +T1558.003,Kerberoasting,Credential Access,UNC2452|Wizard Spider T1552.006,Group Policy Preferences,Credential Access,APT33 -T1003.003,NTDS,Credential Access,FIN6|Dragonfly 2.0 -T1003.002,Security Account Manager,Credential Access,Threat Group-3390|Ke3chang|Soft Cell|Night Dragon|Dragonfly 2.0|menuPass -T1003.001,LSASS Memory,Credential Access,Sandworm Team|Whitefly|Blue Mockingbird|Silence|Threat Group-3390|Leviathan|APT41|Soft Cell|TEMP.Veles|APT33|APT39|Stolen Pencil|APT32|Lazarus Group|Leafminer|Magic Hound|MuddyWater|PLATINUM|FIN8|BRONZE BUTLER|OilRig|FIN6|APT3|APT28|APT1|Ke3chang|Cleaver +T1003.003,NTDS,Credential Access,Wizard Spider|Chimera|FIN6|Dragonfly 2.0 +T1003.002,Security Account Manager,Credential Access,Wizard Spider|Threat Group-3390|Ke3chang|Soft Cell|Night Dragon|Dragonfly 2.0|menuPass +T1003.001,LSASS Memory,Credential Access,Sandworm Team|Whitefly|Blue Mockingbird|Silence|Threat Group-3390|Leviathan|APT41|Soft Cell|TEMP.Veles|APT33|APT39|Stolen Pencil|APT32|Leafminer|Lazarus Group|Magic Hound|MuddyWater|FIN8|PLATINUM|OilRig|BRONZE BUTLER|FIN6|APT3|APT28|APT1|Ke3chang|Cleaver T1110.004,Credential Stuffing,Credential Access,no -T1110.003,Password Spraying,Credential Access,APT33|Leafminer|Lazarus Group -T1110.002,Password Cracking,Credential Access,APT41|Dragonfly 2.0|APT3 -T1110.001,Password Guessing,Credential Access,no -T1021.006,Windows Remote Management,Lateral Movement,Threat Group-3390 +T1110.003,Password Spraying,Credential Access,APT28|APT33|Leafminer|Lazarus Group +T1110.002,Password Cracking,Credential Access,FIN6|APT41|Dragonfly 2.0|APT3 +T1110.001,Password Guessing,Credential Access,APT28 +T1021.006,Windows Remote Management,Lateral Movement,UNC2452|Wizard Spider|Threat Group-3390 T1021.005,VNC,Lateral Movement,GCMAN T1021.004,SSH,Lateral Movement,Rocke|TEMP.Veles|Leviathan|APT39|OilRig|menuPass|GCMAN T1021.003,Distributed Component Object Model,Lateral Movement,no -T1021.002,SMB/Windows Admin Shares,Lateral Movement,Blue Mockingbird|APT39|APT32|Orangeworm|FIN8|APT3|Lazarus Group|Threat Group-1314|Turla|Deep Panda|Ke3chang -T1021.001,Remote Desktop Protocol,Lateral Movement,Blue Mockingbird|Wizard Spider|Silence|APT41|TEMP.Veles|Leviathan|APT39|Stolen Pencil|Cobalt Group|Dragonfly 2.0|FIN8|APT3|OilRig|menuPass|FIN10|Patchwork|FIN6|Lazarus Group|APT1|Axiom +T1021.002,SMB/Windows Admin Shares,Lateral Movement,Wizard Spider|Chimera|Blue Mockingbird|APT39|APT32|Orangeworm|FIN8|APT3|Lazarus Group|Threat Group-1314|Turla|Deep Panda|Ke3chang +T1021.001,Remote Desktop Protocol,Lateral Movement,Chimera|Blue Mockingbird|Wizard Spider|Silence|APT41|TEMP.Veles|Leviathan|APT39|Stolen Pencil|Cobalt Group|Dragonfly 2.0|FIN8|APT3|OilRig|FIN10|menuPass|Patchwork|FIN6|Lazarus Group|APT1|Axiom T1554,Compromise Client Software Binary,Persistence,no T1036.006,Space after Filename,Defense Evasion,no -T1036.005,Match Legitimate Name or Location,Defense Evasion,Rocke|Sandworm Team|APT39|Blue Mockingbird|Whitefly|Tropic Trooper|Silence|APT41|menuPass|TEMP.Veles|MuddyWater|BRONZE BUTLER|Sowbug|APT32|Patchwork|Poseidon Group|admin@338|Carbanak|APT1 -T1036.004,Masquerade Task or Service,Defense Evasion,Wizard Spider|APT-C-36|Carbanak|APT32|FIN6|FIN7 +T1036.005,Match Legitimate Name or Location,Defense Evasion,UNC2452|Chimera|PROMETHIUM|Rocke|Sandworm Team|APT39|Blue Mockingbird|Whitefly|Tropic Trooper|Silence|APT41|menuPass|TEMP.Veles|MuddyWater|BRONZE BUTLER|Sowbug|APT32|Patchwork|Poseidon Group|admin@338|Carbanak|APT1 +T1036.004,Masquerade Task or Service,Defense Evasion,UNC2452|Lazarus Group|PROMETHIUM|Wizard Spider|APT-C-36|Carbanak|APT32|FIN6|FIN7 T1036.003,Rename System Utilities,Defense Evasion,menuPass|APT32|Soft Cell|PLATINUM T1036.002,Right-to-Left Override,Defense Evasion,BRONZE BUTLER|BlackTech|Ke3chang|Scarlet Mimic -T1036.001,Invalid Code Signature,Defense Evasion,Windshift +T1036.001,Invalid Code Signature,Defense Evasion,Windshift|APT37 T1553.003,SIP and Trust Provider Hijacking,Defense Evasion,no -T1553.002,Code Signing,Defense Evasion,Patchwork|Silence|APT41|FIN6|TA505|FIN7|Honeybee|Leviathan|APT37|CopyKittens|Winnti Group|Suckfly|Molerats|Darkhotel +T1553.002,Code Signing,Defense Evasion,UNC2452|Wizard Spider|PROMETHIUM|Patchwork|Silence|APT41|FIN6|TA505|FIN7|Honeybee|Leviathan|CopyKittens|Winnti Group|Suckfly|Molerats|Darkhotel T1553.001,Gatekeeper Bypass,Defense Evasion,no T1553,Subvert Trust Controls,Defense Evasion,no T1027.003,Steganography,Defense Evasion,BRONZE BUTLER|Tropic Trooper|MuddyWater|APT37 -T1027.002,Software Packing,Defense Evasion,TA505|Rocke|Soft Cell|The White Company|APT39|APT38|Dark Caracal|Elderwood|APT3|Patchwork|APT29|Night Dragon -T1027.001,Binary Padding,Defense Evasion,Gamaredon Group|Patchwork|APT32|Leviathan|BRONZE BUTLER|Moafee +T1027.002,Software Packing,Defense Evasion,Lazarus Group|TA505|Rocke|Soft Cell|The White Company|APT39|APT38|Dark Caracal|Elderwood|APT3|Patchwork|APT29|Night Dragon +T1027.001,Binary Padding,Defense Evasion,Gamaredon Group|APT32|Patchwork|Leviathan|BRONZE BUTLER|Moafee T1222.002,Linux and Mac File and Directory Permissions Modification,Defense Evasion,Rocke|APT32 -T1222.001,Windows File and Directory Permissions Modification,Defense Evasion,no -T1552.004,Private Keys,Credential Access,Rocke +T1222.001,Windows File and Directory Permissions Modification,Defense Evasion,Wizard Spider +T1552.004,Private Keys,Credential Access,UNC2452|Rocke T1552.003,Bash History,Credential Access,no T1552.002,Credentials in Registry,Credential Access,APT32 T1552.001,Credentials In Files,Credential Access,Leafminer|APT33|OilRig|TA505|Stolen Pencil|MuddyWater|APT3 T1552,Unsecured Credentials,Credential Access,no T1216.001,PubPrn,Defense Evasion,APT32 -T1070.006,Timestomp,Defense Evasion,Rocke|TEMP.Veles|APT32|Lazarus Group|APT28 +T1070.006,Timestomp,Defense Evasion,UNC2452|Rocke|TEMP.Veles|APT32|Lazarus Group|APT28 T1070.005,Network Share Connection Removal,Defense Evasion,Threat Group-3390 -T1070.004,File Deletion,Defense Evasion,Sandworm Team|Rocke|Tropic Trooper|Gamaredon Group|Wizard Spider|APT41|Kimsuky|Silence|The White Company|TEMP.Veles|APT32|APT38|Patchwork|Honeybee|Cobalt Group|Dragonfly 2.0|menuPass|FIN8|OilRig|FIN5|BRONZE BUTLER|Magic Hound|APT3|FIN10|APT28|Threat Group-3390|Group5|Lazarus Group|APT18|APT29 +T1070.004,File Deletion,Defense Evasion,UNC2452|FIN6|Sandworm Team|Rocke|Tropic Trooper|Gamaredon Group|Wizard Spider|APT41|Kimsuky|Silence|The White Company|TEMP.Veles|APT32|APT38|Honeybee|Patchwork|Cobalt Group|Dragonfly 2.0|menuPass|FIN8|BRONZE BUTLER|FIN5|APT3|OilRig|Magic Hound|FIN10|APT28|Threat Group-3390|Group5|Lazarus Group|APT18|APT29 T1070.003,Clear Command History,Defense Evasion,APT41 -T1550.004,Web Session Cookie,Defense Evasion|Lateral Movement,no +T1550.004,Web Session Cookie,Defense Evasion|Lateral Movement,UNC2452 T1550.001,Application Access Token,Defense Evasion|Lateral Movement,APT28 T1550.003,Pass the Ticket,Defense Evasion|Lateral Movement,APT32|BRONZE BUTLER|APT29 T1550.002,Pass the Hash,Defense Evasion|Lateral Movement,Soft Cell|APT32|Night Dragon|APT28|APT1 -T1550,Use Alternate Authentication Material,Defense Evasion|Lateral Movement,no +T1550,Use Alternate Authentication Material,Defense Evasion|Lateral Movement,UNC2452 T1548.004,Elevated Execution with Prompt,Privilege Escalation|Defense Evasion,no T1548.003,Sudo and Sudo Caching,Privilege Escalation|Defense Evasion,no -T1548.002,Bypass User Access Control,Privilege Escalation|Defense Evasion,APT37|MuddyWater|Honeybee|Cobalt Group|Threat Group-3390|BRONZE BUTLER|Patchwork|APT29 +T1548.002,Bypass User Account Control,Privilege Escalation|Defense Evasion,APT37|MuddyWater|Honeybee|Cobalt Group|Threat Group-3390|BRONZE BUTLER|Patchwork|APT29 T1548.001,Setuid and Setgid,Privilege Escalation|Defense Evasion,no T1548,Abuse Elevation Control Mechanism,Privilege Escalation|Defense Evasion,no T1136.003,Cloud Account,Persistence,no T1070.002,Clear Linux or Mac System Logs,Defense Evasion,Rocke T1070.001,Clear Windows Event Logs,Defense Evasion,APT41|APT38|Dragonfly 2.0|APT32|FIN8|FIN5|APT28 T1136.002,Domain Account,Persistence,Soft Cell -T1136.001,Local Account,Persistence,APT39|APT41|Dragonfly 2.0|Leafminer|APT3 +T1136.001,Local Account,Persistence,APT39|APT41|Leafminer|Dragonfly 2.0|APT3 T1547.011,Plist Modification,Persistence|Privilege Escalation,no T1547.010,Port Monitors,Persistence|Privilege Escalation,no T1547.009,Shortcut Modification,Persistence|Privilege Escalation,APT39|Darkhotel|APT29|Gorgon Group|Dragonfly 2.0|Leviathan|Lazarus Group T1547.008,LSASS Driver,Persistence|Privilege Escalation,no T1547.007,Re-opened Applications,Persistence|Privilege Escalation,no T1547.006,Kernel Modules and Extensions,Persistence|Privilege Escalation,no -T1547.005,Security Support Provider,Persistence|Privilege Escalation,no -T1547.004,Winlogon Helper DLL,Persistence|Privilege Escalation,Tropic Trooper|Turla +T1547.005,Security Support Provider,Persistence|Privilege Escalation,Lazarus Group +T1547.004,Winlogon Helper DLL,Persistence|Privilege Escalation,Wizard Spider|Tropic Trooper|Turla T1547.003,Time Providers,Persistence|Privilege Escalation,no T1546.014,Emond,Privilege Escalation|Persistence,no T1546.013,PowerShell Profile,Privilege Escalation|Persistence,Turla @@ -244,30 +346,30 @@ T1546.007,Netsh Helper DLL,Privilege Escalation|Persistence,no T1546.006,LC_LOAD_DYLIB Addition,Privilege Escalation|Persistence,no T1546.005,Trap,Privilege Escalation|Persistence,no T1546.004,.bash_profile and .bashrc,Privilege Escalation|Persistence,no -T1546.003,Windows Management Instrumentation Event Subscription,Privilege Escalation|Persistence,APT33|Blue Mockingbird|Turla|Leviathan|APT29 +T1546.003,Windows Management Instrumentation Event Subscription,Privilege Escalation|Persistence,UNC2452|APT33|Blue Mockingbird|Turla|Leviathan|APT29 T1546.002,Screensaver,Privilege Escalation|Persistence,no T1546.001,Change Default File Association,Privilege Escalation|Persistence,Kimsuky -T1547.001,Registry Run Keys / Startup Folder,Persistence|Privilege Escalation,Rocke|Tropic Trooper|Gamaredon Group|Sharpshooter|Molerats|Silence|RTM|Inception|APT41|Machete|Kimsuky|APT33|APT39|APT32|APT18|Turla|Dark Caracal|Cobalt Group|Honeybee|Threat Group-3390|Dragonfly 2.0|Gorgon Group|Ke3chang|APT19|Leviathan|MuddyWater|APT37|BRONZE BUTLER|Magic Hound|APT3|FIN10|FIN7|Patchwork|FIN6|Lazarus Group|Putter Panda|APT29|Darkhotel +T1547.001,Registry Run Keys / Startup Folder,Persistence|Privilege Escalation,Wizard Spider|PROMETHIUM|Rocke|Tropic Trooper|Gamaredon Group|Sharpshooter|Molerats|Silence|RTM|Inception|APT41|Machete|Kimsuky|APT33|APT39|APT32|APT18|Turla|Dark Caracal|Cobalt Group|Honeybee|APT19|Ke3chang|Threat Group-3390|Dragonfly 2.0|Gorgon Group|MuddyWater|APT37|Leviathan|BRONZE BUTLER|Magic Hound|APT3|FIN10|FIN7|Patchwork|FIN6|Lazarus Group|Putter Panda|APT29|Darkhotel T1218.002,Control Panel,Defense Evasion,no -T1218.010,Regsvr32,Defense Evasion,Blue Mockingbird|Inception|WIRTE|Cobalt Group|APT19|Leviathan|APT32|Deep Panda +T1218.010,Regsvr32,Defense Evasion,Blue Mockingbird|Inception|WIRTE|APT19|Cobalt Group|Leviathan|APT32|Deep Panda T1218.009,Regsvcs/Regasm,Defense Evasion,no -T1218.005,Mshta,Defense Evasion,Inception|Kimsuky|APT32|MuddyWater|FIN7 -T1218.004,InstallUtil,Defense Evasion,no -T1218.001,Compiled HTML File,Defense Evasion,APT41|Silence|Lazarus Group|Dark Caracal|OilRig +T1218.005,Mshta,Defense Evasion,Lazarus Group|Inception|Kimsuky|APT32|MuddyWater|FIN7 +T1218.004,InstallUtil,Defense Evasion,menuPass +T1218.001,Compiled HTML File,Defense Evasion,APT41|Silence|OilRig|Lazarus Group|Dark Caracal T1218.003,CMSTP,Defense Evasion,Cobalt Group|MuddyWater -T1218.011,Rundll32,Defense Evasion,APT32|Sandworm Team|Blue Mockingbird|TA505|MuddyWater|APT29|APT19|CopyKittens|APT3|Carbanak|APT28 +T1218.011,Rundll32,Defense Evasion,UNC2452|Gamaredon Group|APT32|Sandworm Team|Blue Mockingbird|TA505|MuddyWater|APT29|APT19|CopyKittens|APT3|Carbanak|APT28 T1547,Boot or Logon Autostart Execution,Persistence|Privilege Escalation,no T1546,Event Triggered Execution,Privilege Escalation|Persistence,no T1098.003,Add Office 365 Global Administrator Role,Persistence,no -T1098.002,Exchange Email Delegate Permissions,Persistence,Magic Hound -T1098.001,Additional Azure Service Principal Credentials,Persistence,no +T1098.002,Exchange Email Delegate Permissions,Persistence,UNC2452|Magic Hound +T1098.001,Additional Cloud Credentials,Persistence,UNC2452 T1543.004,Launch Daemon,Persistence|Privilege Escalation,no -T1543.003,Windows Service,Persistence|Privilege Escalation,Blue Mockingbird|DarkVishnya|Wizard Spider|APT32|APT41|Kimsuky|Tropic Trooper|Cobalt Group|Ke3chang|Honeybee|FIN7|Threat Group-3390|APT19|APT3|Lazarus Group|Carbanak +T1543.003,Windows Service,Persistence|Privilege Escalation,PROMETHIUM|Blue Mockingbird|DarkVishnya|Wizard Spider|APT32|APT41|Kimsuky|Tropic Trooper|Threat Group-3390|Honeybee|Cobalt Group|Ke3chang|FIN7|APT19|APT3|Lazarus Group|Carbanak T1543.002,Systemd Service,Persistence|Privilege Escalation,Rocke T1543.001,Launch Agent,Persistence|Privilege Escalation,no T1037.005,Startup Items,Persistence|Privilege Escalation,no T1037.004,Rc.common,Persistence|Privilege Escalation,no -T1055.012,Process Hollowing,Defense Evasion|Privilege Escalation,Threat Group-3390|menuPass|Gorgon Group|Patchwork +T1055.012,Process Hollowing,Defense Evasion|Privilege Escalation,menuPass|Gorgon Group|Threat Group-3390|Patchwork T1055.013,Process Doppelgänging,Defense Evasion|Privilege Escalation,Leafminer T1055.011,Extra Window Memory Injection,Defense Evasion|Privilege Escalation,no T1055.014,VDSO Hijacking,Defense Evasion|Privilege Escalation,no @@ -277,7 +379,7 @@ T1055.005,Thread Local Storage,Defense Evasion|Privilege Escalation,no T1055.004,Asynchronous Procedure Call,Defense Evasion|Privilege Escalation,no T1055.003,Thread Execution Hijacking,Defense Evasion|Privilege Escalation,no T1055.002,Portable Executable Injection,Defense Evasion|Privilege Escalation,Rocke|Gorgon Group -T1055.001,Dynamic-link Library Injection,Defense Evasion|Privilege Escalation,TA505|Turla|Tropic Trooper|Lazarus Group|Putter Panda +T1055.001,Dynamic-link Library Injection,Defense Evasion|Privilege Escalation,Wizard Spider|TA505|Turla|Tropic Trooper|Lazarus Group|Putter Panda T1037.003,Network Logon Script,Persistence|Privilege Escalation,no T1543,Create or Modify System Process,Persistence|Privilege Escalation,no T1037.002,Logon Script (Mac),Persistence|Privilege Escalation,no @@ -291,7 +393,7 @@ T1505.001,SQL Stored Procedures,Persistence,no T1053.003,Cron,Execution|Persistence|Privilege Escalation,Rocke T1053.004,Launchd,Execution|Persistence|Privilege Escalation,no T1053.001,At (Linux),Execution|Persistence|Privilege Escalation,no -T1053.005,Scheduled Task,Execution|Persistence|Privilege Escalation,Gamaredon Group|Blue Mockingbird|MuddyWater|Wizard Spider|Frankenstein|APT-C-36|BRONZE BUTLER|APT41|Machete|Soft Cell|Silence|TEMP.Veles|APT33|APT39|Dragonfly 2.0|Patchwork|OilRig|Rancor|Cobalt Group|FIN8|menuPass|FIN10|APT32|FIN7|Stealth Falcon|FIN6|APT3|APT29 +T1053.005,Scheduled Task,Execution|Persistence|Privilege Escalation,UNC2452|Chimera|Gamaredon Group|Blue Mockingbird|MuddyWater|Wizard Spider|Frankenstein|APT-C-36|BRONZE BUTLER|APT41|Machete|Soft Cell|Silence|TEMP.Veles|APT33|APT39|Cobalt Group|OilRig|Rancor|Dragonfly 2.0|Patchwork|FIN8|FIN7|APT32|menuPass|FIN10|Stealth Falcon|FIN6|APT3|APT29 T1053.002,At (Windows),Execution|Persistence|Privilege Escalation,BRONZE BUTLER|Threat Group-3390|APT18 T1542,Pre-OS Boot,Defense Evasion|Persistence,no T1137.001,Office Template Macros,Persistence,MuddyWater @@ -316,52 +418,52 @@ T1526,Cloud Service Discovery,Discovery,no T1505,Server Software Component,Persistence,no T1499,Endpoint Denial of Service,Impact,no T1497,Virtualization/Sandbox Evasion,Defense Evasion|Discovery,no -T1498,Network Denial of Service,Impact,no +T1498,Network Denial of Service,Impact,APT28 T1496,Resource Hijacking,Impact,Blue Mockingbird|Rocke|APT41|Lazarus Group T1495,Firmware Corruption,Impact,no T1491,Defacement,Impact,no T1490,Inhibit System Recovery,Impact,no -T1489,Service Stop,Impact,Lazarus Group +T1489,Service Stop,Impact,Wizard Spider|Lazarus Group T1486,Data Encrypted for Impact,Impact,APT41|TA505|APT38 T1485,Data Destruction,Impact,Sandworm Team|Lazarus Group|APT38 -T1484,Group Policy Modification,Defense Evasion|Privilege Escalation,no -T1482,Domain Trust Discovery,Discovery,Wizard Spider +T1484,Domain Policy Modification,Defense Evasion|Privilege Escalation,no +T1482,Domain Trust Discovery,Discovery,UNC2452|Wizard Spider T1480,Execution Guardrails,Defense Evasion,no +T1220,XSL Script Processing,Defense Evasion,Cobalt Group T1222,File and Directory Permissions Modification,Defense Evasion,no T1221,Template Injection,Defense Evasion,Gamaredon Group|Frankenstein|Inception|APT28|Tropic Trooper|Dragonfly 2.0|DarkHydrus -T1220,XSL Script Processing,Defense Evasion,Cobalt Group -T1197,BITS Jobs,Defense Evasion|Persistence,Patchwork|APT41|Leviathan -T1217,Browser Bookmark Discovery,Discovery,no -T1213,Data from Information Repositories,Collection,Turla -T1189,Drive-by Compromise,Initial Access,Turla|Windshift|RTM|Darkhotel|APT38|Dragonfly 2.0|BRONZE BUTLER|Leafminer|Dark Caracal|APT19|APT32|Lazarus Group|Threat Group-3390|Elderwood|APT37|Patchwork|PLATINUM -T1203,Exploitation for Client Execution,Execution,Sandworm Team|MuddyWater|Frankenstein|Inception|BlackTech|APT41|admin@338|Threat Group-3390|APT12|The White Company|APT33|APT32|APT28|Tropic Trooper|Lazarus Group|BRONZE BUTLER|Cobalt Group|APT37|Patchwork|Leviathan|Elderwood|TA459|APT29 -T1212,Exploitation for Credential Access,Credential Access,no -T1211,Exploitation for Defense Evasion,Defense Evasion,APT28 -T1190,Exploit Public-Facing Application,Initial Access,Blue Mockingbird|Rocke|APT39|BlackTech|APT41|Soft Cell|Night Dragon|Axiom -T1210,Exploitation of Remote Services,Lateral Movement,Threat Group-3390|APT28 -T1202,Indirect Command Execution,Defense Evasion,no +T1203,Exploitation for Client Execution,Execution,Sandworm Team|MuddyWater|Frankenstein|Inception|BlackTech|APT41|admin@338|Threat Group-3390|APT12|The White Company|APT33|APT32|APT28|Tropic Trooper|BRONZE BUTLER|Lazarus Group|Cobalt Group|APT29|Patchwork|Leviathan|APT37|Elderwood|TA459 T1200,Hardware Additions,Initial Access,DarkVishnya -T1201,Password Policy Discovery,Discovery,Turla|OilRig -T1219,Remote Access Software,Command And Control,Sandworm Team|DarkVishnya|RTM|Kimsuky|Night Dragon|Thrip|Cobalt Group|Carbanak +T1202,Indirect Command Execution,Defense Evasion,no +T1213,Data from Information Repositories,Collection,FIN6|Turla T1207,Rogue Domain Controller,Defense Evasion,no -T1199,Trusted Relationship,Initial Access,APT28|menuPass -T1218,Signed Binary Proxy Execution,Defense Evasion,no T1204,User Execution,Execution,no -T1216,Signed Script Proxy Execution,Defense Evasion,no +T1217,Browser Bookmark Discovery,Discovery,no +T1190,Exploit Public-Facing Application,Initial Access,UNC2452|APT28|APT29|GOLD SOUTHFIELD|Blue Mockingbird|Rocke|APT39|BlackTech|APT41|Soft Cell|Night Dragon|Axiom +T1210,Exploitation of Remote Services,Lateral Movement,Wizard Spider|Threat Group-3390|APT28 +T1197,BITS Jobs,Defense Evasion|Persistence,Patchwork|APT41|Leviathan +T1201,Password Policy Discovery,Discovery,Turla|OilRig T1195,Supply Chain Compromise,Initial Access,Elderwood T1205,Traffic Signaling,Defense Evasion|Persistence|Command And Control,no +T1189,Drive-by Compromise,Initial Access,Dragonfly|PROMETHIUM|Turla|Windshift|RTM|Darkhotel|APT38|Lazarus Group|APT32|Dark Caracal|Dragonfly 2.0|BRONZE BUTLER|Leafminer|APT19|Threat Group-3390|APT37|Patchwork|PLATINUM|Elderwood +T1212,Exploitation for Credential Access,Credential Access,no +T1219,Remote Access Software,Command And Control,Sandworm Team|DarkVishnya|RTM|Kimsuky|Night Dragon|Thrip|Cobalt Group|Carbanak +T1211,Exploitation for Defense Evasion,Defense Evasion,APT28 +T1218,Signed Binary Proxy Execution,Defense Evasion,no +T1216,Signed Script Proxy Execution,Defense Evasion,no +T1199,Trusted Relationship,Initial Access,GOLD SOUTHFIELD|APT28|menuPass T1176,Browser Extensions,Persistence,Kimsuky|Stolen Pencil T1175,Component Object Model and Distributed COM,Lateral Movement|Execution,no -T1187,Forced Authentication,Credential Access,DarkHydrus|Dragonfly 2.0 T1185,Man in the Browser,Collection,no -T1134,Access Token Manipulation,Defense Evasion|Privilege Escalation,Blue Mockingbird -T1136,Create Account,Persistence,no -T1140,Deobfuscate/Decode Files or Information,Defense Evasion,Rocke|Sandworm Team|Gamaredon Group|Molerats|Frankenstein|Turla|WIRTE|Darkhotel|Tropic Trooper|menuPass|Honeybee|Threat Group-3390|APT19|Gorgon Group|Leviathan|MuddyWater|APT28|OilRig|BRONZE BUTLER +T1187,Forced Authentication,Credential Access,Dragonfly 2.0|DarkHydrus T1149,LC_MAIN Hijacking,Defense Evasion,no -T1135,Network Share Discovery,Discovery,APT32|APT39|DarkVishnya|APT41|Tropic Trooper|APT1|Dragonfly 2.0|Sowbug +T1136,Create Account,Persistence,no +T1134,Access Token Manipulation,Defense Evasion|Privilege Escalation,FIN6|Blue Mockingbird +T1135,Network Share Discovery,Discovery,Wizard Spider|APT32|APT39|DarkVishnya|APT41|Tropic Trooper|APT1|Dragonfly 2.0|Sowbug +T1140,Deobfuscate/Decode Files or Information,Defense Evasion,UNC2452|Rocke|Sandworm Team|Gamaredon Group|Molerats|Frankenstein|Turla|WIRTE|Darkhotel|Tropic Trooper|menuPass|Threat Group-3390|Gorgon Group|APT19|Honeybee|Leviathan|MuddyWater|APT28|OilRig|BRONZE BUTLER T1137,Office Application Startup,Persistence,Gamaredon Group|APT32 T1153,Source,Execution,no -T1133,External Remote Services,Persistence|Initial Access,Sandworm Team|APT41|Soft Cell|TEMP.Veles|Night Dragon|OilRig|Dragonfly 2.0|Ke3chang|FIN5|Threat Group-3390|APT18 +T1133,External Remote Services,Persistence|Initial Access,Wizard Spider|GOLD SOUTHFIELD|Chimera|Sandworm Team|APT41|Soft Cell|TEMP.Veles|Night Dragon|Ke3chang|OilRig|Dragonfly 2.0|FIN5|Threat Group-3390|APT18 T1132,Data Encoding,Command And Control,no T1129,Shared Modules,Execution,no T1127,Trusted Developer Utilities Proxy Execution,Defense Evasion,no @@ -369,72 +471,72 @@ T1125,Video Capture,Collection,Silence|FIN7 T1124,System Time Discovery,Discovery,The White Company|Lazarus Group|BRONZE BUTLER|Turla T1123,Audio Capture,Collection,APT37 T1120,Peripheral Device Discovery,Discovery,Turla|APT37|Gamaredon Group|Equation|APT28 -T1119,Automated Collection,Collection,Tropic Trooper|Frankenstein|APT1|APT28|Patchwork|OilRig|FIN5|Threat Group-3390|FIN6 +T1119,Automated Collection,Collection,Gamaredon Group|Tropic Trooper|Frankenstein|APT1|APT28|Patchwork|FIN5|OilRig|Threat Group-3390|FIN6 T1115,Clipboard Data,Collection,APT39|APT38 T1114,Email Collection,Collection,no -T1113,Screen Capture,Collection,Gamaredon Group|APT39|Silence|MuddyWater|Dragonfly 2.0|OilRig|Dark Caracal|FIN7|BRONZE BUTLER|Magic Hound|Group5|APT28 -T1112,Modify Registry,Defense Evasion,Gamaredon Group|Blue Mockingbird|Wizard Spider|Silence|APT41|Turla|APT32|APT38|Dragonfly 2.0|APT19|Threat Group-3390|Honeybee|Patchwork|Gorgon Group|FIN8 +T1113,Screen Capture,Collection,Gamaredon Group|APT39|Silence|MuddyWater|OilRig|Dragonfly 2.0|FIN7|Dark Caracal|BRONZE BUTLER|Magic Hound|Group5|APT28 +T1112,Modify Registry,Defense Evasion,Lazarus Group|Gamaredon Group|Blue Mockingbird|Wizard Spider|Silence|APT41|Turla|APT32|APT38|Dragonfly 2.0|Patchwork|APT19|Gorgon Group|Threat Group-3390|Honeybee|FIN8 T1111,Two-Factor Authentication Interception,Credential Access,no T1110,Brute Force,Credential Access,DarkVishnya|APT39|OilRig|FIN5|Turla T1108,Redundant Access,Defense Evasion|Persistence,no -T1106,Native API,Execution,Gamaredon Group|Tropic Trooper|Sharpshooter|Turla|Silence|Gorgon Group|APT37 -T1105,Ingress Tool Transfer,Command And Control,Sandworm Team|Whitefly|Rocke|APT39|Tropic Trooper|Sharpshooter|Molerats|Frankenstein|Silence|APT-C-36|APT41|Soft Cell|TA505|WIRTE|APT33|MuddyWater|APT18|APT38|Rancor|Cobalt Group|Turla|Gorgon Group|OilRig|Dragonfly 2.0|APT37|FIN8|PLATINUM|Leviathan|Elderwood|Magic Hound|APT3|APT32|BRONZE BUTLER|menuPass|FIN7|Gamaredon Group|Patchwork|Lazarus Group|Threat Group-3390|APT28 +T1106,Native API,Execution,Chimera|Gamaredon Group|Tropic Trooper|Sharpshooter|Turla|Silence|APT37|Gorgon Group +T1105,Ingress Tool Transfer,Command And Control,UNC2452|Chimera|Sandworm Team|Whitefly|Rocke|APT39|Tropic Trooper|Sharpshooter|Molerats|Frankenstein|Silence|APT-C-36|APT41|Soft Cell|TA505|WIRTE|APT33|MuddyWater|APT18|APT38|Rancor|OilRig|Dragonfly 2.0|Cobalt Group|Turla|Gorgon Group|APT37|Leviathan|Elderwood|PLATINUM|FIN8|Magic Hound|APT32|APT3|BRONZE BUTLER|menuPass|FIN7|Gamaredon Group|Patchwork|Lazarus Group|Threat Group-3390|APT28 T1104,Multi-Stage Channels,Command And Control,APT41|MuddyWater|APT3 -T1102,Web Service,Command And Control,Gamaredon Group|Rocke|Inception|FIN6 +T1102,Web Service,Command And Control,Chimera|Gamaredon Group|Rocke|Inception|FIN6 T1098,Account Manipulation,Persistence,APT3|Dragonfly 2.0|Lazarus Group -T1095,Non-Application Layer Protocol,Command And Control,APT29|PLATINUM|APT3 +T1095,Non-Application Layer Protocol,Command And Control,FIN6|APT29|PLATINUM|APT3 T1092,Communication Through Removable Media,Command And Control,APT28 T1091,Replication Through Removable Media,Lateral Movement|Initial Access,Tropic Trooper|Darkhotel|APT28 -T1090,Proxy,Command And Control,Sandworm Team|Blue Mockingbird|Wizard Spider|APT41|Turla -T1087,Account Discovery,Discovery,no -T1083,File and Directory Discovery,Discovery,Gamaredon Group|Tropic Trooper|Inception|APT41|Kimsuky|APT32|MuddyWater|APT18|Leafminer|Honeybee|Dark Caracal|Dragonfly 2.0|Magic Hound|Sowbug|BRONZE BUTLER|APT3|APT28|Patchwork|Lazarus Group|Dust Storm|admin@338|Turla|Ke3chang -T1082,System Information Discovery,Discovery,Rocke|Sandworm Team|Blue Mockingbird|Tropic Trooper|Frankenstein|Inception|Kimsuky|Darkhotel|MuddyWater|APT18|Honeybee|APT19|APT37|APT32|Magic Hound|OilRig|APT3|Sowbug|Gamaredon Group|Patchwork|Stealth Falcon|Lazarus Group|admin@338|Turla|Ke3chang -T1080,Taint Shared Content,Lateral Movement,BRONZE BUTLER|Darkhotel -T1078,Valid Accounts,Defense Evasion|Persistence|Privilege Escalation|Initial Access,Sandworm Team|Wizard Spider|Silence|APT41|Soft Cell|TEMP.Veles|APT39|FIN4|Night Dragon|Dragonfly 2.0|FIN8|Leviathan|APT33|OilRig|FIN5|menuPass|APT28|FIN10|Suckfly|FIN6|Threat Group-3390|APT18|PittyTiger|Carbanak +T1090,Proxy,Command And Control,Sandworm Team|Blue Mockingbird|APT41|Turla +T1087,Account Discovery,Discovery,UNC2452 +T1083,File and Directory Discovery,Discovery,UNC2452|Gamaredon Group|Tropic Trooper|Inception|APT41|Kimsuky|APT32|MuddyWater|APT18|Dragonfly 2.0|Leafminer|Honeybee|Dark Caracal|APT3|BRONZE BUTLER|Sowbug|Magic Hound|APT28|Patchwork|Lazarus Group|Dust Storm|admin@338|Turla|Ke3chang +T1082,System Information Discovery,Discovery,UNC2452|Wizard Spider|Rocke|Sandworm Team|Blue Mockingbird|Tropic Trooper|Frankenstein|Inception|Kimsuky|Darkhotel|MuddyWater|APT18|APT37|Honeybee|APT19|APT32|Magic Hound|Sowbug|OilRig|APT3|Gamaredon Group|Patchwork|Stealth Falcon|Lazarus Group|admin@338|Turla|Ke3chang +T1080,Taint Shared Content,Lateral Movement,Gamaredon Group|BRONZE BUTLER|Darkhotel +T1078,Valid Accounts,Defense Evasion|Persistence|Privilege Escalation|Initial Access,UNC2452|Chimera|Sandworm Team|Wizard Spider|Silence|APT41|Soft Cell|TEMP.Veles|APT39|FIN4|Night Dragon|Dragonfly 2.0|Leviathan|APT33|FIN8|FIN5|OilRig|APT28|FIN10|menuPass|Suckfly|FIN6|Threat Group-3390|APT18|PittyTiger|Carbanak T1074,Data Staged,Collection,Wizard Spider T1072,Software Deployment Tools,Execution|Lateral Movement,Silence|APT32|Threat Group-1314 T1071,Application Layer Protocol,Command And Control,Rocke|Magic Hound|Dragonfly 2.0 -T1070,Indicator Removal on Host,Defense Evasion,no -T1069,Permission Groups Discovery,Discovery,TA505|APT3 +T1070,Indicator Removal on Host,Defense Evasion,UNC2452 +T1069,Permission Groups Discovery,Discovery,UNC2452|TA505|APT3 T1068,Exploitation for Privilege Escalation,Privilege Escalation,Whitefly|APT33|Cobalt Group|PLATINUM|FIN8|APT32|Threat Group-3390|FIN6|APT28 T1064,Scripting,Defense Evasion|Execution,no T1062,Hypervisor,Persistence,no T1061,Graphical User Interface,Execution,no -T1059,Command and Scripting Interpreter,Execution,APT32|Molerats|Whitefly|Dragonfly 2.0|APT19|FIN7|OilRig|FIN5|Stealth Falcon|FIN6|Ke3chang -T1057,Process Discovery,Discovery,Rocke|Frankenstein|Inception|Darkhotel|MuddyWater|APT1|APT38|Tropic Trooper|APT37|Honeybee|OilRig|APT3|Magic Hound|APT28|Winnti Group|Stealth Falcon|Poseidon Group|Lazarus Group|Molerats|Turla|Deep Panda|Ke3chang +T1059,Command and Scripting Interpreter,Execution,APT32|Molerats|Whitefly|APT39|APT19|FIN7|Dragonfly 2.0|OilRig|FIN5|Stealth Falcon|FIN6|Ke3chang +T1057,Process Discovery,Discovery,UNC2452|Rocke|Frankenstein|Inception|Darkhotel|MuddyWater|APT1|APT38|Tropic Trooper|APT37|Honeybee|OilRig|APT3|Magic Hound|APT28|Winnti Group|Stealth Falcon|Poseidon Group|Lazarus Group|Molerats|Turla|Deep Panda|Ke3chang T1056,Input Capture,Collection|Credential Access,no -T1055,Process Injection,Defense Evasion|Privilege Escalation,APT32|Sharpshooter|Silence|APT41|Kimsuky|Turla|Cobalt Group|APT37|Honeybee|PLATINUM +T1055,Process Injection,Defense Evasion|Privilege Escalation,APT32|Sharpshooter|Silence|APT41|Kimsuky|Cobalt Group|APT37|Turla|Honeybee|PLATINUM T1053,Scheduled Task/Job,Execution|Persistence|Privilege Escalation,no T1052,Exfiltration Over Physical Medium,Exfiltration,no T1051,Shared Webroot,Lateral Movement,no -T1049,System Network Connections Discovery,Discovery,Tropic Trooper|APT41|APT38|Soft Cell|APT32|APT1|OilRig|APT3|menuPass|Threat Group-3390|Poseidon Group|admin@338|Turla|Ke3chang +T1049,System Network Connections Discovery,Discovery,Tropic Trooper|APT41|APT38|Soft Cell|APT32|APT1|OilRig|APT3|Threat Group-3390|menuPass|Poseidon Group|admin@338|Turla|Ke3chang T1048,Exfiltration Over Alternative Protocol,Exfiltration,no -T1047,Windows Management Instrumentation,Execution,Blue Mockingbird|Wizard Spider|Frankenstein|APT41|FIN6|Soft Cell|APT32|MuddyWater|OilRig|Threat Group-3390|FIN8|Leviathan|menuPass|Stealth Falcon|Lazarus Group|APT29|Deep Panda -T1046,Network Service Scanning,Discovery,Rocke|DarkVishnya|APT41|Tropic Trooper|APT39|APT32|Leafminer|OilRig|Cobalt Group|menuPass|Suckfly|FIN6|Threat Group-3390 -T1043,Commonly Used Port,Command And Control,Machete|OilRig|APT28|TEMP.Veles|Night Dragon|APT29|APT18|APT19|Dragonfly 2.0|FIN7|FIN8|APT37|Magic Hound|APT3|Lazarus Group|Threat Group-3390 +T1047,Windows Management Instrumentation,Execution,UNC2452|Chimera|Blue Mockingbird|Wizard Spider|Frankenstein|APT41|FIN6|Soft Cell|APT32|MuddyWater|OilRig|Threat Group-3390|FIN8|Leviathan|menuPass|Stealth Falcon|Lazarus Group|APT29|Deep Panda +T1046,Network Service Scanning,Discovery,Rocke|DarkVishnya|APT41|Tropic Trooper|APT39|APT32|Cobalt Group|Leafminer|OilRig|menuPass|Suckfly|FIN6|Threat Group-3390 +T1043,Commonly Used Port,Command And Control,OilRig|APT28|TEMP.Veles|Night Dragon|APT29|APT18|FIN7|Dragonfly 2.0|APT19|FIN8|APT37|APT3|Magic Hound|Lazarus Group|Threat Group-3390 T1041,Exfiltration Over C2 Channel,Exfiltration,Sandworm Team|MuddyWater|Wizard Spider|Frankenstein|Kimsuky|Soft Cell|APT32|APT3|Gamaredon Group|Stealth Falcon|Lazarus Group|Ke3chang T1040,Network Sniffing,Credential Access|Discovery,Sandworm Team|DarkVishnya|APT33|Stolen Pencil|APT28 -T1039,Data from Network Shared Drive,Collection,Sowbug|BRONZE BUTLER|menuPass +T1039,Data from Network Shared Drive,Collection,Gamaredon Group|BRONZE BUTLER|Sowbug|menuPass T1037,Boot or Logon Initialization Scripts,Persistence|Privilege Escalation,Rocke -T1036,Masquerading,Defense Evasion,Windshift|APT32|BRONZE BUTLER|menuPass|Dragonfly 2.0 +T1036,Masquerading,Defense Evasion,UNC2452|Windshift|APT32|BRONZE BUTLER|menuPass|Dragonfly 2.0 T1034,Path Interception,Persistence|Privilege Escalation,no -T1033,System Owner/User Discovery,Discovery,Frankenstein|APT41|Soft Cell|Tropic Trooper|APT39|MuddyWater|APT32|APT37|APT19|Dragonfly 2.0|OilRig|Magic Hound|FIN10|Gamaredon Group|Patchwork|Stealth Falcon|Lazarus Group|APT3 +T1033,System Owner/User Discovery,Discovery,Wizard Spider|Frankenstein|APT41|Soft Cell|Tropic Trooper|APT39|MuddyWater|APT32|APT37|APT19|Dragonfly 2.0|OilRig|Magic Hound|FIN10|Gamaredon Group|Patchwork|Stealth Falcon|Lazarus Group|APT3 T1030,Data Transfer Size Limits,Exfiltration,Threat Group-3390 T1029,Scheduled Transfer,Exfiltration,no -T1027,Obfuscated Files or Information,Defense Evasion,Gamaredon Group|Rocke|Sandworm Team|Blue Mockingbird|Whitefly|Molerats|Wizard Spider|Mofang|Frankenstein|Inception|APT-C-36|APT41|Machete|Soft Cell|Turla|TA505|Silence|APT33|Night Dragon|Darkhotel|Gallmaker|APT29|APT18|Tropic Trooper|Cobalt Group|Patchwork|Leafminer|APT37|Threat Group-3390|Honeybee|Dark Caracal|menuPass|APT19|BlackOasis|FIN8|Leviathan|Elderwood|MuddyWater|FIN7|Magic Hound|OilRig|APT3|APT32|Group5|Dust Storm|Lazarus Group|Putter Panda|APT28 +T1027,Obfuscated Files or Information,Defense Evasion,UNC2452|FIN6|Chimera|Gamaredon Group|Rocke|Sandworm Team|Blue Mockingbird|Whitefly|Molerats|Wizard Spider|Mofang|Frankenstein|Inception|APT-C-36|APT41|Machete|Soft Cell|Turla|TA505|Silence|APT33|Night Dragon|Darkhotel|Gallmaker|APT29|APT18|Tropic Trooper|menuPass|Honeybee|Patchwork|Threat Group-3390|APT19|Cobalt Group|Leafminer|APT37|Dark Caracal|FIN8|MuddyWater|FIN7|BlackOasis|Leviathan|Elderwood|OilRig|Magic Hound|APT3|APT32|Group5|Lazarus Group|Dust Storm|Putter Panda|APT28 T1026,Multiband Communication,Command And Control,Lazarus Group T1025,Data from Removable Media,Collection,Machete|Turla|Gamaredon Group|APT28 T1021,Remote Services,Lateral Movement,no -T1020,Automated Exfiltration,Exfiltration,Tropic Trooper|Frankenstein|Honeybee -T1018,Remote System Discovery,Discovery,Sandworm Team|Rocke|Wizard Spider|Silence|Soft Cell|APT39|APT32|Deep Panda|Threat Group-3390|Dragonfly 2.0|Leafminer|Ke3chang|FIN8|APT3|FIN5|BRONZE BUTLER|menuPass|FIN6|Turla -T1016,System Network Configuration Discovery,Discovery,Sandworm Team|Tropic Trooper|Frankenstein|APT41|Soft Cell|APT32|Darkhotel|MuddyWater|APT1|APT19|Dragonfly 2.0|Magic Hound|OilRig|menuPass|Threat Group-3390|Stealth Falcon|Lazarus Group|APT3|Naikon|admin@338|Turla|Ke3chang +T1020,Automated Exfiltration,Exfiltration,Gamaredon Group|Tropic Trooper|Frankenstein|Honeybee +T1018,Remote System Discovery,Discovery,UNC2452|Sandworm Team|Rocke|Wizard Spider|Silence|Soft Cell|APT39|APT32|Threat Group-3390|Dragonfly 2.0|Ke3chang|Leafminer|Deep Panda|FIN8|FIN5|APT3|BRONZE BUTLER|menuPass|FIN6|Turla +T1016,System Network Configuration Discovery,Discovery,Wizard Spider|Sandworm Team|Tropic Trooper|Frankenstein|APT41|Soft Cell|APT32|Darkhotel|MuddyWater|APT1|Dragonfly 2.0|APT19|OilRig|Magic Hound|menuPass|Threat Group-3390|Stealth Falcon|Lazarus Group|APT3|Naikon|admin@338|Turla|Ke3chang T1014,Rootkit,Defense Evasion,Rocke|APT41|APT28|Winnti Group -T1012,Query Registry,Discovery,APT32|Dragonfly 2.0|Threat Group-3390|OilRig|Stealth Falcon|Lazarus Group|Turla +T1012,Query Registry,Discovery,APT32|Threat Group-3390|Dragonfly 2.0|OilRig|Stealth Falcon|Lazarus Group|Turla T1011,Exfiltration Over Other Network Medium,Exfiltration,no T1010,Application Window Discovery,Discovery,Lazarus Group T1008,Fallback Channels,Command And Control,APT41|OilRig|Lazarus Group T1007,System Service Discovery,Discovery,BRONZE BUTLER|APT1|OilRig|Poseidon Group|admin@338|Turla|Ke3chang T1006,Direct Volume Access,Defense Evasion,no -T1005,Data from Local System,Collection,Gamaredon Group|APT39|Frankenstein|Inception|Kimsuky|Soft Cell|Turla|menuPass|Dark Caracal|Dragonfly 2.0|Honeybee|APT37|APT28|APT3|BRONZE BUTLER|Patchwork|Stealth Falcon|Lazarus Group|Dust Storm|Threat Group-3390|APT1|Ke3chang +T1005,Data from Local System,Collection,UNC2452|FIN6|Gamaredon Group|APT39|Frankenstein|Inception|Kimsuky|Soft Cell|Turla|menuPass|Dark Caracal|Dragonfly 2.0|Honeybee|APT28|APT37|APT3|BRONZE BUTLER|Patchwork|Stealth Falcon|Lazarus Group|Dust Storm|Threat Group-3390|APT1|Ke3chang T1003,OS Credential Dumping,Credential Access,APT39|Frankenstein|APT32|APT28|Leviathan|Sowbug|Suckfly|Poseidon Group|Axiom T1001,Data Obfuscation,Command And Control,Axiom diff --git a/dist/saaws/default/analytic_stories.conf b/dist/saaws/default/analytic_stories.conf index 38566e185d..405a6a0303 100644 --- a/dist/saaws/default/analytic_stories.conf +++ b/dist/saaws/default/analytic_stories.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security_content -# On Date: 2021-03-30T19:36:01 UTC +# On Date: 2021-04-12T22:03:03 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -23,6 +23,7 @@ providing_technologies = none description = This analytic story contains detections that query your AWS Cloudtrail for activities related to privilege escalation. narrative = Amazon Web Services provides a neat feature called Identity and Access Management (IAM) that enables organizations to manage various AWS services and resources in a secure way. All IAM users have roles, groups and policies associated with them which governs and sets permissions to allow a user to access specific restrictions.\ However, if these IAM policies are misconfigured and have specific combinations of weak permissions; it can allow attackers to escalate their privileges and further compromise the organization. Rhino Security Labs have published comprehensive blogs detailing various AWS Escalation methods. By using this as an inspiration, Splunk’s research team wants to highlight how these attack vectors look in AWS Cloudtrail logs and provide you with detection queries to uncover these potentially malicious events via this Analytic Story. \ +product = ['Splunk Security Analytics for AWS', 'Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [AWS Network ACL Activity] category = Cloud Security @@ -33,12 +34,13 @@ version = 2 reference = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] detection_searches = ["ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Network Access Control List Deleted - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1562.007"], "nist": ["DE.AE", "DE.DP"]} -investigative_searches = ["ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Get DNS traffic ratio - Response Task", "ESCU - Get DNS Server History for a host - Response Task", "ESCU - AWS Network ACL Details from ID - Response Task", "ESCU - Get Process Responsible For The DNS Traffic - Response Task", "ESCU - Get All AWS Activity From IP Address - Response Task", "ESCU - AWS Network Interface details via resourceId - Response Task", "ESCU - Get Process Information For Port Activity - Response Task"] -support_searches = ["ESCU - Baseline of blocked outbound traffic from AWS", "ESCU - Baseline of Network ACL Activity by ARN"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - AWS Network Interface details via resourceId - Response Task", "ESCU - Get All AWS Activity From IP Address - Response Task", "ESCU - AWS Network ACL Details from ID - Response Task"] +support_searches = [] data_models = [] providing_technologies = none description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and operational/risk auditing of your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Management Console, AWS Command Line Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable to attacks. This analytic story contains detection searches that leverage CloudTrail logs from AWS to check for bad configurations and malicious activity in your AWS network access controls. +product = ['Splunk Security Analytics for AWS', 'Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [AWS Security Hub Alerts] category = Cloud Security @@ -49,12 +51,13 @@ version = 1 reference = ["https://aws.amazon.com/security-hub/features/"] detection_searches = ["ESCU - Detect Spike in AWS Security Hub Alerts for EC2 Instance - Rule"] mappings = {"cis20": ["CIS 13"], "nist": ["DE.AE", "DE.DP"]} -investigative_searches = ["ESCU - Get EC2 Instance Details by instanceId - Response Task", "ESCU - Get EC2 Launch Details - Response Task", "ESCU - AWS Investigate User Activities By ARN - Response Task"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Get EC2 Instance Details by instanceId - Response Task", "ESCU - Get EC2 Launch Details - Response Task"] support_searches = [] data_models = [] providing_technologies = none description = This story is focused around detecting Security Hub alerts generated from AWS narrative = AWS Security Hub collects and consolidates findings from AWS security services enabled in your environment, such as intrusion detection findings from Amazon GuardDuty, vulnerability scans from Amazon Inspector, S3 bucket policy findings from Amazon Macie, publicly accessible and cross-account resources from IAM Access Analyzer, and resources lacking WAF coverage from AWS Firewall Manager. +product = ['Splunk Security Analytics for AWS', 'Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Cloud Cryptomining] category = Cloud Security @@ -65,8 +68,8 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High Number Of Cloud Instances Launched - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created In Previously Unused Region - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078.004", "T1535"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Investigate AWS activities via region name - Response Task", "ESCU - Get EC2 Launch Details - Response Task", "ESCU - Get EC2 Instance Details by instanceId - Response Task", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - AWS Investigate Security Hub alerts by dest - Response Task", "ESCU - Get Notable History - Response Task"] -support_searches = ["ESCU - Baseline Of Cloud Instances Destroyed", "ESCU - Previously Seen Cloud Compute Images - Initial", "ESCU - Previously Seen Cloud Compute Images - Update", "ESCU - Previously Seen Cloud Compute Instance Types - Initial", "ESCU - Previously Seen Cloud Compute Instance Types - Update", "ESCU - Previously Seen Cloud Regions - Initial", "ESCU - Baseline Of Cloud Instances Launched", "ESCU - Previously Seen Cloud Compute Creations By User - Update", "ESCU - Previously Seen Cloud Compute Creations By User - Initial", "ESCU - Previously Seen Cloud Regions - Update"] +investigative_searches = ["ESCU - Get EC2 Instance Details by instanceId - Response Task", "ESCU - Get EC2 Launch Details - Response Task", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - AWS Investigate Security Hub alerts by dest - Response Task", "ESCU - Investigate AWS activities via region name - Response Task"] +support_searches = ["ESCU - Previously Seen Cloud Compute Images - Update", "ESCU - Previously Seen Cloud Compute Instance Types - Initial", "ESCU - Previously Seen Cloud Compute Instance Types - Update", "ESCU - Previously Seen Cloud Compute Images - Initial", "ESCU - Baseline Of Cloud Instances Destroyed", "ESCU - Previously Seen Cloud Regions - Initial", "ESCU - Previously Seen Cloud Regions - Update", "ESCU - Previously Seen Cloud Compute Creations By User - Initial", "ESCU - Baseline Of Cloud Instances Launched", "ESCU - Previously Seen Cloud Compute Creations By User - Update"] data_models = ["Change"] providing_technologies = none description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. @@ -74,6 +77,7 @@ narrative = Cryptomining is an intentionally difficult, resource-intensive busin Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Azure. It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ When malicious miners appropriate a cloud instance, often spinning up hundreds of new instances, the costs can become astronomical for the account holder. So it is critically important to monitor your systems for suspicious activities that could indicate that your network has been infiltrated. \ This Analytic Story is focused on detecting suspicious new instances in your cloud environment to help prevent cryptominers from gaining a foothold. It contains detection searches that will detect when a previously unused instance type or AMI is used. It also contains support searches to build lookup files to ensure proper execution of the detection searches. +product = ['Splunk Security Analytics for AWS', 'Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Cloud Federated Credential Abuse] category = Cloud Security @@ -90,6 +94,7 @@ data_models = [] providing_technologies = none description = This analytical story addresses events that indicate abuse of cloud federated credentials. These credentials are usually extracted from endpoint desktop or servers specially those servers that provide federation services such as Windows Active Directory Federation Services. Identity Federation relies on objects such as Oauth2 tokens, cookies or SAML assertions in order to provide seamless access between cloud and perimeter environments. If these objects are either hijacked or forged then attackers will be able to pivot into victim's cloud environements. narrative = This story is composed of detection searches based on endpoint that addresses the use of Mimikatz, Escalation of Privileges and Abnormal processes that may indicate the extraction of Federated directory objects such as passwords, Oauth2 tokens, certificates and keys. Cloud environment (AWS, Azure) related events are also addressed in specific cloud environment detection searches. +product = ['Splunk Security Analytics for AWS', 'Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Office 365 Detections] category = Cloud Security @@ -106,6 +111,7 @@ data_models = [] providing_technologies = none description = This story is focused around detecting Office 365 Attacks. narrative = More and more companies are using Microsofts Office 365 cloud offering. Therefore, we see more and more attacks against Office 365. This story provides various detections for Office 365 attacks. +product = ['Splunk Security Analytics for AWS', 'Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Ransomware Cloud] category = Malware @@ -116,12 +122,13 @@ version = 1 reference = ["https://rhinosecuritylabs.com/aws/s3-ransomware-part-1-attack-vector/", "https://github.com/d1vious/git-wild-hunt", "https://www.youtube.com/watch?v=PgzNib37g0M"] detection_searches = ["ESCU - AWS Detect Users creating keys with encrypt policy without MFA - Rule", "ESCU - AWS Detect Users with KMS keys performing encryption S3 - Rule"] mappings = {"mitre_attack": ["T1486"]} -investigative_searches = ["ESCU - Get Notable History - Response Task"] +investigative_searches = [] support_searches = [] data_models = [] providing_technologies = none description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware. These searches include cloud related objects that may be targeted by malicious actors via cloud providers own encryption features. narrative = Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise.Cloud ransomware can be deployed by obtaining high privilege credentials from targeted users or resources. +product = ['Splunk Security Analytics for AWS', 'Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Suspicious AWS Login Activities] category = Cloud Security @@ -133,11 +140,12 @@ reference = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integr detection_searches = ["ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule"] mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1535"], "nist": ["DE.AE", "DE.DP"]} investigative_searches = ["ESCU - AWS Investigate User Activities By ARN - Response Task"] -support_searches = ["ESCU - Update previously seen users in CloudTrail", "ESCU - Previously seen users in CloudTrail"] +support_searches = [] data_models = ["Authentication"] providing_technologies = none description = Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. narrative = It is important to monitor and control who has access to your AWS infrastructure. Detecting suspicious logins to your AWS infrastructure will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any EC2 instances created by the attacker. +product = ['Splunk Security Analytics for AWS', 'Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Suspicious AWS S3 Activities] category = Cloud Security @@ -148,14 +156,15 @@ version = 2 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] detection_searches = ["ESCU - Detect New Open S3 Buckets over AWS CLI - Rule", "ESCU - Detect New Open S3 buckets - Rule"] mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1530"], "nist": ["DE.CM", "PR.AC", "PR.DS"]} -investigative_searches = ["ESCU - Investigate AWS activities via region name - Response Task", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - AWS S3 Bucket details via bucketName - Response Task", "ESCU - Get All AWS Activity From IP Address - Response Task", "ESCU - Get Notable History - Response Task"] -support_searches = ["ESCU - Baseline of S3 Bucket deletion activity by ARN", "ESCU - Previously seen S3 bucket access by remote IP"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - AWS S3 Bucket details via bucketName - Response Task", "ESCU - Get All AWS Activity From IP Address - Response Task", "ESCU - Investigate AWS activities via region name - Response Task"] +support_searches = [] data_models = [] providing_technologies = none description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. narrative = As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\ Amazon's "shared responsibility" model dictates that the company has responsibility for the environment outside of the VM and the customer is responsible for the security inside of the S3 container. As such, it's important to stay vigilant for activities that may belie suspicious behavior inside of your environment.\ Among things to look out for are S3 access from unfamiliar locations and by unfamiliar users. Some of the searches in this Analytic Story help you detect suspicious behavior and others help you investigate more deeply, when the situation warrants. +product = ['Splunk Security Analytics for AWS', 'Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Suspicious Cloud Authentication Activities] category = Cloud Security @@ -166,13 +175,14 @@ version = 1 reference = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/", "https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] detection_searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - Detect AWS Console Login by New User - Rule", "ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule"] mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1535"], "nist": ["DE.AE", "DE.DP", "PR.AC", "PR.DS"]} -investigative_searches = ["ESCU - Investigate AWS User Activities by user field - Response Task", "ESCU - Get Notable History - Response Task"] -support_searches = ["ESCU - Previously Seen Users in CloudTrail - Initial", "ESCU - Previously Seen AWS Cross Account Activity - Initial", "ESCU - Previously Seen Users In CloudTrail - Update", "ESCU - Previously Seen AWS Cross Account Activity - Update"] +investigative_searches = ["ESCU - Investigate AWS User Activities by user field - Response Task"] +support_searches = ["ESCU - Previously Seen AWS Cross Account Activity - Update", "ESCU - Previously Seen Users In CloudTrail - Update", "ESCU - Previously Seen Users in CloudTrail - Initial", "ESCU - Previously Seen AWS Cross Account Activity - Initial"] data_models = ["Authentication"] providing_technologies = none description = Monitor your cloud authentication events. Searches within this Analytic Story leverage the recent cloud updates to the Authentication data model to help you stay aware of and investigate suspicious login activity. narrative = It is important to monitor and control who has access to your cloud infrastructure. Detecting suspicious logins will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any compute activity whether legitimate or otherwise.\ This Analytic Story has data model versions of cloud searches leveraging Authentication data, including those looking for suspicious login activity, and cross-account activity for AWS. +product = ['Splunk Security Analytics for AWS', 'Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Suspicious Cloud Instance Activities] category = Cloud Security @@ -183,12 +193,13 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High Number Of Cloud Instances Destroyed - Rule", "ESCU - Abnormally High Number Of Cloud Instances Launched - Rule", "ESCU - Cloud Instance Modified By Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078.004"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get All AWS Activity From IP Address - Response Task", "ESCU - AWS Investigate User Activities By ARN - Response Task"] -support_searches = ["ESCU - Previously Seen Cloud Instance Modifications By User - Initial", "ESCU - Previously Seen Cloud Instance Modifications By User - Update", "ESCU - Baseline Of Cloud Instances Launched", "ESCU - Baseline Of Cloud Instances Destroyed"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Get All AWS Activity From IP Address - Response Task"] +support_searches = ["ESCU - Previously Seen Cloud Instance Modifications By User - Update", "ESCU - Baseline Of Cloud Instances Destroyed", "ESCU - Previously Seen Cloud Instance Modifications By User - Initial", "ESCU - Baseline Of Cloud Instances Launched"] data_models = ["Change"] providing_technologies = none description = Monitor your cloud infrastructure provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your cloud environment. narrative = Monitoring your cloud infrastructure logs allows you enable governance, compliance, and risk auditing. It is crucial for a company to monitor events and actions taken in the their cloud environments to ensure that your instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your cloud compute instances and helps you respond and investigate those activities. +product = ['Splunk Security Analytics for AWS', 'Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Suspicious Cloud Provisioning Activities] category = Cloud Security @@ -199,13 +210,14 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Cloud Provisioning Activity From Previously Unseen City - Rule", "ESCU - Cloud Provisioning Activity From Previously Unseen Country - Rule", "ESCU - Cloud Provisioning Activity From Previously Unseen IP Address - Rule", "ESCU - Cloud Provisioning Activity From Previously Unseen Region - Rule"] mappings = {"cis20": ["CIS 1"], "mitre_attack": ["T1078"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get Notable History - Response Task"] -support_searches = ["ESCU - Previously Seen Cloud Provisioning Activity Sources - Update", "ESCU - Previously Seen Cloud Provisioning Activity Sources - Initial"] +investigative_searches = [] +support_searches = ["ESCU - Previously Seen Cloud Provisioning Activity Sources - Initial", "ESCU - Previously Seen Cloud Provisioning Activity Sources - Update"] data_models = ["Change"] providing_technologies = none description = Monitor your cloud infrastructure provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your cloud environment. narrative = Because most enterprise cloud infrastructure activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where it is impossible to add specific IPs to an allow list because they vary.\ This Analytic Story was designed to provide you with flexibility in the precision you employ in specifying legitimate geographic regions. It can be as specific as an IP address or a city, or as broad as a region (think state) or an entire country. By determining how precise you want your geographical locations to be and monitoring for new locations that haven't previously accessed your environment, you can detect adversaries as they begin to probe your environment. Since there are legitimate reasons for activities from unfamiliar locations, this is not a standalone indicator. Nevertheless, location can be a relevant piece of information that you may wish to investigate further. +product = ['Splunk Security Analytics for AWS', 'Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] [Suspicious Cloud User Activities] category = Cloud Security @@ -217,11 +229,12 @@ reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.p detection_searches = ["ESCU - Abnormally High Number Of Cloud Infrastructure API Calls - Rule", "ESCU - Abnormally High Number Of Cloud Security Group API Calls - Rule", "ESCU - Cloud API Calls From Previously Unseen User Roles - Rule"] mappings = {"cis20": ["CIS 1", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078", "T1078.004"], "nist": ["DE.CM", "DE.DP", "ID.AM", "PR.AC"]} investigative_searches = ["ESCU - AWS Investigate User Activities By ARN - Response Task"] -support_searches = ["ESCU - Previously Seen Cloud API Calls Per User Role - Update", "ESCU - Baseline Of Cloud Security Group API Calls Per User", "ESCU - Baseline Of Cloud Infrastructure API Calls Per User", "ESCU - Previously Seen Cloud API Calls Per User Role - Initial"] +support_searches = ["ESCU - Previously Seen Cloud API Calls Per User Role - Initial", "ESCU - Baseline Of Cloud Security Group API Calls Per User", "ESCU - Previously Seen Cloud API Calls Per User Role - Update", "ESCU - Baseline Of Cloud Infrastructure API Calls Per User"] data_models = ["Change"] providing_technologies = none description = Detect and investigate suspicious activities by users and roles in your cloud environments. narrative = It seems obvious that it is critical to monitor and control the users who have access to your cloud infrastructure. Nevertheless, it's all too common for enterprises to lose track of ad-hoc accounts, leaving their servers vulnerable to attack. In fact, this was the very oversight that led to Tesla's cryptojacking attack in February, 2018.\ In addition to compromising the security of your data, when bad actors leverage your compute resources, it can incur monumental costs, since you will be billed for any new instances and increased bandwidth usage. +product = ['Splunk Security Analytics for AWS', 'Splunk Enterprise', 'Splunk Enterprise Security', 'Splunk Cloud'] #### END STORIES #### \ No newline at end of file diff --git a/dist/saaws/default/app.conf b/dist/saaws/default/app.conf index 980a4b23a8..2f76ac5958 100644 --- a/dist/saaws/default/app.conf +++ b/dist/saaws/default/app.conf @@ -8,7 +8,6 @@ build = 25386 [triggers] reload.analytic_stories = simple -reload.usage_searches = simple reload.use_case_library = simple reload.correlationsearches = simple reload.analyticstories = simple diff --git a/dist/saaws/default/collections.conf b/dist/saaws/default/collections.conf index 369a4ac35d..1fd6a7f12a 100644 --- a/dist/saaws/default/collections.conf +++ b/dist/saaws/default/collections.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security_content -# On Date: 2021-03-30T19:36:01 UTC +# On Date: 2021-04-12T22:03:03 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/dist/saaws/default/commands.conf b/dist/saaws/default/commands.conf deleted file mode 100644 index 14ea427b91..0000000000 --- a/dist/saaws/default/commands.conf +++ /dev/null @@ -1,10 +0,0 @@ -[dnstwist] -filename = dnstwist.py -chunked = true - -# run story functionality has been moved to: https://github.com/splunk/analytic_story_execution' -# [runstory] -# filename = runstory.py -# chunked = true -# is_risky = true - diff --git a/dist/saaws/default/es_investigations.conf b/dist/saaws/default/es_investigations.conf index 2ddbfc379b..6b986f3dd3 100644 --- a/dist/saaws/default/es_investigations.conf +++ b/dist/saaws/default/es_investigations.conf @@ -11,21 +11,21 @@ label = AWS Network ACL Activity description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. disabled = 0 -panels = ["panel://workbench_panel_get_process_info___response_task", "panel://workbench_panel_get_notable_history___response_task", "panel://workbench_panel_aws_investigate_user_activities_by_arn___response_task", "panel://workbench_panel_get_dns_traffic_ratio___response_task", "panel://workbench_panel_get_dns_server_history_for_a_host___response_task", "panel://workbench_panel_aws_network_acl_details_from_id___response_task", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic___response_task", "panel://workbench_panel_get_all_aws_activity_from_ip_address___response_task", "panel://workbench_panel_aws_network_interface_details_via_resourceid___response_task", "panel://workbench_panel_get_process_information_for_port_activity___response_task"] +panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn___response_task", "panel://workbench_panel_aws_network_interface_details_via_resourceid___response_task", "panel://workbench_panel_get_all_aws_activity_from_ip_address___response_task", "panel://workbench_panel_aws_network_acl_details_from_id___response_task"] [panel_group://workbench_panel_group_aws_security_hub_alerts] label = AWS Security Hub Alerts description = This story is focused around detecting Security Hub alerts generated from AWS disabled = 0 -panels = ["panel://workbench_panel_get_ec2_instance_details_by_instanceid___response_task", "panel://workbench_panel_get_ec2_launch_details___response_task", "panel://workbench_panel_aws_investigate_user_activities_by_arn___response_task"] +panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn___response_task", "panel://workbench_panel_get_ec2_instance_details_by_instanceid___response_task", "panel://workbench_panel_get_ec2_launch_details___response_task"] [panel_group://workbench_panel_group_cloud_cryptomining] label = Cloud Cryptomining description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. disabled = 0 -panels = ["panel://workbench_panel_investigate_aws_activities_via_region_name___response_task", "panel://workbench_panel_get_ec2_launch_details___response_task", "panel://workbench_panel_get_ec2_instance_details_by_instanceid___response_task", "panel://workbench_panel_aws_investigate_user_activities_by_arn___response_task", "panel://workbench_panel_aws_investigate_security_hub_alerts_by_dest___response_task", "panel://workbench_panel_get_notable_history___response_task"] +panels = ["panel://workbench_panel_get_ec2_instance_details_by_instanceid___response_task", "panel://workbench_panel_get_ec2_launch_details___response_task", "panel://workbench_panel_aws_investigate_user_activities_by_arn___response_task", "panel://workbench_panel_aws_investigate_security_hub_alerts_by_dest___response_task", "panel://workbench_panel_investigate_aws_activities_via_region_name___response_task"] [panel_group://workbench_panel_group_cloud_federated_credential_abuse] label = Cloud Federated Credential Abuse @@ -60,21 +60,21 @@ label = Suspicious AWS S3 Activities description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. disabled = 0 -panels = ["panel://workbench_panel_investigate_aws_activities_via_region_name___response_task", "panel://workbench_panel_aws_investigate_user_activities_by_arn___response_task", "panel://workbench_panel_aws_s3_bucket_details_via_bucketname___response_task", "panel://workbench_panel_get_all_aws_activity_from_ip_address___response_task", "panel://workbench_panel_get_notable_history___response_task"] +panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn___response_task", "panel://workbench_panel_aws_s3_bucket_details_via_bucketname___response_task", "panel://workbench_panel_get_all_aws_activity_from_ip_address___response_task", "panel://workbench_panel_investigate_aws_activities_via_region_name___response_task"] [panel_group://workbench_panel_group_suspicious_cloud_authentication_activities] label = Suspicious Cloud Authentication Activities description = Monitor your cloud authentication events. Searches within this Analytic Story leverage the recent cloud updates to the Authentication data model to help you stay aware of and investigate suspicious login activity. disabled = 0 -panels = ["panel://workbench_panel_investigate_aws_user_activities_by_user_field___response_task", "panel://workbench_panel_get_notable_history___response_task"] +panels = ["panel://workbench_panel_investigate_aws_user_activities_by_user_field___response_task"] [panel_group://workbench_panel_group_suspicious_cloud_instance_activities] label = Suspicious Cloud Instance Activities description = Monitor your cloud infrastructure provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your cloud environment. disabled = 0 -panels = ["panel://workbench_panel_get_all_aws_activity_from_ip_address___response_task", "panel://workbench_panel_aws_investigate_user_activities_by_arn___response_task"] +panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn___response_task", "panel://workbench_panel_get_all_aws_activity_from_ip_address___response_task"] [panel_group://workbench_panel_group_suspicious_cloud_provisioning_activities] label = Suspicious Cloud Provisioning Activities @@ -188,22 +188,6 @@ tokens = {\ }\ -[panel://workbench_panel_all_backup_logs_for_host___response_task] -label = All backup logs for host -description = Retrieve the backup logs for the last 2 weeks for a specific host in order to investigate why backups are not completing successfully. -disabled = 0 -tokens = {\ - "dest": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR dest=",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "null"\ - }\ -}\ - - [panel://workbench_panel_amazon_eks_kubernetes_activity_by_src_ip___response_task] label = Amazon EKS Kubernetes activity by src ip description = This search provides investigation data about requests via user agent, authentication request URI, verb and cluster name data against Kubernetes cluster from a specific IP address @@ -220,22 +204,6 @@ tokens = {\ }\ -[panel://workbench_panel_gcp_kubernetes_activity_by_src_ip___response_task] -label = GCP Kubernetes activity by src ip -description = This search provides investigation data about requests via user agent, authentication request URI, resource path and cluster name data against Kubernetes cluster from a specific IP address -disabled = 0 -tokens = {\ - "src_ip": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR src_ip=",\ - "valueType": "primitive",\ - "value": "file",\ - "default": "null"\ - }\ -}\ - - [panel://workbench_panel_get_all_aws_activity_from_city___response_task] label = Get All AWS Activity From City description = This search retrieves all the activity from a specific city and will create a table containing the time, city, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. @@ -300,78 +268,6 @@ tokens = {\ }\ -[panel://workbench_panel_get_backup_logs_for_endpoint___response_task] -label = Get Backup Logs For Endpoint -description = This search will tell you the backup status from your netbackup_logs of a specific endpoint for the last week. -disabled = 0 -tokens = {\ - "dest": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR dest=",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "null"\ - }\ -}\ - - -[panel://workbench_panel_get_certificate_logs_for_a_domain___response_task] -label = Get Certificate logs for a domain -description = This search queries the Certificates datamodel and give you all the information for a specific domain. Please note that the certificates issued by "Let's Encrypt" are widely used by attackers. -disabled = 0 -tokens = {\ - "domain": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR domain=",\ - "valueType": "primitive",\ - "value": "file",\ - "default": "null"\ - }\ -}\ - - -[panel://workbench_panel_get_dns_server_history_for_a_host___response_task] -label = Get DNS Server History for a host -description = While investigating any detections it is important to understand which and how many DNS servers a host has connected to in the past. This search uses data that is tagged as DNS and gives you a count and list of DNS servers that a particular host has connected to the previous 24 hours. -disabled = 0 -tokens = {\ - "src_ip": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR src_ip=",\ - "valueType": "primitive",\ - "value": "file",\ - "default": "null"\ - }\ -}\ - - -[panel://workbench_panel_get_dns_traffic_ratio___response_task] -label = Get DNS traffic ratio -description = This search calculates the ratio of DNS traffic originating and coming from a host to a list of DNS servers over the last 24 hours. A high value of this ratio could be very useful to quickly understand if a src_ip (host) is sending a high volume of data out via port 53, could be an indicator of data exfiltration via DNS. -disabled = 0 -tokens = {\ - "src_ip": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR src_ip=",\ - "valueType": "primitive",\ - "value": "file",\ - "default": "null"\ - },\ - "dest_ip": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR dest_ip=",\ - "valueType": "primitive",\ - "value": "file",\ - "default": "null"\ - }\ -}\ - - [panel://workbench_panel_get_ec2_instance_details_by_instanceid___response_task] label = Get EC2 Instance Details by instanceId description = This search queries AWS description logs and returns all the information about a specific instance via the instanceId field @@ -404,294 +300,6 @@ tokens = {\ }\ -[panel://workbench_panel_get_email_info___response_task] -label = Get Email Info -description = This search returns all the information Splunk might have collected a specific email message over the last 2 hours. -disabled = 0 -tokens = {\ - "message_id": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR message_id=",\ - "valueType": "primitive",\ - "value": "file",\ - "default": "null"\ - }\ -}\ - - -[panel://workbench_panel_get_emails_from_specific_sender___response_task] -label = Get Emails From Specific Sender -description = This search returns all the emails from a specific sender over the last 24 and next hours. -disabled = 0 -tokens = {\ - "src_user": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR src_user=",\ - "valueType": "primitive",\ - "value": "file",\ - "default": "null"\ - }\ -}\ - - -[panel://workbench_panel_get_first_occurrence_and_last_occurrence_of_a_mac_address___response_task] -label = Get First Occurrence and Last Occurrence of a MAC Address -description = This search allows you to gather more context around a notable which has detected a new device connecting to your network. Use this search to determine the first and last occurrences of the suspicious device attempting to connect with your network. -disabled = 0 -tokens = {\ - "src_mac": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR src_mac=",\ - "valueType": "primitive",\ - "value": "file",\ - "default": "null"\ - }\ -}\ - - -[panel://workbench_panel_get_history_of_email_sources___response_task] -label = Get History Of Email Sources -description = This search returns a list of all email sources seen in the 48 hours prior to the notable event to 24 hours after, and the number of emails from each source. -disabled = 0 -tokens = {\ - "src": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR src=",\ - "valueType": "primitive",\ - "value": "file",\ - "default": "null"\ - }\ -}\ - - -[panel://workbench_panel_get_logon_rights_modifications_for_endpoint___response_task] -label = Get Logon Rights Modifications For Endpoint -description = This search allows you to retrieve any modifications to logon rights associated with a specific host. -disabled = 0 -tokens = {\ - "dest": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR dest=",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "null"\ - }\ -}\ - - -[panel://workbench_panel_get_logon_rights_modifications_for_user___response_task] -label = Get Logon Rights Modifications For User -description = This search allows you to retrieve any modifications to logon rights for a specific user account. -disabled = 0 -tokens = {\ - "user": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR user=",\ - "valueType": "primitive",\ - "value": "identity",\ - "default": "null"\ - }\ -}\ - - -[panel://workbench_panel_get_notable_history___response_task] -label = Get Notable History -description = This search queries the notable index and returns all the Notable Events for the particular destination host, giving the analyst an overview of the incidents that may have occurred with the host under investigation. -disabled = 0 -tokens = {\ - "dest": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR dest=",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "null"\ - }\ -}\ - - -[panel://workbench_panel_get_outbound_emails_to_hidden_cobra_threat_actors___response_task] -label = Get Outbound Emails to Hidden Cobra Threat Actors -description = This search returns the information of the users that sent emails to the accounts controlled by the Hidden Cobra Threat Actors: specifically to `misswang8107@gmail.com`, and from `redhat@gmail.com`. -disabled = 0 -tokens = {\ - "src_user": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR src_user=",\ - "valueType": "primitive",\ - "value": "file",\ - "default": "null"\ - },\ - "recipient": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR recipient=",\ - "valueType": "primitive",\ - "value": "file",\ - "default": "null"\ - }\ -}\ - - -[panel://workbench_panel_get_parent_process_info___response_task] -label = Get Parent Process Info -description = This search queries the Endpoint data model to give you details about the parent process of a process running on a host which is under investigation. Enter the values of the process name in question and the dest -disabled = 0 -tokens = {\ - "parent_process_name": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR parent_process_name=",\ - "valueType": "primitive",\ - "value": "file",\ - "default": "null"\ - },\ - "dest": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR dest=",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "null"\ - }\ -}\ - - -[panel://workbench_panel_get_process_file_activity___response_task] -label = Get Process File Activity -description = This search returns the file activity for a specific process on a specific endpoint -disabled = 0 -tokens = {\ - "process_name": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR process_name=",\ - "valueType": "primitive",\ - "value": "file",\ - "default": "null"\ - },\ - "dest": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR dest=",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "null"\ - }\ -}\ - - -[panel://workbench_panel_get_process_info___response_task] -label = Get Process Info -description = This search queries the Endpoint data model to give you details about the process running on a host which is under investigation. To gather the process info, enter the values for the process name in question and the destination IP address. -disabled = 0 -tokens = {\ - "process_name": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR process_name=",\ - "valueType": "primitive",\ - "value": "file",\ - "default": "null"\ - },\ - "dest": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR dest=",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "null"\ - }\ -}\ - - -[panel://workbench_panel_get_process_information_for_port_activity___response_task] -label = Get Process Information For Port Activity -description = This search will return information about the process associated with observed network traffic to a specific destination port from a specific host. -disabled = 0 -tokens = {\ - "dest_port": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR dest_port=",\ - "valueType": "primitive",\ - "value": "file",\ - "default": "null"\ - },\ - "dest": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR dest=",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "null"\ - }\ -}\ - - -[panel://workbench_panel_get_process_responsible_for_the_dns_traffic___response_task] -label = Get Process Responsible For The DNS Traffic -description = While investigating, an analyst will want to know what process and parent_process is responsible for generating suspicious DNS traffic. Use the following search and enter the value of `dest` in the search to get specific details on the process responsible for creating the DNS traffic. -disabled = 0 -tokens = {\ - "dest": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR dest=",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "null"\ - }\ -}\ - - -[panel://workbench_panel_get_sysmon_wmi_activity_for_host___response_task] -label = Get Sysmon WMI Activity for Host -description = This search queries Sysmon WMI events for the host of interest. -disabled = 0 -tokens = {\ - "process": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR process=",\ - "valueType": "primitive",\ - "value": "file",\ - "default": "null"\ - },\ - "dest": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR dest=",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "null"\ - }\ -}\ - - -[panel://workbench_panel_get_web_session_information_via_session_id___response_task] -label = Get Web Session Information via session id -description = This search helps an analyst investigate a notable event to find out more about a specific web session. The search looks for a specific web session ID in the HTTP web traffic and outputs the URL and user agents, grouped by source IP address and HTTP status code. -disabled = 0 -tokens = {\ - "session_id": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR session_id=",\ - "valueType": "primitive",\ - "value": "file",\ - "default": "null"\ - }\ -}\ - - [panel://workbench_panel_investigate_aws_user_activities_by_user_field___response_task] label = Investigate AWS User Activities by user field description = This search lists all the logged CloudTrail activities by a specific user and will create a table containing the source of the user, the region of the activity, the name and type of the event, the action taken, and the user's identity information. @@ -724,187 +332,3 @@ tokens = {\ }\ -[panel://workbench_panel_investigate_failed_logins_for_multiple_destinations___response_task] -label = Investigate Failed Logins for Multiple Destinations -description = This search returns failed logins to multiple destinations by user. -disabled = 0 -tokens = {\ - "user": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR user=",\ - "valueType": "primitive",\ - "value": "identity",\ - "default": "null"\ - }\ -}\ - - -[panel://workbench_panel_investigate_network_traffic_from_src_ip___response_task] -label = Investigate Network Traffic From src ip -description = This search allows you to find all the network traffic from a specific IP address. -disabled = 0 -tokens = {\ - "src_ip": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR src_ip=",\ - "valueType": "primitive",\ - "value": "file",\ - "default": "null"\ - }\ -}\ - - -[panel://workbench_panel_investigate_okta_activity_by_ip_address___response_task] -label = Investigate Okta Activity by IP Address -description = This search returns all okta events from a specific IP address. -disabled = 0 -tokens = {\ - "user": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR user=",\ - "valueType": "primitive",\ - "value": "identity",\ - "default": "null"\ - }\ -}\ - - -[panel://workbench_panel_investigate_okta_activity_by_app___response_task] -label = Investigate Okta Activity by app -description = This search returns all okta events associated with a specific app -disabled = 0 -tokens = {\ - "app": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR app=",\ - "valueType": "primitive",\ - "value": "file",\ - "default": "null"\ - }\ -}\ - - -[panel://workbench_panel_investigate_pass_the_hash_attempts___response_task] -label = Investigate Pass the Hash Attempts -description = This search hunts for dumped NTLM hashes used for pass the hash. -disabled = 0 -tokens = {\ - "dest": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR dest=",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "null"\ - }\ -}\ - - -[panel://workbench_panel_investigate_pass_the_ticket_attempts___response_task] -label = Investigate Pass the Ticket Attempts -description = This search hunts for dumped kerberos ticket from LSASS memory. -disabled = 0 -tokens = {\ - "dest": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR dest=",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "null"\ - }\ -}\ - - -[panel://workbench_panel_investigate_previous_unseen_user___response_task] -label = Investigate Previous Unseen User -description = This search returns previous unseen user, which didn't log in for 30 days. -disabled = 0 -tokens = {\ - "dest": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR dest=",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "null"\ - }\ -}\ - - -[panel://workbench_panel_investigate_successful_remote_desktop_authentications___response_task] -label = Investigate Successful Remote Desktop Authentications -description = This search returns the source, destination, and user for all successful remote-desktop authentications. A successful authentication after a brute-force attack on a destination machine is suspicious behavior. -disabled = 0 -tokens = {\ - "dest": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR dest=",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "null"\ - }\ -}\ - - -[panel://workbench_panel_investigate_suspicious_strings_in_http_header___response_task] -label = Investigate Suspicious Strings in HTTP Header -description = This search helps an analyst investigate a notable event related to a potential Apache Struts exploitation. To investigate, we will want to isolate and analyze the "payload" or the commands that were passed to the vulnerable hosts by creating a few regular expressions to carve out the commands focusing on common keywords from the payload, such as cmd.exe, /bin/bash and whois. The search returns these suspicious strings found in the HTTP logs of the system of interest. -disabled = 0 -tokens = {\ - "src_ip": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR src_ip=",\ - "valueType": "primitive",\ - "value": "file",\ - "default": "null"\ - },\ - "dest_ip": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR dest_ip=",\ - "valueType": "primitive",\ - "value": "file",\ - "default": "null"\ - }\ -}\ - - -[panel://workbench_panel_investigate_user_activities_in_okta___response_task] -label = Investigate User Activities In Okta -description = This search returns all okta events by a specific user -disabled = 0 -tokens = {\ - "user": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR user=",\ - "valueType": "primitive",\ - "value": "identity",\ - "default": "null"\ - }\ -}\ - - -[panel://workbench_panel_investigate_web_posts_from_src___response_task] -label = Investigate Web POSTs From src -description = This investigative search retrieves POST requests from a specified source IP or hostname. Identifying the POST requests, as well as their associated destination URLs and user agent(s), may help you scope and characterize the suspicious traffic. -disabled = 0 -tokens = {\ - "src": {\ - "valuePrefix": "\"",\ - "valueSuffix": "\"",\ - "delimiter": " OR src=",\ - "valueType": "primitive",\ - "value": "file",\ - "default": "null"\ - }\ -}\ - - diff --git a/dist/saaws/default/macros.conf b/dist/saaws/default/macros.conf index e6ecf142c3..33c0f08703 100644 --- a/dist/saaws/default/macros.conf +++ b/dist/saaws/default/macros.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security_content -# On Date: 2021-03-30T19:36:01 UTC +# On Date: 2021-04-12T22:03:03 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/dist/saaws/default/savedsearches.conf b/dist/saaws/default/savedsearches.conf index 57d7dcf2df..481be4bc2d 100644 --- a/dist/saaws/default/savedsearches.conf +++ b/dist/saaws/default/savedsearches.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security_content -# On Date: 2021-03-30T19:36:01 UTC +# On Date: 2021-04-12T22:03:03 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -37,7 +37,7 @@ action.correlationsearch.label = ESCU - AWS Create Policy Version to allow all r action.correlationsearch.annotations = {"analytic_story": ["AWS IAM Privilege Escalation"], "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078.004"], "nist": ["PR.DS", "PR.AC", "DE.CM"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -76,7 +76,7 @@ action.correlationsearch.label = ESCU - AWS CreateAccessKey - Rule action.correlationsearch.annotations = {"analytic_story": ["AWS IAM Privilege Escalation"], "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1136.003"], "nist": ["PR.DS", "PR.AC", "DE.CM"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -115,7 +115,7 @@ action.correlationsearch.label = ESCU - AWS CreateLoginProfile - Rule action.correlationsearch.annotations = {"analytic_story": ["AWS IAM Privilege Escalation"], "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1136.003"], "nist": ["PR.DS", "PR.AC", "DE.CM"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -154,7 +154,7 @@ action.correlationsearch.label = ESCU - AWS Cross Account Activity From Previous action.correlationsearch.annotations = {"analytic_story": ["Suspicious Cloud Authentication Activities"], "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.AC", "PR.DS", "DE.AE"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -193,7 +193,7 @@ action.correlationsearch.label = ESCU - AWS Detect Users creating keys with encr action.correlationsearch.annotations = {"analytic_story": ["Ransomware Cloud"], "mitre_attack": ["T1486"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -232,7 +232,7 @@ action.correlationsearch.label = ESCU - AWS Detect Users with KMS keys performin action.correlationsearch.annotations = {"analytic_story": ["Ransomware Cloud"], "mitre_attack": ["T1486"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -271,7 +271,7 @@ action.correlationsearch.label = ESCU - AWS Network Access Control List Created action.correlationsearch.annotations = {"analytic_story": ["AWS Network ACL Activity"], "cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1562.007"], "nist": ["DE.DP", "DE.AE"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -310,7 +310,7 @@ action.correlationsearch.label = ESCU - AWS Network Access Control List Deleted action.correlationsearch.annotations = {"analytic_story": ["AWS Network ACL Activity"], "cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1562.007"], "nist": ["DE.DP", "DE.AE"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -349,7 +349,7 @@ action.correlationsearch.label = ESCU - AWS SAML Access by Provider User and Pri action.correlationsearch.annotations = {"analytic_story": ["Cloud Federated Credential Abuse"], "mitre_attack": ["T1078"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -388,7 +388,7 @@ action.correlationsearch.label = ESCU - AWS SAML Update identity provider - Rule action.correlationsearch.annotations = {"analytic_story": ["Cloud Federated Credential Abuse"], "mitre_attack": ["T1078"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -427,7 +427,7 @@ action.correlationsearch.label = ESCU - AWS SetDefaultPolicyVersion - Rule action.correlationsearch.annotations = {"analytic_story": ["AWS IAM Privilege Escalation"], "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078.004"], "nist": ["PR.DS", "PR.AC", "DE.CM"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -466,7 +466,7 @@ action.correlationsearch.label = ESCU - AWS UpdateLoginProfile - Rule action.correlationsearch.annotations = {"analytic_story": ["AWS IAM Privilege Escalation"], "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1136.003"], "nist": ["PR.DS", "PR.AC", "DE.CM"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -505,7 +505,7 @@ action.correlationsearch.label = ESCU - Abnormally High Number Of Cloud Infrastr action.correlationsearch.annotations = {"analytic_story": ["Suspicious Cloud User Activities"], "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078.004"], "nist": ["DE.DP", "DE.CM", "PR.AC"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -544,7 +544,7 @@ action.correlationsearch.label = ESCU - Abnormally High Number Of Cloud Instance action.correlationsearch.annotations = {"analytic_story": ["Suspicious Cloud Instance Activities"], "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078.004"], "nist": ["DE.DP", "DE.AE"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -583,7 +583,7 @@ action.correlationsearch.label = ESCU - Abnormally High Number Of Cloud Instance action.correlationsearch.annotations = {"analytic_story": ["Cloud Cryptomining", "Suspicious Cloud Instance Activities"], "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078.004"], "nist": ["DE.DP", "DE.AE"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -622,7 +622,7 @@ action.correlationsearch.label = ESCU - Abnormally High Number Of Cloud Security action.correlationsearch.annotations = {"analytic_story": ["Suspicious Cloud User Activities"], "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078.004"], "nist": ["DE.DP", "DE.CM", "PR.AC"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -661,7 +661,7 @@ action.correlationsearch.label = ESCU - Cloud API Calls From Previously Unseen U action.correlationsearch.annotations = {"analytic_story": ["Suspicious Cloud User Activities"], "cis20": ["CIS 1"], "mitre_attack": ["T1078"], "nist": ["ID.AM"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -700,7 +700,7 @@ action.correlationsearch.label = ESCU - Cloud Compute Instance Created By Previo action.correlationsearch.annotations = {"analytic_story": ["Cloud Cryptomining"], "cis20": ["CIS 1"], "mitre_attack": ["T1078.004"], "nist": ["ID.AM"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -739,7 +739,7 @@ action.correlationsearch.label = ESCU - Cloud Compute Instance Created In Previo action.correlationsearch.annotations = {"analytic_story": ["Cloud Cryptomining"], "cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1535"], "nist": ["DE.DP", "DE.AE"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -778,7 +778,7 @@ action.correlationsearch.label = ESCU - Cloud Compute Instance Created With Prev action.correlationsearch.annotations = {"analytic_story": ["Cloud Cryptomining"], "cis20": ["CIS 1"], "nist": ["ID.AM"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -817,7 +817,7 @@ action.correlationsearch.label = ESCU - Cloud Compute Instance Created With Prev action.correlationsearch.annotations = {"analytic_story": ["Cloud Cryptomining"], "cis20": ["CIS 1"], "nist": ["ID.AM"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -856,7 +856,7 @@ action.correlationsearch.label = ESCU - Cloud Instance Modified By Previously Un action.correlationsearch.annotations = {"analytic_story": ["Suspicious Cloud Instance Activities"], "cis20": ["CIS 1"], "mitre_attack": ["T1078.004"], "nist": ["ID.AM"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -896,7 +896,7 @@ action.correlationsearch.label = ESCU - Cloud Provisioning Activity From Previou action.correlationsearch.annotations = {"analytic_story": ["Suspicious Cloud Provisioning Activities"], "cis20": ["CIS 1"], "mitre_attack": ["T1078"], "nist": ["ID.AM"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -936,7 +936,7 @@ action.correlationsearch.label = ESCU - Cloud Provisioning Activity From Previou action.correlationsearch.annotations = {"analytic_story": ["Suspicious Cloud Provisioning Activities"], "cis20": ["CIS 1"], "mitre_attack": ["T1078"], "nist": ["ID.AM"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -976,7 +976,7 @@ action.correlationsearch.label = ESCU - Cloud Provisioning Activity From Previou action.correlationsearch.annotations = {"analytic_story": ["Suspicious Cloud Provisioning Activities"], "cis20": ["CIS 1"], "mitre_attack": ["T1078"], "nist": ["ID.AM"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -1016,7 +1016,7 @@ action.correlationsearch.label = ESCU - Cloud Provisioning Activity From Previou action.correlationsearch.annotations = {"analytic_story": ["Suspicious Cloud Provisioning Activities"], "cis20": ["CIS 1"], "mitre_attack": ["T1078"], "nist": ["ID.AM"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -1055,7 +1055,7 @@ action.correlationsearch.label = ESCU - Detect AWS Console Login by New User - R action.correlationsearch.annotations = {"analytic_story": ["Suspicious Cloud Authentication Activities"], "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -1094,7 +1094,7 @@ action.correlationsearch.label = ESCU - Detect AWS Console Login by User from Ne action.correlationsearch.annotations = {"analytic_story": ["Suspicious AWS Login Activities", "Suspicious Cloud Authentication Activities"], "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1535"], "nist": ["DE.DP", "DE.AE"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -1133,7 +1133,7 @@ action.correlationsearch.label = ESCU - Detect AWS Console Login by User from Ne action.correlationsearch.annotations = {"analytic_story": ["Suspicious AWS Login Activities", "Suspicious Cloud Authentication Activities"], "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1535"], "nist": ["DE.DP", "DE.AE"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -1172,7 +1172,7 @@ action.correlationsearch.label = ESCU - Detect AWS Console Login by User from Ne action.correlationsearch.annotations = {"analytic_story": ["Suspicious AWS Login Activities", "Suspicious Cloud Authentication Activities"], "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1535"], "nist": ["DE.DP", "DE.AE"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -1211,7 +1211,7 @@ action.correlationsearch.label = ESCU - Detect New Open S3 Buckets over AWS CLI action.correlationsearch.annotations = {"analytic_story": ["Suspicious AWS S3 Activities"], "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1530"], "nist": ["PR.DS", "PR.AC", "DE.CM"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -1250,7 +1250,7 @@ action.correlationsearch.label = ESCU - Detect New Open S3 buckets - Rule action.correlationsearch.annotations = {"analytic_story": ["Suspicious AWS S3 Activities"], "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1530"], "nist": ["PR.DS", "PR.AC", "DE.CM"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -1289,7 +1289,7 @@ action.correlationsearch.label = ESCU - Detect Spike in AWS Security Hub Alerts action.correlationsearch.annotations = {"analytic_story": ["AWS Security Hub Alerts"], "cis20": ["CIS 13"], "nist": ["DE.DP", "DE.AE"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -1328,7 +1328,7 @@ action.correlationsearch.label = ESCU - O365 Add App Role Assignment Grant User action.correlationsearch.annotations = {"analytic_story": ["Office 365 Detections", "Cloud Federated Credential Abuse"], "kill_chain_phases": ["Actions on Objective"], "mitre_attack": ["T1136.003"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -1367,7 +1367,7 @@ action.correlationsearch.label = ESCU - O365 Added Service Principal - Rule action.correlationsearch.annotations = {"analytic_story": ["Office 365 Detections", "Cloud Federated Credential Abuse"], "kill_chain_phases": ["Actions on Objective"], "mitre_attack": ["T1136.003"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -1406,7 +1406,7 @@ action.correlationsearch.label = ESCU - O365 Bypass MFA via Trusted IP - Rule action.correlationsearch.annotations = {"analytic_story": ["Office 365 Detections"], "kill_chain_phases": ["Actions on Objective"], "mitre_attack": ["T1562.007"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -1445,7 +1445,7 @@ action.correlationsearch.label = ESCU - O365 Disable MFA - Rule action.correlationsearch.annotations = {"analytic_story": ["Office 365 Detections"], "kill_chain_phases": ["Actions on Objective"], "mitre_attack": ["T1556"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -1484,7 +1484,7 @@ action.correlationsearch.label = ESCU - O365 Excessive Authentication Failures A action.correlationsearch.annotations = {"analytic_story": ["Office 365 Detections"], "kill_chain_phases": ["Not Applicable"], "mitre_attack": ["T1110"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -1523,7 +1523,7 @@ action.correlationsearch.label = ESCU - O365 Excessive SSO logon errors - Rule action.correlationsearch.annotations = {"analytic_story": ["Office 365 Detections", "Cloud Federated Credential Abuse"], "kill_chain_phases": ["Actions on Objective"], "mitre_attack": ["T1556"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -1562,7 +1562,7 @@ action.correlationsearch.label = ESCU - O365 New Federated Domain Added - Rule action.correlationsearch.annotations = {"analytic_story": ["Office 365 Detections", "Cloud Federated Credential Abuse"], "kill_chain_phases": ["Actions on Objective"], "mitre_attack": ["T1136.003"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -1601,7 +1601,7 @@ action.correlationsearch.label = ESCU - O365 PST export alert - Rule action.correlationsearch.annotations = {"analytic_story": ["Office 365 Detections"], "kill_chain_phases": ["Actions on Objective"], "mitre_attack": ["T1114"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -1640,7 +1640,7 @@ action.correlationsearch.label = ESCU - O365 Suspicious Admin Email Forwarding - action.correlationsearch.annotations = {"analytic_story": ["Office 365 Detections"], "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1114.003"], "nist": ["DE.DP", "DE.AE"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -1679,7 +1679,7 @@ action.correlationsearch.label = ESCU - O365 Suspicious Rights Delegation - Rule action.correlationsearch.annotations = {"analytic_story": ["Office 365 Detections"], "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1114.002"], "nist": ["DE.DP", "DE.AE"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -1718,7 +1718,7 @@ action.correlationsearch.label = ESCU - O365 Suspicious User Email Forwarding - action.correlationsearch.annotations = {"analytic_story": ["Office 365 Detections"], "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1114.003"], "nist": ["DE.DP", "DE.AE"]} schedule_window = auto alert.digest_mode = 1 -disabled = true +disabled = false enableSched = 1 counttype = number of events relation = greater than @@ -1750,7 +1750,7 @@ schedule_window = auto action.escu.providing_technologies = [] action.escu.eli5 = This search is used to build a Machine Learning Toolkit (MLTK) model for how many API calls are performed by each user. By default, the search uses the last 90 days of data to build the model and the model is rebuilt weekly. The model created by this search is then used in the corresponding detection search, which identifies subsequent outliers in the number of instances created in a small time window. action.escu.how_to_implement = You must have Enterprise Security 6.0 or later, if not you will need to verify that the Machine Learning Toolkit (MLTK) version 4.2 or later is installed, along with any required dependencies. Depending on the number of users in your environment, you may also need to adjust the value for max_inputs in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 90 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data. -disabled = true +disabled = false is_visible = false search = | tstats count as api_calls from datamodel=Change where All_Changes.user!=unknown All_Changes.status=success by All_Changes.user _time span=1h | `drop_dm_object_name("All_Changes")` | eval HourOfDay=strftime(_time, "%H") | eval HourOfDay=floor(HourOfDay/4)*4 | eval DayOfWeek=strftime(_time, "%w") | eval isWeekend=if(DayOfWeek >= 1 AND DayOfWeek <= 5, 0, 1) | table _time api_calls, user, HourOfDay, isWeekend | eventstats dc(api_calls) as api_calls by user, HourOfDay, isWeekend | where api_calls >= 1 | fit DensityFunction api_calls by "user,HourOfDay,isWeekend" into cloud_excessive_api_calls_v1 dist=norm show_density=true @@ -1773,7 +1773,7 @@ action.escu.providing_technologies = [] action.escu.eli5 = This search is used to build a Machine Learning Toolkit (MLTK) model for how many instances are destroyed in the environment. By default, the search uses the last 90 days of data to build the model and the model is rebuilt weekly. The model created by this search is then used in the corresponding detection search, which identifies subsequent outliers in the number of instances destroyed in a small time window. action.escu.how_to_implement = You must have Enterprise Security 6.0 or later, if not you will need to verify that the Machine Learning Toolkit (MLTK) version 4.2 or later is installed, along with any required dependencies. Depending on the number of users in your environment, you may also need to adjust the value for max_inputs in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data.\ More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. -disabled = true +disabled = false is_visible = false search = | tstats count as instances_destroyed from datamodel=Change where All_Changes.action=deleted AND All_Changes.status=success AND All_Changes.object_category=instance by _time span=1h | makecontinuous span=1h _time | eval instances_destroyed=coalesce(instances_destroyed, (random()%2)*0.0000000001) | eval HourOfDay=strftime(_time, "%H") | eval HourOfDay=floor(HourOfDay/4)*4 | eval DayOfWeek=strftime(_time, "%w") | eval isWeekend=if(DayOfWeek >= 1 AND DayOfWeek <= 5, 0, 1) | table _time instances_destroyed, HourOfDay, isWeekend | fit DensityFunction instances_destroyed by "HourOfDay,isWeekend" into cloud_excessive_instances_destroyed_v1 dist=expon show_density=true @@ -1796,7 +1796,7 @@ action.escu.providing_technologies = [] action.escu.eli5 = This search is used to build a Machine Learning Toolkit (MLTK) model for how many instances are created in the environment. By default, the search uses the last 90 days of data to build the model and the model is rebuilt weekly. The model created by this search is then used in the corresponding detection search, which identifies subsequent outliers in the number of instances created in a small time window. action.escu.how_to_implement = You must have Enterprise Security 6.0 or later, if not you will need to verify that the Machine Learning Toolkit (MLTK) version 4.2 or later is installed, along with any required dependencies. Depending on the number of users in your environment, you may also need to adjust the value for max_inputs in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 90 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data.\ More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. -disabled = true +disabled = false is_visible = false search = | tstats count as instances_launched from datamodel=Change where (All_Changes.action=created) AND All_Changes.status=success AND All_Changes.object_category=instance by _time span=1h | makecontinuous span=1h _time | eval instances_launched=coalesce(instances_launched, (random()%2)*0.0000000001) | eval HourOfDay=strftime(_time, "%H") | eval HourOfDay=floor(HourOfDay/4)*4 | eval DayOfWeek=strftime(_time, "%w") | eval isWeekend=if(DayOfWeek >= 1 AND DayOfWeek <= 5, 0, 1) | table _time instances_launched, HourOfDay, isWeekend | fit DensityFunction instances_launched by "HourOfDay,isWeekend" into cloud_excessive_instances_created_v1 dist=expon show_density=true @@ -1818,476 +1818,10 @@ schedule_window = auto action.escu.providing_technologies = [] action.escu.eli5 = This search is used to build a Machine Learning Toolkit (MLTK) model for how many API calls for security groups are performed by each user. By default, the search uses the last 90 days of data to build the model and the model is rebuilt weekly. action.escu.how_to_implement = You must have Enterprise Security 6.0 or later, if not you will need to verify that the Machine Learning Toolkit (MLTK) version 4.2 or later is installed, along with any required dependencies. Depending on the number of users in your environment, you may also need to adjust the value for max_inputs in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 90 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data. -disabled = true +disabled = false is_visible = false search = | tstats count as security_group_api_calls from datamodel=Change where All_Changes.object_category=firewall All_Changes.status=success by All_Changes.user _time span=1h | `drop_dm_object_name("All_Changes")` | eval HourOfDay=strftime(_time, "%H") | eval HourOfDay=floor(HourOfDay/4)*4 | eval DayOfWeek=strftime(_time, "%w") | eval isWeekend=if(DayOfWeek >= 1 AND DayOfWeek <= 5, 0, 1) | table _time security_group_api_calls, user, HourOfDay, isWeekend | eventstats dc(security_group_api_calls) as security_group_api_calls by user, HourOfDay, isWeekend | where security_group_api_calls >= 1 | fit DensityFunction security_group_api_calls by "user,HourOfDay,isWeekend" into cloud_excessive_security_group_api_calls_v1 dist=norm show_density=true -[ESCU - Baseline of API Calls per User ARN] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of API Calls per User ARN -description = This search establishes, on a per-hour basis, the average and the standard deviation of the number of API calls made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. -action.escu.creation_date = 2018-04-09 -action.escu.modification_date = 2018-04-09 -action.escu.analytic_story = ["AWS User Monitoring"] -action.escu.data_models = [] -cron_schedule = 0 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search establishes, on a per-hour basis, the average and the standard deviation of the number of API calls made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. -disabled = true -is_visible = false -search = `cloudtrail` eventType=AwsApiCall | spath output=arn path=userIdentity.arn | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup api_call_by_user_baseline | stats count - -[ESCU - Baseline of Command Line Length - MLTK] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of Command Line Length - MLTK -description = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the length of the command lines observed for each user in the environment. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies outliers in the length of the command line. -action.escu.creation_date = 2019-05-08 -action.escu.modification_date = 2019-05-08 -action.escu.analytic_story = ["Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Ransomware", "Suspicious Command-Line Executions", "Suspicious MSHTA Activity", "Unusual Processes"] -action.escu.data_models = [] -cron_schedule = 0 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the length of the command lines observed for each user in the environment. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies outliers in the length of the command line. -action.escu.how_to_implement = You must be ingesting endpoint data and populating the Endpoint data model. In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. Depending on the number of users in your environment, you may also need to adjust the value for max_inputs in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data. More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. -disabled = true -is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as start_time max(_time) as end_time FROM datamodel=Endpoint.Processes by Processes.user Processes.dest Processes.process_name Processes.process | `drop_dm_object_name(Processes)` | search user!=unknown | `security_content_ctime(start_time)`| `security_content_ctime(end_time)`| eval processlen=len(process) | fit DensityFunction processlen by user into cmdline_pdfmodel - -[ESCU - Baseline of DNS Query Length - MLTK] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of DNS Query Length - MLTK -description = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the length of the DNS queries for each DNS record type observed in the environment. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search, which uses it to identify outliers in the length of the DNS query. -action.escu.creation_date = 2019-05-08 -action.escu.modification_date = 2019-05-08 -action.escu.analytic_story = ["Command and Control", "Hidden Cobra Malware", "Suspicious DNS Traffic"] -action.escu.data_models = ["Network_Resolution"] -cron_schedule = 0 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the length of the DNS queries for each DNS record type observed in the environment. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search, which uses it to identify outliers in the length of the DNS query. -action.escu.how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data. More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. -disabled = true -is_visible = false -search = | tstats `security_content_summariesonly` count from datamodel=Network_Resolution by DNS.query DNS.record_type | search DNS.record_type=* | `drop_dm_object_name("DNS")` | eval query_length = len(query) | fit DensityFunction query_length by record_type into dns_query_pdfmodel - -[ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK -description = This search is used to build a Machine Learning Toolkit (MLTK) model for how many RunInstances users do in the environment. By default, the search uses the last 90 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies subsequent outliers in the number of RunInstances performed by a user in a small time window. -action.escu.creation_date = 2019-11-14 -action.escu.modification_date = 2019-11-14 -action.escu.analytic_story = ["AWS Cryptomining", "Suspicious AWS EC2 Activities"] -action.escu.data_models = [] -cron_schedule = 0 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search is used to build a Machine Learning Toolkit (MLTK) model for how many RunInstances users do in the environment. By default, the search uses the last 90 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies subsequent outliers in the number of RunInstances performed by a user in a small time window. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.\ -In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. Depending on the number of users in your environment, you may also need to adjust the value for max_inputs in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data.\ -More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. -disabled = true -is_visible = false -search = `cloudtrail` eventName=RunInstances errorCode=success `ec2_excessive_runinstances_mltk_input_filter` | bucket span=10m _time | stats count as instances_launched by _time src_user | fit DensityFunction instances_launched threshold=0.0005 into ec2_excessive_runinstances_v1 - -[ESCU - Baseline of Excessive AWS Instances Terminated by User - MLTK] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of Excessive AWS Instances Terminated by User - MLTK -description = This search is used to build a Machine Learning Toolkit (MLTK) model for how many TerminateInstances users do in the environment. By default, the search uses the last 90 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies subsequent outliers in the number of TerminateInstances performed by a user in a small time window. -action.escu.creation_date = 2019-11-14 -action.escu.modification_date = 2019-11-14 -action.escu.analytic_story = ["Suspicious AWS EC2 Activities"] -action.escu.data_models = [] -cron_schedule = 0 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search is used to build a Machine Learning Toolkit (MLTK) model for how many TerminateInstances users do in the environment. By default, the search uses the last 90 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies subsequent outliers in the number of TerminateInstances performed by a user in a small time window. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.\ -In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. Depending on the number of users in your environment, you may also need to adjust the value for max_inputs in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data.\ -More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. -disabled = true -is_visible = false -search = `cloudtrail` eventName=TerminateInstances errorCode=success `ec2_excessive_terminateinstances_mltk_input_filter` | bucket span=10m _time | stats count as instances_terminated by _time src_user | fit DensityFunction instances_terminated threshold=0.0005 into ec2_excessive_terminateinstances_v1 - -[ESCU - Baseline of Network ACL Activity by ARN] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of Network ACL Activity by ARN -description = This search establishes, on a per-hour basis, the average and the standard deviation of the number of API calls that were related to network ACLs made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. -action.escu.creation_date = 2018-05-21 -action.escu.modification_date = 2018-05-21 -action.escu.analytic_story = ["AWS Network ACL Activity"] -action.escu.data_models = [] -cron_schedule = 0 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search establishes, on a per-hour basis, the average and the standard deviation of the number of API calls that were related to network ACLs made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. To add or remove API event names for network ACLs, edit the macro `network_acl_events`. -disabled = true -is_visible = false -search = `cloudtrail` `network_acl_events` | spath output=arn path=userIdentity.arn | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup network_acl_activity_baseline | stats count - -[ESCU - Baseline of S3 Bucket deletion activity by ARN] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of S3 Bucket deletion activity by ARN -description = This search establishes, on a per-hour basis, the average and standard deviation for the number of API calls related to deleting an S3 bucket by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. -action.escu.creation_date = 2018-07-17 -action.escu.modification_date = 2018-07-17 -action.escu.analytic_story = ["Suspicious AWS S3 Activities"] -action.escu.data_models = [] -cron_schedule = 0 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search establishes, on a per-hour basis, the average and standard deviation for the number of API calls related to deleting an S3 bucket by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. -disabled = true -is_visible = false -search = `cloudtrail` eventName=DeleteBucket | spath output=arn path=userIdentity.arn | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup s3_deletion_baseline | stats count - -[ESCU - Baseline of SMB Traffic - MLTK] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of SMB Traffic - MLTK -description = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the number of SMB connections observed each hour for every day of week. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search to identify outliers in the number of SMB connections for that hour and day of the week. -action.escu.creation_date = 2019-05-08 -action.escu.modification_date = 2019-05-08 -action.escu.analytic_story = ["DHS Report TA18-074A", "Disabling Security Tools", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Netsh Abuse", "Ransomware"] -action.escu.data_models = ["Network_Traffic"] -cron_schedule = 0 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the number of SMB connections observed each hour for every day of week. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search to identify outliers in the number of SMB connections for that hour and day of the week. -action.escu.how_to_implement = You must be ingesting network traffic and populating the Network_Traffic data model. In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. To improve your results, you may consider adding "src" to the by clause, which will build the model for each unique source in your enviornment. However, if you have a large number of hosts in your environment, this search may be very resource intensive. In this case, you may need to raise the value of max_inputs and/or max_groups in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data. More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. -disabled = true -is_visible = false -search = | tstats `security_content_summariesonly` count from datamodel=Network_Traffic where All_Traffic.dest_port=139 OR All_Traffic.dest_port=445 OR All_Traffic.app=smb by _time span=10m, All_Traffic.src | eval HourOfDay=strftime(_time, "%H") | eval DayOfWeek=strftime(_time, "%A") | `drop_dm_object_name("All_Traffic")` | fit DensityFunction count by "HourOfDay,DayOfWeek" into smb_pdfmodel - -[ESCU - Baseline of Security Group Activity by ARN] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of Security Group Activity by ARN -description = This search establishes, on a per-hour basis, the average and the standard deviation for the number of API calls related to security groups made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. -action.escu.creation_date = 2018-04-17 -action.escu.modification_date = 2018-04-17 -action.escu.analytic_story = ["AWS User Monitoring"] -action.escu.data_models = [] -cron_schedule = 0 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search establishes, on a per-hour basis, the average and the standard deviation for the number of API calls related to security groups made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. To add or remove API event names for security groups, edit the macro `security_group_api_calls`. -disabled = true -is_visible = false -search = `cloudtrail` `security_group_api_calls` | spath output=arn path=userIdentity.arn | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup security_group_activity_baseline | stats count - -[ESCU - Baseline of blocked outbound traffic from AWS] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of blocked outbound traffic from AWS -description = This search establishes, on a per-hour basis, the average and the standard deviation of the number of outbound connections blocked in your VPC flow logs by each source IP address (IP address of your EC2 instances). Also recorded is the number of data points for each source IP. This table outputs to a lookup file to allow the detection search to operate quickly. -action.escu.creation_date = 2018-05-07 -action.escu.modification_date = 2018-05-07 -action.escu.analytic_story = ["AWS Network ACL Activity", "Command and Control", "Suspicious AWS Traffic"] -action.escu.data_models = [] -cron_schedule = 0 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search establishes, on a per-hour basis, the average and the standard deviation of the number of outbound connections blocked in your VPC flow logs by each source IP address (IP address of your EC2 instances). Also recorded is the number of data points for each source IP. This table outputs to a lookup file to allow the detection search to operate quickly. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your `VPC flow logs.`. -disabled = true -is_visible = false -search = `cloudwatchlogs_vpcflow` action=blocked (src_ip=10.0.0.0/8 OR src_ip=172.16.0.0/12 OR src_ip=192.168.0.0/16) ( dest_ip!=10.0.0.0/8 AND dest_ip!=172.16.0.0/12 AND dest_ip!=192.168.0.0/16) | bucket _time span=1h | stats count as numberOfBlockedConnections by _time, src_ip | stats count(numberOfBlockedConnections) as numDataPoints, latest(numberOfBlockedConnections) as latestCount, avg(numberOfBlockedConnections) as avgBlockedConnections, stdev(numberOfBlockedConnections) as stdevBlockedConnections by src_ip | table src_ip, latestCount, numDataPoints, avgBlockedConnections, stdevBlockedConnections | outputlookup baseline_blocked_outbound_connections | stats count - -[ESCU - Count of Unique IPs Connecting to Ports] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Count of Unique IPs Connecting to Ports -description = The search counts the number of times a connection was observed to each destination port, and the number of unique source IPs connecting to them. -action.escu.creation_date = 2017-09-13 -action.escu.modification_date = 2017-09-13 -action.escu.analytic_story = [] -action.escu.data_models = ["Network_Traffic"] -cron_schedule = 0 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = The search counts the number of times a connection was observed to each destination port, and the number of unique source IPs connecting to them. -action.escu.how_to_implement = To successfully implement this search, you must be ingesting network traffic, and populating the Network_Traffic data model. -disabled = true -is_visible = false -search = | tstats `security_content_summariesonly` count dc(All_Traffic.src) as numberOfUniqueHosts from datamodel=Network_Traffic by All_Traffic.dest_port | `drop_dm_object_name("All_Traffic")` | sort - count - -[ESCU - Count of assets by category] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Count of assets by category -description = This search shows you every asset category you have and the assets that belong to those categories. -action.escu.creation_date = 2017-09-13 -action.escu.modification_date = 2017-09-13 -action.escu.analytic_story = ["Asset Tracking"] -action.escu.data_models = [] -cron_schedule = 0 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search shows you every asset category you have and the assets that belong to those categories. -action.escu.how_to_implement = To successfully implement this search you must first leverage the Assets and Identity framework in Enterprise Security to populate your assets_by_str.csv file which should then be mapped to the Identity_Management data model. The Identity_Management data model will contain a list of known authorized company assets. Ensure that all inventoried systems are constantly vetted and updated. -disabled = true -is_visible = false -search = | from datamodel Identity_Management.All_Assets | stats count values(nt_host) by category | sort -count - -[ESCU - Create a list of approved AWS service accounts] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Create a list of approved AWS service accounts -description = This search looks for successful API activity in CloudTrail within the last 30 days, filters out known users from the identity table, and outputs values of users into `aws_service_accounts.csv` lookup file. -action.escu.creation_date = 2018-12-03 -action.escu.modification_date = 2018-12-03 -action.escu.analytic_story = ["AWS User Monitoring"] -action.escu.data_models = [] -cron_schedule = 0 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search looks for successful API activity in CloudTrail within the last 30 days, filters out known users from the identity table, and outputs values of users into `aws_service_accounts.csv` lookup file. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the service account entires in `aws_service_accounts.csv`, which is a lookup file created as a result of running this support search. Please remove the entries of service accounts that are not legitimate. -disabled = true -is_visible = false -search = `cloudtrail` errorCode=success | rename userName as identity | search NOT [inputlookup identity_lookup_expanded | fields identity] | stats count by identity | table identity | outputlookup aws_service_accounts | stats count - -[ESCU - DNSTwist Domain Names] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - DNSTwist Domain Names -description = This search creates permutations of your existing domains, removes the valid domain names and stores them in a specified lookup file so they can be checked for in the associated detection searches. -action.escu.creation_date = 2018-10-08 -action.escu.modification_date = 2018-10-08 -action.escu.analytic_story = ["Brand Monitoring", "Suspicious Emails"] -action.escu.data_models = [] -cron_schedule = 0 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search creates permutations of your existing domains, removes the valid domain names and stores them in a specified lookup file so they can be checked for in the associated detection searches. -action.escu.how_to_implement = To successfully implement this search you need to update the file called domains.csv in the DA-ESS-SOC/lookup directory. Or `cim_corporate_email_domains.csv` and `cim_corporate_web_domains.csv` from **Splunk\_SA\_CIM**. -disabled = true -is_visible = false -search = | dnstwist domainlist=domains.csv | `remove_valid_domains` | eval domain_abuse="true" | table domain, domain_abuse | outputlookup brandMonitoring_lookup | stats count - -[ESCU - Discover DNS records] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Discover DNS records -description = The search takes corporate and common cloud provider domains configured under `cim_corporate_email_domains.csv`, `cim_corporate_web_domains.csv`, and `cloud_domains.csv` finds their responses across the last 30 days from data in the `Network_Resolution ` datamodel, then stores the output under the `discovered_dns_records.csv` lookup -action.escu.creation_date = 2019-02-14 -action.escu.modification_date = 2019-02-14 -action.escu.analytic_story = ["DNS Hijacking"] -action.escu.data_models = ["Network_Resolution"] -cron_schedule = 0 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = The search takes corporate and common cloud provider domains configured under `cim_corporate_email_domains.csv`, `cim_corporate_web_domains.csv`, and `cloud_domains.csv` finds their responses across the last 30 days from data in the `Network_Resolution ` datamodel, then stores the output under the `discovered_dns_records.csv` lookup -action.escu.how_to_implement = To successfully implement this search, you must be ingesting DNS logs, and populating the Network_Resolution data model. Also make sure that the cim_corporate_web_domains and cim_corporate_email_domains lookups are populated with the domains owned by your corporation -disabled = true -is_visible = false -search = | inputlookup cim_corporate_email_domains.csv | inputlookup append=T cim_corporate_web_domains.csv | inputlookup append=T cim_cloud_domains.csv | eval domain = trim(replace(domain, "\*", "")) | join domain [|tstats `security_content_summariesonly` count values(DNS.record_type) as type, values(DNS.answer) as answer from datamodel=Network_Resolution where DNS.message_type=RESPONSE DNS.answer!="unknown" DNS.answer!="" by DNS.query | rename DNS.query as query | where query!="unknown" | rex field=query "(?\w+\.\w+?)(?:$|/)"] | makemv delim=" " answer | makemv delim=" " type | sort -count | table count,domain,type,query,answer | outputlookup createinapp=true discovered_dns_records - -[ESCU - Identify Systems Creating Remote Desktop Traffic] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Identify Systems Creating Remote Desktop Traffic -description = This search counts the numbers of times the system has generated remote desktop traffic. -action.escu.creation_date = 2017-09-15 -action.escu.modification_date = 2017-09-15 -action.escu.analytic_story = [] -action.escu.data_models = ["Network_Traffic"] -cron_schedule = 0 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search counts the numbers of times the system has generated remote desktop traffic. -action.escu.how_to_implement = To successfully implement this search, you must ingest network traffic and populate the Network_Traffic data model. -disabled = true -is_visible = false -search = | tstats `security_content_summariesonly` count from datamodel=Network_Traffic where All_Traffic.dest_port=3389 by All_Traffic.src | `drop_dm_object_name("All_Traffic")` | sort - count - -[ESCU - Identify Systems Receiving Remote Desktop Traffic] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Identify Systems Receiving Remote Desktop Traffic -description = This search counts the numbers of times the system has created remote desktop traffic -action.escu.creation_date = 2017-09-15 -action.escu.modification_date = 2017-09-15 -action.escu.analytic_story = [] -action.escu.data_models = ["Network_Traffic"] -cron_schedule = 0 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search counts the numbers of times the system has created remote desktop traffic -action.escu.how_to_implement = To successfully implement this search you must ingest network traffic and populate the Network_Traffic data model. If a system receives a lot of remote desktop traffic, you can apply the category common_rdp_destination to it. -disabled = true -is_visible = false -search = | tstats `security_content_summariesonly` count from datamodel=Network_Traffic where All_Traffic.dest_port=3389 by All_Traffic.dest | `drop_dm_object_name("All_Traffic")` | sort - count - -[ESCU - Identify Systems Using Remote Desktop] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Identify Systems Using Remote Desktop -description = This search counts the numbers of times the remote desktop process, mstsc.exe, has run on each system. -action.escu.creation_date = 2019-04-01 -action.escu.modification_date = 2019-04-01 -action.escu.analytic_story = [] -action.escu.data_models = ["Endpoint"] -cron_schedule = 0 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search counts the numbers of times the remote desktop process, mstsc.exe, has run on each system. -action.escu.how_to_implement = To successfully implement this search you must be ingesting endpoint data that records process activity. -disabled = true -is_visible = false -search = | tstats `security_content_summariesonly` count from datamodel=Endpoint.Processes where Processes.process_name="*mstsc.exe*" by Processes.dest Processes.process_name | `drop_dm_object_name(Processes)` | sort - count - -[ESCU - Monitor Successful Backups] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Monitor Successful Backups -description = This search is intended to give you a feel for how often successful backups are conducted in your environment. Fluctuations in these numbers will allow you to determine when you should investigate. -action.escu.creation_date = 2017-09-12 -action.escu.modification_date = 2017-09-12 -action.escu.analytic_story = ["Monitor Backup Solution"] -action.escu.data_models = [] -cron_schedule = 0 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search is intended to give you a feel for how often successful backups are conducted in your environment. Fluctuations in these numbers will allow you to determine when you should investigate. -action.escu.how_to_implement = To successfully implement this search you must be ingesting your backup logs. -disabled = true -is_visible = false -search = `netbackup` "Disk/Partition backup completed successfully." | bucket _time span=1d | stats dc(COMPUTERNAME) as count values(COMPUTERNAME) as dest by _time, MESSAGE - -[ESCU - Monitor Unsuccessful Backups] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Monitor Unsuccessful Backups -description = This search is intended to give you a feel for how often backup failures happen in your environments. Fluctuations in these numbers will allow you to determine when you should investigate. -action.escu.creation_date = 2017-09-12 -action.escu.modification_date = 2017-09-12 -action.escu.analytic_story = ["Monitor Backup Solution"] -action.escu.data_models = [] -cron_schedule = 0 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search is intended to give you a feel for how often backup failures happen in your environments. Fluctuations in these numbers will allow you to determine when you should investigate. -action.escu.how_to_implement = To successfully implement this search you must be ingesting your backup logs. -disabled = true -is_visible = false -search = `netbackup` "An error occurred, failed to backup." | bucket _time span=1d | stats dc(COMPUTERNAME) as count values(COMPUTERNAME) as dest by _time, MESSAGE - -[ESCU - Previously Seen AWS Cross Account Activity] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen AWS Cross Account Activity -description = This search looks for **AssumeRole** events where the requesting account differs from the requested account, then writes these relationships to a lookup file. -action.escu.creation_date = 2018-06-04 -action.escu.modification_date = 2018-06-04 -action.escu.analytic_story = ["AWS Cross Account Activity"] -action.escu.data_models = [] -cron_schedule = 0 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search looks for **AssumeRole** events where the requesting account differs from the requested account, then writes these relationships to a lookup file. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Validate the user name entries in `previously_seen_aws_cross_account_activity.csv`, a lookup file created by this support search. -disabled = true -is_visible = false -search = `cloudtrail` eventName=AssumeRole | spath output=requestingAccountId path=userIdentity.accountId | spath output=requestedAccountId path=resources{}.accountId | search requestingAccountId=* | where requestingAccountId!=requestedAccountId | stats earliest(_time) as firstTime latest(_time) as lastTime by requestingAccountId, requestedAccountId | outputlookup previously_seen_aws_cross_account_activity | stats count - [ESCU - Previously Seen AWS Cross Account Activity - Initial] action.escu = 0 action.escu.enabled = 1 @@ -2306,7 +1840,7 @@ schedule_window = auto action.escu.providing_technologies = [] action.escu.eli5 = This search looks for **AssumeRole** events where the requesting account differs from the requested account, then writes these relationships to a lookup file. action.escu.how_to_implement = You must install and configure the Splunk Add-on for AWS (version 5.1.0 or later)and Enterprise Security 6.2, which contains the required updates to the Authentication data model for cloud use cases. Validate the user name entries in `previously_seen_aws_cross_account_activity.csv`, a lookup file created by this support search. -disabled = true +disabled = false is_visible = false search = | tstats earliest(_time) as firstTime latest(_time) as lastTime from datamodel=Authentication where Authentication.signature=AssumeRole by Authentication.vendor_account Authentication.user Authentication.src Authentication.user_role | `drop_dm_object_name(Authentication)` | rex field=user_role "arn:aws:sts:*:(?.*):" | where vendor_account != dest_account | rename vendor_account as requestingAccountId dest_account as requestedAccountId | table requestingAccountId requestedAccountId firstTime lastTime | outputlookup previously_seen_aws_cross_account_activity @@ -2328,54 +1862,10 @@ schedule_window = auto action.escu.providing_technologies = [] action.escu.eli5 = This search looks for **AssumeRole** events where the requesting account differs from the requested account, then writes these relationships to a lookup file. action.escu.how_to_implement = You must install and configure the Splunk Add-on for AWS (version 5.1.0 or later) and Enterprise Security 6.2, which contains the required updates to the Authentication data model for cloud use cases. Validate the user name entries in `previously_seen_aws_cross_account_activity.csv`, a lookup file created by this support search. -disabled = true +disabled = false is_visible = false search = | tstats earliest(_time) as firstTime latest(_time) as lastTime from datamodel=Authentication where Authentication.signature=AssumeRole by Authentication.vendor_account Authentication.user Authentication.src Authentication.user_role | `drop_dm_object_name(Authentication)` | rex field=user_role "arn:aws:sts:*:(?.*):" | where vendor_account != dest_account | rename vendor_account as requestingAccountId dest_account as requestedAccountId | inputlookup append=t previously_seen_aws_cross_account_activity | stats min(firstTime) as firstTime max(lastTime) as lastTime by requestingAccountId requestedAccountId | outputlookup previously_seen_aws_cross_account_activity -[ESCU - Previously Seen AWS Provisioning Activity Sources] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen AWS Provisioning Activity Sources -description = This search builds a table of the first and last times seen for every IP address (along with its physical location) previously associated with cloud-provisioning activity. This is broadly defined as any event that runs or creates something. -action.escu.creation_date = 2018-03-16 -action.escu.modification_date = 2018-03-16 -action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] -action.escu.data_models = [] -cron_schedule = 0 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search builds a table of the first and last times seen for every IP address (along with its physical location) previously associated with cloud-provisioning activity. This is broadly defined as any event that runs or creates something. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. -disabled = true -is_visible = false -search = `cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | stats earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv | stats count - -[ESCU - Previously Seen AWS Regions] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen AWS Regions -description = This search looks for CloudTrail events where an AWS instance is started and creates a baseline of most recent time (latest) and the first time (earliest) we've seen this region in our dataset grouped by the value awsRegion for the last 30 days -action.escu.creation_date = 2018-01-08 -action.escu.modification_date = 2018-01-08 -action.escu.analytic_story = ["AWS Cryptomining", "Suspicious AWS EC2 Activities"] -action.escu.data_models = [] -cron_schedule = 0 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search looks for CloudTrail events where an AWS instance is started and creates a baseline of most recent time (latest) and the first time (earliest) we've seen this region in our dataset grouped by the value awsRegion for the last 30 days -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. -disabled = true -is_visible = false -search = `cloudtrail` StartInstances | stats earliest(_time) as earliest latest(_time) as latest by awsRegion | outputlookup previously_seen_aws_regions.csv | stats count - [ESCU - Previously Seen Cloud API Calls Per User Role - Initial] action.escu = 0 action.escu.enabled = 1 @@ -2394,7 +1884,7 @@ schedule_window = auto action.escu.providing_technologies = [] action.escu.eli5 = This search builds a table of the first and last times seen for every user role and command combination. This is broadly defined as any event that runs or creates something. This table is then cached. action.escu.how_to_implement = You must be ingesting Cloud infrastructure logs from your cloud provider. -disabled = true +disabled = false is_visible = false search = | tstats earliest(_time) as firstTimeSeen, latest(_time) as lastTimeSeen from datamodel=Change where All_Changes.user_type=AssumedRole AND All_Changes.status=success by All_Changes.user, All_Changes.command | `drop_dm_object_name("All_Changes")` | eventstats min(firstTimeSeen) as globalFirstTime | eval enough_data = if(globalFirstTime <= relative_time(now(), "-7d@d"), 1, 0) | table user, command, firstTimeSeen, lastTimeSeen, enough_data | outputlookup previously_seen_cloud_api_calls_per_user_role @@ -2416,7 +1906,7 @@ schedule_window = auto action.escu.providing_technologies = [] action.escu.eli5 = This search updates the table of the first and last times seen for every user role and command combination. action.escu.how_to_implement = You must be ingesting Cloud infrastructure logs from your cloud provider. -disabled = true +disabled = false is_visible = false search = | tstats earliest(_time) as firstTimeSeen, latest(_time) as lastTimeSeen from datamodel=Change where All_Changes.user_type=AssumedRole AND All_Changes.status=success by All_Changes.user, All_Changes.command | `drop_dm_object_name("All_Changes")` | table user, command, firstTimeSeen, lastTimeSeen | inputlookup previously_seen_cloud_api_calls_per_user_role append=t | stats min(firstTimeSeen) as firstTimeSeen, max(lastTimeSeen) as lastTimeSeen by user, command | where lastTimeSeen > relative_time(now(), `previously_seen_cloud_api_calls_per_user_role_forget_window`) | eventstats min(firstTimeSeen) as globalFirstTime | eval enough_data = if(globalFirstTime <= relative_time(now(), "-7d@d"), 1, 0) | table user, command, firstTimeSeen, lastTimeSeen, enough_data | outputlookup previously_seen_cloud_api_calls_per_user_role @@ -2438,7 +1928,7 @@ schedule_window = auto action.escu.providing_technologies = [] action.escu.eli5 = This search builds a table of previously seen users that have launched a cloud compute instance. action.escu.how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the proper TAs installed. -disabled = true +disabled = false is_visible = false search = | tstats earliest(_time) as firstTimeSeen, latest(_time) as lastTimeSeen from datamodel=Change where All_Changes.action=created AND All_Changes.object_category=instance by All_Changes.user | `drop_dm_object_name("All_Changes")` | outputlookup previously_seen_cloud_compute_creations_by_user | stats count @@ -2460,7 +1950,7 @@ schedule_window = auto action.escu.providing_technologies = [] action.escu.eli5 = This search builds a table of previously seen users that have launched a cloud compute instance. action.escu.how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the proper TAs installed. -disabled = true +disabled = false is_visible = false search = | tstats earliest(_time) as firstTimeSeen, latest(_time) as lastTimeSeen from datamodel=Change where All_Changes.action=created AND All_Changes.object_category=instance by All_Changes.user| `drop_dm_object_name("All_Changes")` | inputlookup append=t previously_seen_cloud_compute_creations_by_user | stats min(firstTimeSeen) as firstTimeSeen max(lastTimeSeen) as lastTimeSeen by user | where lastTimeSeen > relative_time(now(), "-90d@d") | eventstats min(firstTimeSeen) as globalFirstTime | eval enough_data = if(globalFirstTime <= relative_time(now(), "-7d@d"), 1, 0) | outputlookup previously_seen_cloud_compute_creations_by_user @@ -2482,7 +1972,7 @@ schedule_window = auto action.escu.providing_technologies = [] action.escu.eli5 = This search builds a table of previously seen images used to launch cloud compute instances action.escu.how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the latest Change Datamodel accelerated -disabled = true +disabled = false is_visible = false search = | tstats earliest(_time) as firstTimeSeen, latest(_time) as lastTimeSeen from datamodel=Change where All_Changes.action=created by All_Changes.Instance_Changes.image_id | `drop_dm_object_name("All_Changes")` | `drop_dm_object_name("Instance_Changes")` | where image_id != "unknown" | eventstats min(firstTimeSeen) as globalFirstTime | eval enough_data = if(globalFirstTime <= relative_time(now(), "-7d@d"), 1, 0) | outputlookup previously_seen_cloud_compute_images @@ -2504,7 +1994,7 @@ schedule_window = auto action.escu.providing_technologies = [] action.escu.eli5 = This search builds a table of previously seen images used to launch cloud compute instances action.escu.how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs -disabled = true +disabled = false is_visible = false search = | tstats earliest(_time) as firstTimeSeen, latest(_time) as lastTimeSeen from datamodel=Change where All_Changes.action=created by All_Changes.Instance_Changes.image_id | `drop_dm_object_name("All_Changes")` | `drop_dm_object_name("Instance_Changes")` | where image_id != "unknown" | inputlookup append=t previously_seen_cloud_compute_images | stats min(firstTimeSeen) as firstTimeSeen max(lastTimeSeen) as lastTimeSeen by image_id | where lastTimeSeen > relative_time(now(), `previously_seen_cloud_compute_images_forget_window`) | eventstats min(firstTimeSeen) as globalFirstTime | eval enough_data = if(globalFirstTime <= relative_time(now(), "-7d@d"), 1, 0) | outputlookup previously_seen_cloud_compute_images @@ -2526,7 +2016,7 @@ schedule_window = auto action.escu.providing_technologies = [] action.escu.eli5 = This search builds a table of previously seen cloud compute instance types action.escu.how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. -disabled = true +disabled = false is_visible = false search = | tstats earliest(_time) as firstTimeSeen, latest(_time) as lastTimeSeen from datamodel=Change where All_Changes.action=created by All_Changes.Instance_Changes.instance_type | `drop_dm_object_name("All_Changes.Instance_Changes")` | where instance_type != "unknown" | eventstats min(firstTimeSeen) as globalFirstTime | eval enough_data = if(globalFirstTime <= relative_time(now(), "-14d@d"), 1, 0) | outputlookup previously_seen_cloud_compute_instance_types @@ -2548,7 +2038,7 @@ schedule_window = auto action.escu.providing_technologies = [] action.escu.eli5 = This search builds a table of previously seen cloud compute instance types action.escu.how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs -disabled = true +disabled = false is_visible = false search = | tstats earliest(_time) as firstTimeSeen, latest(_time) as lastTimeSeen from datamodel=Change where All_Changes.action=created by All_Changes.Instance_Changes.instance_type | `drop_dm_object_name("All_Changes.Instance_Changes")` | where instance_type != "unknown" | inputlookup append=t previously_seen_cloud_compute_instance_types | stats min(firstTimeSeen) as firstTimeSeen max(lastTimeSeen) as lastTimeSeen by instance_type | where lastTimeSeen > relative_time(now(), `previously_seen_cloud_compute_instance_type_forget_window`) | eventstats min(firstTimeSeen) as globalFirstTime | eval enough_data = if(globalFirstTime <= relative_time(now(), "-14d@d"), 1, 0) | outputlookup previously_seen_cloud_compute_instance_types @@ -2570,7 +2060,7 @@ schedule_window = auto action.escu.providing_technologies = [] action.escu.eli5 = This search builds a table of previously seen users that have modified a cloud instance. action.escu.how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the latest Change Datamodel accelerated. -disabled = true +disabled = false is_visible = false search = | tstats earliest(_time) as firstTimeSeen, latest(_time) as lastTimeSeen from datamodel=Change where All_Changes.action=modified All_Changes.change_type=EC2 All_Changes.status=success by All_Changes.user | `drop_dm_object_name("All_Changes")` | eventstats min(firstTimeSeen) as globalFirstTime | eval enough_data = if(globalFirstTime <= relative_time(now(), "-7d@d"), 1, 0) | outputlookup previously_seen_cloud_instance_modifications_by_user @@ -2592,7 +2082,7 @@ schedule_window = auto action.escu.providing_technologies = [] action.escu.eli5 = This search updates a table of previously seen Cloud Instance modifications that have been made by a user action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. To add or remove APIs that modify an EC2 instance, edit the macro `ec2_modification_api_calls`. -disabled = true +disabled = false is_visible = false search = | tstats earliest(_time) as firstTimeSeen, latest(_time) as lastTimeSeen from datamodel=Change where All_Changes.action=modified All_Changes.change_type=EC2 All_Changes.status=success by All_Changes.user | `drop_dm_object_name("All_Changes")` | inputlookup append=t previously_seen_cloud_instance_modifications_by_user | stats min(firstTimeSeen) as firstTimeSeen max(lastTimeSeen) as lastTimeSeen by user | where lastTimeSeen > relative_time(now(), `previously_seen_cloud_compute_images_forget_window`) | eventstats min(firstTimeSeen) as globalFirstTime | eval enough_data = if(globalFirstTime <= relative_time(now(), "-7d@d"), 1, 0) | outputlookup previously_seen_cloud_instance_modifications_by_user @@ -2614,7 +2104,7 @@ schedule_window = auto action.escu.providing_technologies = [] action.escu.eli5 = This search builds a table of the first and last times seen for every IP address (along with its physical location) previously associated with cloud-provisioning activity. This is broadly defined as any event that runs or creates something. This table is then cached. action.escu.how_to_implement = You must be ingesting Cloud infrastructure logs from your cloud provider. -disabled = true +disabled = false is_visible = false search = | tstats earliest(_time) as firstTimeSeen, latest(_time) as lastTimeSeen from datamodel=Change where (All_Changes.action=started OR All_Changes.action=created) All_Changes.status=success by All_Changes.src | `drop_dm_object_name("All_Changes")` | iplocation src | where isnotnull(Country) | eventstats min(firstTimeSeen) as globalFirstTime | eval enough_data = if(globalFirstTime <= relative_time(now(), "-7d@d"), 1, 0) | table src, City, Country, Region, firstTimeSeen, lastTimeSeen, enough_data | outputlookup previously_seen_cloud_provisioning_activity_sources @@ -2636,7 +2126,7 @@ schedule_window = auto action.escu.providing_technologies = [] action.escu.eli5 = This returns the first and last times seen for every IP address (along with its physical location) previously associated with cloud-provisioning activity within the last day. Cloud provisioning is broadly defined as any event that runs or creates something. It then updates this information with historical data and filters out locations that have not been seen within the specified time window. This updated table is then cached. action.escu.how_to_implement = You must be ingesting Cloud infrastructure logs from your cloud provider. -disabled = true +disabled = false is_visible = false search = | tstats earliest(_time) as firstTimeSeen, latest(_time) as lastTimeSeen from datamodel=Change where (All_Changes.action=started OR All_Changes.action=created) All_Changes.status=success by All_Changes.src | `drop_dm_object_name("All_Changes")` | iplocation src | where isnotnull(Country) | table src, firstTimeSeen, lastTimeSeen, City, Country, Region | inputlookup previously_seen_cloud_provisioning_activity_sources append=t | stats min(firstTimeSeen) as firstTimeSeen, max(lastTimeSeen) as lastTimeSeen by src, City, Country, Region | where lastTimeSeen > relative_time(now(), `previously_seen_cloud_provisioning_activity_forget_window`) | eventstats min(firstTimeSeen) as globalFirstTime | eval enough_data = if(globalFirstTime <= relative_time(now(), "-7d@d"), 1, 0) | table src, City, Country, Region, firstTimeSeen, lastTimeSeen, enough_data | outputlookup previously_seen_cloud_provisioning_activity_sources @@ -2658,7 +2148,7 @@ schedule_window = auto action.escu.providing_technologies = [] action.escu.eli5 = This search looks for cloud compute events where a compute instance is started and creates a baseline of most recent time, `lastTime` and the first time `firstTime` we've seen this region in our dataset grouped by the region for the last 30 days action.escu.how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. -disabled = true +disabled = false is_visible = false search = | tstats earliest(_time) as firstTimeSeen, latest(_time) as lastTimeSeen from datamodel=Change where All_Changes.action=created by All_Changes.vendor_region | `drop_dm_object_name("All_Changes")` | eventstats min(firstTimeSeen) as globalFirstTime | eval enough_data = if(globalFirstTime <= relative_time(now(), "-14d@d"), 1, 0) | outputlookup previously_seen_cloud_regions @@ -2680,142 +2170,10 @@ schedule_window = auto action.escu.providing_technologies = [] action.escu.eli5 = This search looks for cloud compute events where a compute instance is started and creates a baseline of most recent time, `lastTime` and the first time `firstTime` we've seen this region in our dataset grouped by the region for the last 30 days action.escu.how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. -disabled = true +disabled = false is_visible = false search = | tstats earliest(_time) as firstTimeSeen, latest(_time) as lastTimeSeen from datamodel=Change where All_Changes.action=created by All_Changes.vendor_region | `drop_dm_object_name("All_Changes")` | inputlookup append=t previously_seen_cloud_regions | stats min(firstTimeSeen) as firstTimeSeen max(lastTimeSeen) as lastTimeSeen by vendor_region | where lastTimeSeen > relative_time(now(), `previously_seen_cloud_region_forget_window`) | eventstats min(firstTimeSeen) as globalFirstTime | eval enough_data = if(globalFirstTime <= relative_time(now(), "-14d@d"), 1, 0) | outputlookup previously_seen_cloud_regions | stats count -[ESCU - Previously Seen EC2 AMIs] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen EC2 AMIs -description = This search builds a table of previously seen AMIs used to launch EC2 instances -action.escu.creation_date = 2018-03-12 -action.escu.modification_date = 2018-03-12 -action.escu.analytic_story = ["AWS Cryptomining"] -action.escu.data_models = [] -cron_schedule = 0 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search builds a table of previously seen AMIs used to launch EC2 instances -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. -disabled = true -is_visible = false -search = `cloudtrail` eventName=RunInstances errorCode=success | rename requestParameters.instancesSet.items{}.imageId as amiID | stats earliest(_time) as firstTime latest(_time) as lastTime by amiID | outputlookup previously_seen_ec2_amis.csv | stats count - -[ESCU - Previously Seen EC2 Instance Types] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen EC2 Instance Types -description = This search builds a table of previously seen EC2 instance types -action.escu.creation_date = 2018-03-08 -action.escu.modification_date = 2018-03-08 -action.escu.analytic_story = ["AWS Cryptomining"] -action.escu.data_models = [] -cron_schedule = 0 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search builds a table of previously seen EC2 instance types -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. -disabled = true -is_visible = false -search = `cloudtrail` eventName=RunInstances errorCode=success | rename requestParameters.instanceType as instanceType | fillnull value="m1.small" instanceType | stats earliest(_time) as earliest latest(_time) as latest by instanceType | outputlookup previously_seen_ec2_instance_types.csv | stats count - -[ESCU - Previously Seen EC2 Launches By User] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen EC2 Launches By User -description = This search builds a table of previously seen ARNs that have launched a EC2 instance. -action.escu.creation_date = 2018-03-15 -action.escu.modification_date = 2018-03-15 -action.escu.analytic_story = ["AWS Cryptomining", "Suspicious AWS EC2 Activities"] -action.escu.data_models = [] -cron_schedule = 0 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search builds a table of previously seen ARNs that have launched a EC2 instance. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. -disabled = true -is_visible = false -search = `cloudtrail` eventName=RunInstances errorCode=success | rename userIdentity.arn as arn | stats earliest(_time) as firstTime latest(_time) as lastTime by arn | outputlookup previously_seen_ec2_launches_by_user.csv | stats count - -[ESCU - Previously Seen EC2 Modifications By User] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen EC2 Modifications By User -description = This search builds a table of previously seen ARNs that have launched a EC2 instance. -action.escu.creation_date = 2018-04-05 -action.escu.modification_date = 2018-04-05 -action.escu.analytic_story = ["Unusual AWS EC2 Modifications"] -action.escu.data_models = [] -cron_schedule = 0 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search builds a table of previously seen ARNs that have launched a EC2 instance. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. To add or remove APIs that modify an EC2 instance, edit the macro `ec2_modification_api_calls`. -disabled = true -is_visible = false -search = `cloudtrail` `ec2_modification_api_calls` errorCode=success | spath output=arn userIdentity.arn | stats earliest(_time) as firstTime latest(_time) as lastTime by arn | outputlookup previously_seen_ec2_modifications_by_user | stats count - -[ESCU - Previously Seen Running Windows Services - Initial] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen Running Windows Services - Initial -description = This collects the services that have been started across your entire enterprise. -action.escu.creation_date = 2020-06-23 -action.escu.modification_date = 2020-06-23 -action.escu.analytic_story = ["Orangeworm Attack Group", "Windows Service Abuse", "NOBELIUM Group"] -action.escu.data_models = [] -cron_schedule = 0 1 1 1,4,7,10 * -enableSched = 1 -dispatch.earliest_time = -90d@d -dispatch.latest_time = -1d@d -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This collects the services that have been started across your entire enterprise. -action.escu.how_to_implement = While this search does not require you to adhere to Splunk CIM, you must be ingesting your Windows security-event logs for it to execute successfully. Please ensure that the Splunk Add-on for Microsoft Windows is version 8.0.0 or above. -disabled = true -is_visible = false -search = `wineventlog_system` EventCode=7036 | rex field=Message "The (?[-\(\)\s\w]+) service entered the (?\w+) state" | where state="running" | stats earliest(_time) as firstTimeSeen, latest(_time) as lastTimeSeen by service | outputlookup previously_seen_running_windows_services - -[ESCU - Previously Seen Running Windows Services - Update] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen Running Windows Services - Update -description = This search returns the first and last time a Windows service was seen across your enterprise within the last hour. It then updates this information with historical data and filters out Windows services pairs that have not been seen within the specified time window. This updated table is then cached. -action.escu.creation_date = 2020-06-23 -action.escu.modification_date = 2020-06-23 -action.escu.analytic_story = ["Orangeworm Attack Group", "Windows Service Abuse", "NOBELIUM Group"] -action.escu.data_models = [] -cron_schedule = 55 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search returns the first and last time a Windows service was seen across your enterprise within the last hour. It then updates this information with historical data and filters out Windows services pairs that have not been seen within the specified time window. This updated table is then cached. -action.escu.how_to_implement = While this search does not require you to adhere to Splunk CIM, you must be ingesting your Windows security-event logs for it to execute successfully. Please ensure that the Splunk Add-on for Microsoft Windows is version 8.0.0 or above. -disabled = true -is_visible = false -search = `wineventlog_system` EventCode=7036 | rex field=Message "The (?[-\(\)\s\w]+) service entered the (?\w+) state" | where state="running" | stats earliest(_time) as firstTimeSeen, latest(_time) as lastTimeSeen by service | inputlookup previously_seen_running_windows_services append=t | stats min(firstTimeSeen) as firstTimeSeen, max(lastTimeSeen) as lastTimeSeen by service | where lastTimeSeen > relative_time(now(), "`previously_seen_windows_service_forget_window`") | outputlookup previously_seen_running_windows_services - [ESCU - Previously Seen Users In CloudTrail - Update] action.escu = 0 action.escu.enabled = 1 @@ -2834,7 +2192,7 @@ schedule_window = auto action.escu.providing_technologies = [] action.escu.eli5 = This search looks for CloudTrail events where a user logs into the console, then updates the baseline of the latest and earliest times, City, Region, and Country we have encountered this user in our dataset, grouped by user, within the last hour. action.escu.how_to_implement = You must install and configure the Splunk Add-on for AWS (version 5.1.0 or later) and Enterprise Security 6.2, which contains the required updates to the Authentication data model for cloud use cases. Validate the user name entries in `previously_seen_users_console_logins`, which is a lookup file created by this support search. -disabled = true +disabled = false is_visible = false search = | tstats earliest(_time) as firstTime latest(_time) as lastTime from datamodel=Authentication where Authentication.signature=ConsoleLogin by Authentication.user Authentication.src | iplocation Authentication.src | rename Authentication.user as user Authentication.src as src | table user src City Region Country firstTime lastTime | inputlookup append=t previously_seen_users_console_logins | stats min(firstTime) as firstTime max(lastTime) as lastTime by user src City Region Country | outputlookup previously_seen_users_console_logins @@ -2856,230 +2214,10 @@ schedule_window = auto action.escu.providing_technologies = [] action.escu.eli5 = This search looks for CloudTrail events where a user logs into the console, then creates a baseline of the latest and earliest times, City, Region, and Country we have encountered this user in our dataset, grouped by username, within the last 30 days. action.escu.how_to_implement = You must install and configure the Splunk Add-on for AWS (version 5.1.0 or later) and Enterprise Security 6.2, which contains the required updates to the Authentication data model for cloud use cases. Validate the user name entries in `previously_seen_users_console_logins`, which is a lookup file created by this support search. -disabled = true +disabled = false is_visible = false search = | tstats earliest(_time) as firstTime latest(_time) as lastTime from datamodel=Authentication where Authentication.signature=ConsoleLogin by Authentication.user Authentication.src | iplocation Authentication.src | rename Authentication.user as user Authentication.src as src | table user src City Region Country firstTime lastTime | outputlookup previously_seen_users_console_logins | stats count -[ESCU - Previously Seen Zoom Child Processes - Initial] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen Zoom Child Processes - Initial -description = This search returns the first and last time a process was seen per endpoint with a parent process of zoom.exe (Windows) or zoom.us (macOS). This table is then cached. -action.escu.creation_date = 2020-05-20 -action.escu.modification_date = 2020-05-20 -action.escu.analytic_story = ["Suspicious Zoom Child Processes"] -action.escu.data_models = ["Endpoint"] -cron_schedule = 0 1 1 1,4,7,10 * -enableSched = 1 -dispatch.earliest_time = -90d@d -dispatch.latest_time = -1d@d -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search returns the first and last time a process was seen per endpoint with a parent process of zoom.exe (Windows) or zoom.us (macOS). This table is then cached. -action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints, to populate the Endpoint data model in the Processes node. -disabled = true -is_visible = false -search = | tstats `security_content_summariesonly` min(_time) as firstTimeSeen max(_time) as lastTimeSeen from datamodel=Endpoint.Processes where (Processes.parent_process_name=zoom.exe OR Processes.parent_process_name=zoom.us) by Processes.process_name Processes.dest| `drop_dm_object_name(Processes)` | table dest, process_name, firstTimeSeen, lastTimeSeen | outputlookup zoom_first_time_child_process - -[ESCU - Previously Seen Zoom Child Processes - Update] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen Zoom Child Processes - Update -description = This search returns the first and last time a process was seen per endpoint with a parent process of zoom.exe (Windows) or zoom.us (macOS) within the last hour. It then updates this information with historical data and filters out proces_name and endpoint pairs that have not been seen within the specified time window. This updated table is outputed to disk. -action.escu.creation_date = 2020-05-20 -action.escu.modification_date = 2020-05-20 -action.escu.analytic_story = ["Suspicious Zoom Child Processes"] -action.escu.data_models = ["Endpoint"] -cron_schedule = 55 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search returns the first and last time a process was seen per endpoint with a parent process of zoom.exe (Windows) or zoom.us (macOS) within the last hour. It then updates this information with historical data and filters out proces_name and endpoint pairs that have not been seen within the specified time window. This updated table is outputed to disk. -action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints, to populate the Endpoint data model in the Processes node. -disabled = true -is_visible = false -search = | tstats `security_content_summariesonly` min(_time) as firstTimeSeen max(_time) as lastTimeSeen from datamodel=Endpoint.Processes where (Processes.parent_process_name=zoom.exe OR Processes.parent_process_name=zoom.us) by Processes.process_name Processes.dest| `drop_dm_object_name(Processes)` | table firstTimeSeen, lastTimeSeen, process_name, dest | inputlookup zoom_first_time_child_process append=t | stats min(firstTimeSeen) as firstTimeSeen max(lastTimeSeen) as lastTimeSeen by process_name, dest | where lastTimeSeen > relative_time(now(), "`previously_seen_zoom_child_processes_forget_window`") | outputlookup zoom_first_time_child_process - -[ESCU - Previously seen API call per user roles in CloudTrail] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously seen API call per user roles in CloudTrail -description = This search looks for successful API calls made by different user roles, then creates a baseline of the earliest and latest times we have encountered this user role. It also returns the name of the API call in our dataset--grouped by user role and name of the API call--that occurred within the last 30 days. In this support search, we are only looking for events where the user identity is Assumed Role. -action.escu.creation_date = 2018-04-16 -action.escu.modification_date = 2018-04-16 -action.escu.analytic_story = ["AWS User Monitoring"] -action.escu.data_models = [] -cron_schedule = 0 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search looks for successful API calls made by different user roles, then creates a baseline of the earliest and latest times we have encountered this user role. It also returns the name of the API call in our dataset--grouped by user role and name of the API call--that occurred within the last 30 days. In this support search, we are only looking for events where the user identity is Assumed Role. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the user role entries in `previously_seen_api_calls_from_user_roles.csv`, which is a lookup file created as a result of running this support search. -disabled = true -is_visible = false -search = `cloudtrail` eventType=AwsApiCall errorCode=success userIdentity.type=AssumedRole | stats earliest(_time) as earliest latest(_time) as latest by userName eventName | outputlookup previously_seen_api_calls_from_user_roles | stats count - -[ESCU - Previously seen S3 bucket access by remote IP] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously seen S3 bucket access by remote IP -description = This search looks for successful access to S3 buckets from remote IP addresses, then creates a baseline of the earliest and latest times we have encountered this remote IP within the last 30 days. In this support search, we are only looking for S3 access events where the HTTP response code from AWS is "200" -action.escu.creation_date = 2018-06-28 -action.escu.modification_date = 2018-06-28 -action.escu.analytic_story = ["Suspicious AWS S3 Activities"] -action.escu.data_models = [] -cron_schedule = 0 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search looks for successful access to S3 buckets from remote IP addresses, then creates a baseline of the earliest and latest times we have encountered this remote IP within the last 30 days. In this support search, we are only looking for S3 access events where the HTTP response code from AWS is "200" -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your S3 access-logs inputs. You must validate the remote IP and bucket name entries in `previously_seen_S3_access_from_remote_ip.csv`, which is a lookup file created as a result of running this support search. -disabled = true -is_visible = false -search = `aws_s3_accesslogs` http_status=200 | stats earliest(_time) as earliest latest(_time) as latest by bucket_name remote_ip | outputlookup previously_seen_S3_access_from_remote_ip | stats count - -[ESCU - Previously seen command line arguments] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously seen command line arguments -description = This search looks for command-line arguments where `cmd.exe /c` is used to execute a program, then creates a baseline of the earliest and latest times we have encountered this command-line argument in our dataset within the last 30 days. -action.escu.creation_date = 2019-03-01 -action.escu.modification_date = 2019-03-01 -action.escu.analytic_story = ["DHS Report TA18-074A", "Disabling Security Tools", "Hidden Cobra Malware", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Suspicious Command-Line Executions", "Suspicious MSHTA Activity"] -action.escu.data_models = ["Endpoint"] -cron_schedule = 0 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search looks for command-line arguments where `cmd.exe /c` is used to execute a program, then creates a baseline of the earliest and latest times we have encountered this command-line argument in our dataset within the last 30 days. -action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must be ingesting logs with both the process name and command line from your endpoints. The complete process name with command-line arguments are mapped to the "process" field in the Endpoint data model. -disabled = true -is_visible = false -search = | tstats `security_content_summariesonly` min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=cmd.exe AND Processes.process="* /c *" by Processes.process | `drop_dm_object_name(Processes)` - -[ESCU - Previously seen users in CloudTrail] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously seen users in CloudTrail -description = This search looks for CloudTrail events where a user logs into the console, then creates a baseline of the latest and earliest times, City, Region, and Country we have encountered this user in our dataset, grouped by ARN, within the last 30 days. NOTE - This baseline search is deprecated and has been updated to use the Authentication Datamodel -action.escu.creation_date = 2018-04-30 -action.escu.modification_date = 2018-04-30 -action.escu.analytic_story = ["Suspicious AWS Login Activities"] -action.escu.data_models = [] -cron_schedule = 0 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search looks for CloudTrail events where a user logs into the console, then creates a baseline of the latest and earliest times, City, Region, and Country we have encountered this user in our dataset, grouped by ARN, within the last 30 days. NOTE - This baseline search is deprecated and has been updated to use the Authentication Datamodel -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the user name entries in `previously_seen_users_console_logins_cloudtrail`, which is a lookup file created as a result of running this support search. -disabled = true -is_visible = false -search = `cloudtrail` eventName=ConsoleLogin | rename userIdentity.arn as user | iplocation src | eval City=if(City LIKE "",src,City),Region=if(Region LIKE "",src,Region) | stats earliest(_time) as firstTime latest(_time) as lastTime by user src City Region Country | outputlookup previously_seen_users_console_logins_cloudtrail | stats count - -[ESCU - Systems Ready for Spectre-Meltdown Windows Patch] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Systems Ready for Spectre-Meltdown Windows Patch -description = Some AV applications can cause the Spectre/Meltdown patch for Windows not to install successfully. This registry key is supposed to be created by the AV engine when it has been patched to be able to handle the Windows patch. If this key has been written, the system can then be patched for Spectre and Meltdown. -action.escu.creation_date = 2018-01-08 -action.escu.modification_date = 2018-01-08 -action.escu.analytic_story = ["Spectre And Meltdown Vulnerabilities"] -action.escu.data_models = [] -cron_schedule = 0 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = Some AV applications can cause the Spectre/Meltdown patch for Windows not to install successfully. This registry key is supposed to be created by the AV engine when it has been patched to be able to handle the Windows patch. If this key has been written, the system can then be patched for Spectre and Meltdown. -action.escu.how_to_implement = You need to be ingesting logs with both the process name and command-line from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. -disabled = true -is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Change_Analysis.All_Changes where All_Changes.object_category=registry AND (All_Changes.object_path="HKLM\Software\Microsoft\Windows\CurrentVersion\QualityCompat*") by All_Changes.dest, All_Changes.command, All_Changes.user, All_Changes.object, All_Changes.object_path | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `drop_dm_object_name("All_Changes")` - -[ESCU - Update previously seen users in CloudTrail] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Update previously seen users in CloudTrail -description = This search looks for CloudTrail events where a user logs into the console, then updates the baseline of the latest and earliest times, City, Region, and Country we have encountered this user in our dataset, grouped by ARN, within the last hour. NOTE - This baseline search is deprecated and has been updated to use the Authentication Datamodel -action.escu.creation_date = 2018-04-30 -action.escu.modification_date = 2018-04-30 -action.escu.analytic_story = ["Suspicious AWS Login Activities"] -action.escu.data_models = [] -cron_schedule = 0 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search looks for CloudTrail events where a user logs into the console, then updates the baseline of the latest and earliest times, City, Region, and Country we have encountered this user in our dataset, grouped by ARN, within the last hour. NOTE - This baseline search is deprecated and has been updated to use the Authentication Datamodel -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the user name entries in `previously_seen_users_console_logins_cloudtrail`, which is a lookup file created as a result of running this support search. -disabled = true -is_visible = false -search = `cloudtrail` eventName=ConsoleLogin | rename userIdentity.arn as user | iplocation src | eval City=if(City LIKE "",src,City),Region=if(Region LIKE "",src,Region) | stats earliest(_time) AS firstTime latest(_time) AS lastTime by user src City Region Country | inputlookup append=t previously_seen_users_console_logins_cloudtrail | stats min(firstTime) as firstTime max(lastTime) as lastTime by user src City Region Country | outputlookup previously_seen_users_console_logins_cloudtrail - -[ESCU - Windows Updates Install Failures] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Windows Updates Install Failures -description = This search is intended to give you a feel for how often Windows updates fail to install in your environment. Fluctuations in these numbers will allow you to determine when you should be concerned. -action.escu.creation_date = 2017-09-14 -action.escu.modification_date = 2017-09-14 -action.escu.analytic_story = [] -action.escu.data_models = [] -cron_schedule = 0 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search is intended to give you a feel for how often Windows updates fail to install in your environment. Fluctuations in these numbers will allow you to determine when you should be concerned. -action.escu.how_to_implement = You must be ingesting your Windows Update Logs -disabled = true -is_visible = false -search = | tstats `security_content_summariesonly` dc(Updates.dest) as count FROM datamodel=Updates where Updates.vendor_product="Microsoft Windows" AND Updates.status=failure by _time span=1d - -[ESCU - Windows Updates Install Successes] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Windows Updates Install Successes -description = This search is intended to give you a feel for how often successful Windows updates are applied in your environments. Fluctuations in these numbers will allow you to determine when you should be concerned. -action.escu.creation_date = 2017-09-14 -action.escu.modification_date = 2017-09-14 -action.escu.analytic_story = [] -action.escu.data_models = [] -cron_schedule = 0 * * * * -enableSched = 1 -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search is intended to give you a feel for how often successful Windows updates are applied in your environments. Fluctuations in these numbers will allow you to determine when you should be concerned. -action.escu.how_to_implement = You must be ingesting your Windows Update Logs -disabled = true -is_visible = false -search = | tstats `security_content_summariesonly` dc(Updates.dest) as count FROM datamodel=Updates where Updates.vendor_product="Microsoft Windows" AND Updates.status=installed by _time span=1d - ### ESCU RESPONSE TASKS ### @@ -3210,27 +2348,6 @@ schedule_window = auto is_visible = false search = | search sourcetype=aws:config | rename resourceId as bucketName |search bucketName=$bucketName$ | table resourceCreationTime bucketName vendor_region action aws_account_id supplementaryConfiguration.AccessControlList -[ESCU - All backup logs for host - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - All backup logs for host - Response Task -description = Retrieve the backup logs for the last 2 weeks for a specific host in order to investigate why backups are not completing successfully. -action.escu.creation_date = 2017-09-12 -action.escu.modification_date = 2017-09-12 -action.escu.analytic_story = ["Monitor Backup Solution"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = Retrieve the backup logs for the last 2 weeks for a specific host in order to investigate why backups are not completing successfully. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | search sourcetype="netbackup_logs" dest=$dest$ - [ESCU - Amazon EKS Kubernetes activity by src ip - Response Task] action.escu = 0 action.escu.enabled = 1 @@ -3252,27 +2369,6 @@ schedule_window = auto is_visible = false search = sourcetype="aws:cloudwatchlogs:eks" |rename sourceIPs{} as src_ip |search src_ip=$src_ip$ | stats count min(_time) as firstTime max(_time) as lastTime values(user.username) values(requestURI) values(verb) values(userAgent) by source annotations.authorization.k8s.io/decision src_ip -[ESCU - GCP Kubernetes activity by src ip - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - GCP Kubernetes activity by src ip - Response Task -description = This search provides investigation data about requests via user agent, authentication request URI, resource path and cluster name data against Kubernetes cluster from a specific IP address -action.escu.creation_date = 2020-04-13 -action.escu.modification_date = 2020-04-13 -action.escu.analytic_story = ["Kubernetes Scanning Activity"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search provides investigation data about requests via user agent, authentication request URI, resource path and cluster name data against Kubernetes cluster from a specific IP address -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = sourcetype="google:gcp:pubsub:message" | rename data.protoPayload.requestMetadata.callerIp as src_ip | search src_ip =$src_ip$ | stats count min(_time) as firstTime max(_time) as lastTime values(data.protoPayload.methodName) as method_names values(data.protoPayload.resourceName) as resource_name values(data.protoPayload.requestMetadata.callerSuppliedUserAgent) as http_user_agent values(data.protoPayload.authenticationInfo.principalEmail) as user values(data.protoPayload.status.message) by src_ip data.resource.labels.cluster_name data.resource.type - [ESCU - Get All AWS Activity From City - Response Task] action.escu = 0 action.escu.enabled = 1 @@ -3357,90 +2453,6 @@ schedule_window = auto is_visible = false search = | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search Region=$Region$ | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, Region, user, userName, userType, src_ip, awsRegion, eventName, errorCode -[ESCU - Get Backup Logs For Endpoint - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Backup Logs For Endpoint - Response Task -description = This search will tell you the backup status from your netbackup_logs of a specific endpoint for the last week. -action.escu.creation_date = 2017-09-14 -action.escu.modification_date = 2017-09-14 -action.escu.analytic_story = ["Ransomware", "SamSam Ransomware"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search will tell you the backup status from your netbackup_logs of a specific endpoint for the last week. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | search sourcetype="netbackup_logs" COMPUTERNAME=$dest$ | rename COMPUTERNAME as dest, MESSAGE as signature | table _time, dest, signature - -[ESCU - Get Certificate logs for a domain - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Certificate logs for a domain - Response Task -description = This search queries the Certificates datamodel and give you all the information for a specific domain. Please note that the certificates issued by "Let's Encrypt" are widely used by attackers. -action.escu.creation_date = 2019-04-29 -action.escu.modification_date = 2019-04-29 -action.escu.analytic_story = ["Common Phishing Frameworks"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search queries the Certificates datamodel and give you all the information for a specific domain. Please note that the certificates issued by "Let's Encrypt" are widely used by attackers. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Certificates.All_Certificates where All_Certificates.SSL.ssl_subject_common_name=*$domain$ by All_Certificates.dest All_Certificates.src All_Certificates.SSL.ssl_issuer_common_name All_Certificates.SSL.ssl_subject_common_name All_Certificates.SSL.ssl_hash | `drop_dm_object_name(All_Certificates)` | `drop_dm_object_name(SSL)` | rename ssl_subject_common_name as domain | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - -[ESCU - Get DNS Server History for a host - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get DNS Server History for a host - Response Task -description = While investigating any detections it is important to understand which and how many DNS servers a host has connected to in the past. This search uses data that is tagged as DNS and gives you a count and list of DNS servers that a particular host has connected to the previous 24 hours. -action.escu.creation_date = 2017-11-09 -action.escu.modification_date = 2017-11-09 -action.escu.analytic_story = ["AWS Network ACL Activity", "Command and Control", "DNS Hijacking", "Data Protection", "Dynamic DNS", "Hidden Cobra Malware", "Host Redirection", "Prohibited Traffic Allowed or Protocol Mismatch", "Suspicious AWS Traffic", "Suspicious DNS Traffic"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = While investigating any detections it is important to understand which and how many DNS servers a host has connected to in the past. This search uses data that is tagged as DNS and gives you a count and list of DNS servers that a particular host has connected to the previous 24 hours. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | search tag=dns src_ip=$src_ip$ dest_port=53 | streamstats time_window=1d count values(dest_ip) as dcip by src_ip | table date_mday src_ip dcip count | sort -count - -[ESCU - Get DNS traffic ratio - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get DNS traffic ratio - Response Task -description = This search calculates the ratio of DNS traffic originating and coming from a host to a list of DNS servers over the last 24 hours. A high value of this ratio could be very useful to quickly understand if a src_ip (host) is sending a high volume of data out via port 53, could be an indicator of data exfiltration via DNS. -action.escu.creation_date = 2017-11-09 -action.escu.modification_date = 2017-11-09 -action.escu.analytic_story = ["AWS Network ACL Activity", "Command and Control", "Data Protection", "Dynamic DNS", "Hidden Cobra Malware", "Suspicious AWS Traffic", "Suspicious DNS Traffic"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = ["Network_Traffic"] -action.escu.eli5 = This search calculates the ratio of DNS traffic originating and coming from a host to a list of DNS servers over the last 24 hours. A high value of this ratio could be very useful to quickly understand if a src_ip (host) is sending a high volume of data out via port 53, could be an indicator of data exfiltration via DNS. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | tstats allow_old_summaries=true sum(All_Traffic.bytes_out) as "bytes_out" sum(All_Traffic.bytes_in) as "bytes_in" from datamodel=Network_Traffic where nodename=All_Traffic All_Traffic.dest_port=53 by All_Traffic.src All_Traffic.dest| `drop_dm_object_name(All_Traffic)` | rename src as src_ip | rename dest as dest_ip | search src_ip=$src_ip$ | search dest_ip = $dest_ip | eval ratio = (bytes_out/bytes_in) | table ratio - [ESCU - Get EC2 Instance Details by instanceId - Response Task] action.escu = 0 action.escu.enabled = 1 @@ -3483,321 +2495,6 @@ schedule_window = auto is_visible = false search = | search sourcetype=aws:cloudtrail dest=$dest$ |rename userIdentity.arn as arn, responseElements.instancesSet.items{}.instanceId as dest, responseElements.instancesSet.items{}.privateIpAddress as privateIpAddress, responseElements.instancesSet.items{}.imageId as amiID, responseElements.instancesSet.items{}.architecture as architecture, responseElements.instancesSet.items{}.keyName as keyName | table arn, awsRegion, dest, architecture, privateIpAddress, amiID, keyName -[ESCU - Get Email Info - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Email Info - Response Task -description = This search returns all the information Splunk might have collected a specific email message over the last 2 hours. -action.escu.creation_date = 2017-11-09 -action.escu.modification_date = 2017-11-09 -action.escu.analytic_story = ["Brand Monitoring", "Suspicious Emails"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search returns all the information Splunk might have collected a specific email message over the last 2 hours. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | from datamodel Email.All_Email | search message_id=$message_id$ - -[ESCU - Get Emails From Specific Sender - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Emails From Specific Sender - Response Task -description = This search returns all the emails from a specific sender over the last 24 and next hours. -action.escu.creation_date = 2017-11-09 -action.escu.modification_date = 2017-11-09 -action.escu.analytic_story = ["Brand Monitoring", "Suspicious Emails", "Web Fraud Detection"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search returns all the emails from a specific sender over the last 24 and next hours. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | from datamodel Email.All_Email | search src_user=$src_user$ - -[ESCU - Get First Occurrence and Last Occurrence of a MAC Address - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get First Occurrence and Last Occurrence of a MAC Address - Response Task -description = This search allows you to gather more context around a notable which has detected a new device connecting to your network. Use this search to determine the first and last occurrences of the suspicious device attempting to connect with your network. -action.escu.creation_date = 2017-09-13 -action.escu.modification_date = 2017-09-13 -action.escu.analytic_story = ["Asset Tracking"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = ["Network_Sessions"] -action.escu.eli5 = This search allows you to gather more context around a notable which has detected a new device connecting to your network. Use this search to determine the first and last occurrences of the suspicious device attempting to connect with your network. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Network_Sessions where nodename=All_Sessions.DHCP All_Sessions.signature=DHCPREQUEST All_Sessions.All_Sessions.src_mac= $src_mac$ by All_Sessions.src_ip All_Sessions.user | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` - -[ESCU - Get History Of Email Sources - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get History Of Email Sources - Response Task -description = This search returns a list of all email sources seen in the 48 hours prior to the notable event to 24 hours after, and the number of emails from each source. -action.escu.creation_date = 2019-02-21 -action.escu.modification_date = 2019-02-21 -action.escu.analytic_story = ["Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Lateral Movement", "Malicious PowerShell", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Ransomware", "SamSam Ransomware"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = ["Email"] -action.escu.eli5 = This search returns a list of all email sources seen in the 48 hours prior to the notable event to 24 hours after, and the number of emails from each source. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = |tstats `security_content_summariesonly` values(All_Email.dest) as dest values(All_Email.recipient) as recepient min(_time) as firstTime max(_time) as lastTime count from datamodel=Email.All_Email by All_Email.src |`drop_dm_object_name(All_Email)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | search src=$src$ - -[ESCU - Get Logon Rights Modifications For Endpoint - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Logon Rights Modifications For Endpoint - Response Task -description = This search allows you to retrieve any modifications to logon rights associated with a specific host. -action.escu.creation_date = 2017-09-12 -action.escu.modification_date = 2017-09-12 -action.escu.analytic_story = ["Account Monitoring and Controls"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search allows you to retrieve any modifications to logon rights associated with a specific host. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | search eventtype=wineventlog_security (signature_id=4718 OR signature_id=4717) dest=$dest$ | rename user as "Account Modified" | table _time, dest, "Account Modified", Access_Right, signature - -[ESCU - Get Logon Rights Modifications For User - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Logon Rights Modifications For User - Response Task -description = This search allows you to retrieve any modifications to logon rights for a specific user account. -action.escu.creation_date = 2019-02-27 -action.escu.modification_date = 2019-02-27 -action.escu.analytic_story = ["Account Monitoring and Controls"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search allows you to retrieve any modifications to logon rights for a specific user account. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | search eventtype=wineventlog_security (signature_id=4718 OR signature_id=4717) user=$user$ | rename user as "Account Modified" | table _time, dest, "Account Modified", Access_Right, signature - -[ESCU - Get Notable History - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Notable History - Response Task -description = This search queries the notable index and returns all the Notable Events for the particular destination host, giving the analyst an overview of the incidents that may have occurred with the host under investigation. -action.escu.creation_date = 2017-09-20 -action.escu.modification_date = 2017-09-20 -action.escu.analytic_story = ["AWS Cross Account Activity", "AWS Cryptomining", "AWS Network ACL Activity", "AWS User Monitoring", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Asset Tracking", "Brand Monitoring", "Cloud Cryptomining", "ColdRoot MacOS RAT", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "DNS Amplification Attacks", "Data Protection", "Disabling Security Tools", "Dynamic DNS", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Host Redirection", "JBoss Vulnerability", "Kubernetes Scanning Activity", "Lateral Movement", "Malicious PowerShell", "Monitor Backup Solution", "Monitor for Unauthorized Software", "Monitor for Updates", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "Router and Infrastructure Security", "SQL Injection", "SamSam Ransomware", "Spectre And Meltdown Vulnerabilities", "Splunk Enterprise Vulnerability", "Splunk Enterprise Vulnerability CVE-2018-11409", "Suspicious AWS EC2 Activities", "Suspicious AWS S3 Activities", "Suspicious AWS Traffic", "Suspicious Cloud Authentication Activities", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual AWS EC2 Modifications", "Unusual Processes", "Use of Cleartext Protocols", "Web Fraud Detection", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse", "Data Exfiltration", "F5 TMUI RCE CVE-2020-5902", "Detect Zerologon Attack", "GCP Cross Account Activity", "Kubernetes Sensitive Object Access Activity", "Kubernetes Sensitive Role Activity", "Ransomware Cloud", "Ryuk Ransomware", "Suspicious Cloud Provisioning Activities", "Suspicious GCP Storage Activities", "Windows DNS SIGRed CVE-2020-1350"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search queries the notable index and returns all the Notable Events for the particular destination host, giving the analyst an overview of the incidents that may have occurred with the host under investigation. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | search `notable` | search dest=$dest$ | table _time, dest, rule_name, owner, priority, severity, status_description - -[ESCU - Get Outbound Emails to Hidden Cobra Threat Actors - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Outbound Emails to Hidden Cobra Threat Actors - Response Task -description = This search returns the information of the users that sent emails to the accounts controlled by the Hidden Cobra Threat Actors: specifically to `misswang8107@gmail.com`, and from `redhat@gmail.com`. -action.escu.creation_date = 2018-06-14 -action.escu.modification_date = 2018-06-14 -action.escu.analytic_story = ["Hidden Cobra Malware"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search returns the information of the users that sent emails to the accounts controlled by the Hidden Cobra Threat Actors: specifically to `misswang8107@gmail.com`, and from `redhat@gmail.com`. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | from datamodel Email.All_Email | search recipient=misswang8107@gmail.com OR src_user=redhat@gmail.com | stats count earliest(_time) as firstTime, latest(_time) as lastTime values(dest) values(src) by src_user recipient | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - -[ESCU - Get Parent Process Info - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Parent Process Info - Response Task -description = This search queries the Endpoint data model to give you details about the parent process of a process running on a host which is under investigation. Enter the values of the process name in question and the dest -action.escu.creation_date = 2019-02-28 -action.escu.modification_date = 2019-02-28 -action.escu.analytic_story = ["Collection and Staging", "Command and Control", "DHS Report TA18-074A", "Disabling Security Tools", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Lateral Movement", "Malicious PowerShell", "Monitor for Unauthorized Software", "Netsh Abuse", "Orangeworm Attack Group", "Phishing Payloads", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "SamSam Ransomware", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search queries the Endpoint data model to give you details about the parent process of a process running on a host which is under investigation. Enter the values of the process name in question and the dest -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | tstats `summariesonly` count values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes by Processes.user Processes.parent_process_name Processes.process_name Processes.dest | `drop_dm_object_name("Processes")` | search parent_process_name= $parent_process_name$ |search dest = $dest$ | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - -[ESCU - Get Process File Activity - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Process File Activity - Response Task -description = This search returns the file activity for a specific process on a specific endpoint -action.escu.creation_date = 2019-11-06 -action.escu.modification_date = 2019-11-06 -action.escu.analytic_story = ["DHS Report TA18-074A", "Suspicious Zoom Child Processes"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search returns the file activity for a specific process on a specific endpoint -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | tstats `security_content_summariesonly` values(Filesystem.file_name) as file_name values(Filesystem.dest) as dest, values(Filesystem.process_name) as process_name from datamodel=Endpoint.Filesystem by Filesystem.dest Filesystem.process_name Filesystem.file_path, Filesystem.action, _time | `drop_dm_object_name(Filesystem)` | search dest=$dest$ | search process_name=$process_name$ | table _time, process_name, dest, action, file_name, file_path - -[ESCU - Get Process Info - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Process Info - Response Task -description = This search queries the Endpoint data model to give you details about the process running on a host which is under investigation. To gather the process info, enter the values for the process name in question and the destination IP address. -action.escu.creation_date = 2019-04-01 -action.escu.modification_date = 2019-04-01 -action.escu.analytic_story = ["AWS Network ACL Activity", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "Data Protection", "Disabling Security Tools", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Lateral Movement", "Malicious PowerShell", "Monitor for Unauthorized Software", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "SamSam Ransomware", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search queries the Endpoint data model to give you details about the process running on a host which is under investigation. To gather the process info, enter the values for the process name in question and the destination IP address. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | tstats `summariesonly` count values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes by Processes.user Processes.parent_process_name Processes.process_name Processes.dest | `drop_dm_object_name("Processes")` | search process_name= $process_name$ | search dest = $dest$ | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - -[ESCU - Get Process Information For Port Activity - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Process Information For Port Activity - Response Task -description = This search will return information about the process associated with observed network traffic to a specific destination port from a specific host. -action.escu.creation_date = 2019-04-01 -action.escu.modification_date = 2019-04-01 -action.escu.analytic_story = ["AWS Network ACL Activity", "Command and Control", "DHS Report TA18-074A", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Lateral Movement", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "SamSam Ransomware", "Suspicious AWS Traffic", "Use of Cleartext Protocols"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search will return information about the process associated with observed network traffic to a specific destination port from a specific host. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) max(_time) as lastTime from datamodel=Endpoint.Processes by Processes.process_name Processes.user Processes.dest Processes.process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | search dest=$dest$ | join dest type=inner [| tstats `security_content_summariesonly` count from datamodel=Endpoint.Ports by Ports.process_id Ports.src Ports.dest_port | `drop_dm_object_name(Ports)` | search dest_port=$dest_port$ | rename src as dest] - -[ESCU - Get Process Responsible For The DNS Traffic - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Process Responsible For The DNS Traffic - Response Task -description = While investigating, an analyst will want to know what process and parent_process is responsible for generating suspicious DNS traffic. Use the following search and enter the value of `dest` in the search to get specific details on the process responsible for creating the DNS traffic. -action.escu.creation_date = 2019-04-01 -action.escu.modification_date = 2019-04-01 -action.escu.analytic_story = ["AWS Network ACL Activity", "Brand Monitoring", "Command and Control", "Data Protection", "Dynamic DNS", "Hidden Cobra Malware", "Suspicious AWS Traffic", "Suspicious DNS Traffic"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = While investigating, an analyst will want to know what process and parent_process is responsible for generating suspicious DNS traffic. Use the following search and enter the value of `dest` in the search to get specific details on the process responsible for creating the DNS traffic. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) max(_time) as lastTime from datamodel=Endpoint.Processes by Processes.parent_process Processes.process_name Processes.user Processes.dest Processes.process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | search dest = $dest$ | join dest type=inner [| tstats `security_content_summariesonly` count from datamodel=Endpoint.Ports where Ports.dest_port=53 by Ports.process_id Ports.src | `drop_dm_object_name(Ports)` | rename src as dest] - -[ESCU - Get Sysmon WMI Activity for Host - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Sysmon WMI Activity for Host - Response Task -description = This search queries Sysmon WMI events for the host of interest. -action.escu.creation_date = 2018-10-23 -action.escu.modification_date = 2018-10-23 -action.escu.analytic_story = ["Ransomware", "Suspicious WMI Use"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search queries Sysmon WMI events for the host of interest. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = sourcetype="XmlWinEventLog:Microsoft-Windows-Sysmon/Operational" EventCode>18 EventCode<22 | rename host as dest | search dest=$dest$| table _time, dest, user, Name, Operation, EventType, Type, Query, Consumer, Filter - -[ESCU - Get Web Session Information via session id - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Web Session Information via session id - Response Task -description = This search helps an analyst investigate a notable event to find out more about a specific web session. The search looks for a specific web session ID in the HTTP web traffic and outputs the URL and user agents, grouped by source IP address and HTTP status code. -action.escu.creation_date = 2018-10-08 -action.escu.modification_date = 2018-10-08 -action.escu.analytic_story = ["Web Fraud Detection"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search helps an analyst investigate a notable event to find out more about a specific web session. The search looks for a specific web session ID in the HTTP web traffic and outputs the URL and user agents, grouped by source IP address and HTTP status code. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | search sourcetype=stream:http session_id = $session_id$ | stats values(url) values(http_user_agent) by src_ip status - [ESCU - Investigate AWS User Activities by user field - Response Task] action.escu = 0 action.escu.enabled = 1 @@ -3840,237 +2537,6 @@ schedule_window = auto is_visible = false search = | search sourcetype=aws:cloudtrail vendor_region=$vendor_region$| rename requestParameters.instancesSet.items{}.instanceId as instanceId | stats values(eventName) by user instanceId vendor_region -[ESCU - Investigate Failed Logins for Multiple Destinations - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Failed Logins for Multiple Destinations - Response Task -description = This search returns failed logins to multiple destinations by user. -action.escu.creation_date = 2019-12-10 -action.escu.modification_date = 2019-12-10 -action.escu.analytic_story = ["Credential Dumping"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = ["Authentication"] -action.escu.eli5 = This search returns failed logins to multiple destinations by user. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | tstats count `security_content_summariesonly` earliest(_time) as first_login latest(_time) as last_login dc(Authentication.dest) AS distinct_count_dest values(Authentication.dest) AS Authentication.dest values(Authentication.app) AS Authentication.app from datamodel=Authentication where Authentication.action=failure by Authentication.user | where distinct_count_dest > 1 | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` | `drop_dm_object_name("Authentication")` | search user=$user$ - -[ESCU - Investigate Network Traffic From src ip - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Network Traffic From src ip - Response Task -description = This search allows you to find all the network traffic from a specific IP address. -action.escu.creation_date = 2018-06-15 -action.escu.modification_date = 2018-06-15 -action.escu.analytic_story = ["ColdRoot MacOS RAT", "Splunk Enterprise Vulnerability CVE-2018-11409"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search allows you to find all the network traffic from a specific IP address. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | from datamodel Network_Traffic.All_Traffic | search src_ip=$src_ip$ - -[ESCU - Investigate Okta Activity by IP Address - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Okta Activity by IP Address - Response Task -description = This search returns all okta events from a specific IP address. -action.escu.creation_date = 2020-04-02 -action.escu.modification_date = 2020-04-02 -action.escu.analytic_story = ["Suspicious Okta Activity"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search returns all okta events from a specific IP address. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = eventtype=okta_log src_ip={src_ip} | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, displayMessage, app, src_ip, state, city, result, outcome.reason - -[ESCU - Investigate Okta Activity by app - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Okta Activity by app - Response Task -description = This search returns all okta events associated with a specific app -action.escu.creation_date = 2020-04-02 -action.escu.modification_date = 2020-04-02 -action.escu.analytic_story = ["Suspicious Okta Activity"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search returns all okta events associated with a specific app -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = eventtype=okta_log app=$app$ | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, displayMessage, app, src_ip, state, city, result, outcome.reason - -[ESCU - Investigate Pass the Hash Attempts - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Pass the Hash Attempts - Response Task -description = This search hunts for dumped NTLM hashes used for pass the hash. -action.escu.creation_date = 2019-12-10 -action.escu.modification_date = 2019-12-10 -action.escu.analytic_story = ["Credential Dumping"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search hunts for dumped NTLM hashes used for pass the hash. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = `wineventlog_security` EventCode=4624 Logon_Type=9 AuthenticationPackageName=Negotiate | stats count earliest(_time) as first_login latest(_time) as last_login by src_user dest | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` | search dest=$dest$ - -[ESCU - Investigate Pass the Ticket Attempts - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Pass the Ticket Attempts - Response Task -description = This search hunts for dumped kerberos ticket from LSASS memory. -action.escu.creation_date = 2019-12-10 -action.escu.modification_date = 2019-12-10 -action.escu.analytic_story = ["Credential Dumping"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search hunts for dumped kerberos ticket from LSASS memory. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = `wineventlog_security` EventCode=4768 OR EventCode=4769 | rex field=user "(?[^\@]+)" | stats count BY new_user, dest, EventCode | stats max(count) AS max_count sum(count) AS sum_count BY new_user, dest| search dest=$dest$ | where sum_count/max_count!=2 | rename new_user AS user - -[ESCU - Investigate Previous Unseen User - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Previous Unseen User - Response Task -description = This search returns previous unseen user, which didn't log in for 30 days. -action.escu.creation_date = 2019-12-10 -action.escu.modification_date = 2019-12-10 -action.escu.analytic_story = ["Credential Dumping"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = ["Authentication"] -action.escu.eli5 = This search returns previous unseen user, which didn't log in for 30 days. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | tstats count `security_content_summariesonly` earliest(_time) as first_login latest(_time) as last_login values(Authentication.dest) AS Authentication.dest values(Authentication.app) AS Authentication.app values(Authentication.action) AS Authentication.action from datamodel=Authentication where Authentication.action=success by _time, Authentication.user | bucket _time span=30d | stats count min(first_login) as first_login max(last_login) as last_login values(Authentication.dest) AS Authentication.dest by Authentication.user | where count=1 | where first_login >= relative_time(now(), "-30d") | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` | `drop_dm_object_name("Authentication")` | search dest=$dest$ - -[ESCU - Investigate Successful Remote Desktop Authentications - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Successful Remote Desktop Authentications - Response Task -description = This search returns the source, destination, and user for all successful remote-desktop authentications. A successful authentication after a brute-force attack on a destination machine is suspicious behavior. -action.escu.creation_date = 2018-12-14 -action.escu.modification_date = 2018-12-14 -action.escu.analytic_story = ["Hidden Cobra Malware", "Lateral Movement", "SamSam Ransomware"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = ["Authentication"] -action.escu.eli5 = This search returns the source, destination, and user for all successful remote-desktop authentications. A successful authentication after a brute-force attack on a destination machine is suspicious behavior. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Authentication where Authentication.signature_id=4624 Authentication.app=win:remote by Authentication.src Authentication.dest Authentication.app Authentication.user Authentication.signature Authentication.src_nt_domain | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `drop_dm_object_name("Authentication")` | search dest=$dest$ | table firstTime lastTime src src_nt_domain dest user app count | sort count - -[ESCU - Investigate Suspicious Strings in HTTP Header - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Suspicious Strings in HTTP Header - Response Task -description = This search helps an analyst investigate a notable event related to a potential Apache Struts exploitation. To investigate, we will want to isolate and analyze the "payload" or the commands that were passed to the vulnerable hosts by creating a few regular expressions to carve out the commands focusing on common keywords from the payload, such as cmd.exe, /bin/bash and whois. The search returns these suspicious strings found in the HTTP logs of the system of interest. -action.escu.creation_date = 2017-10-20 -action.escu.modification_date = 2017-10-20 -action.escu.analytic_story = ["Apache Struts Vulnerability"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search helps an analyst investigate a notable event related to a potential Apache Struts exploitation. To investigate, we will want to isolate and analyze the "payload" or the commands that were passed to the vulnerable hosts by creating a few regular expressions to carve out the commands focusing on common keywords from the payload, such as cmd.exe, /bin/bash and whois. The search returns these suspicious strings found in the HTTP logs of the system of interest. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | search sourcetype=stream:http | search src_ip=$src_ip$ | search dest_ip=$dest_ip$ | eval cs_content_type_length = len(cs_content_type) | search cs_content_type_length > 100 | rex field="cs_content_type" (?cmd.exe) | eval suspicious_strings_found=if(match(cs_content_type, "application"), "True", "False") | rename suspicious_strings_found AS "Suspicious Content-Type Found" | fields "Suspicious Content-Type Found", dest_ip, src_ip, suspicious_strings, cs_content_type, cs_content_type_length, url - -[ESCU - Investigate User Activities In Okta - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate User Activities In Okta - Response Task -description = This search returns all okta events by a specific user -action.escu.creation_date = 2020-04-02 -action.escu.modification_date = 2020-04-02 -action.escu.analytic_story = ["Suspicious Okta Activity"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search returns all okta events by a specific user -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = eventtype=okta_log user=$user$ | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, displayMessage, app, src_ip, state, city, result, outcome.reason - -[ESCU - Investigate Web POSTs From src - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Web POSTs From src - Response Task -description = This investigative search retrieves POST requests from a specified source IP or hostname. Identifying the POST requests, as well as their associated destination URLs and user agent(s), may help you scope and characterize the suspicious traffic. -action.escu.creation_date = 2018-12-06 -action.escu.modification_date = 2018-12-06 -action.escu.analytic_story = ["Apache Struts Vulnerability"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = ["Web"] -action.escu.eli5 = This investigative search retrieves POST requests from a specified source IP or hostname. Identifying the POST requests, as well as their associated destination URLs and user agent(s), may help you scope and characterize the suspicious traffic. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | tstats `security_content_summariesonly` values(Web.url) as url from datamodel=Web by Web.src,Web.http_user_agent,Web.http_method | `drop_dm_object_name("Web")`| search http_method, "POST" | search src=$src$ - ### END ESCU RESPONSE TASKS ### diff --git a/dist/saaws/default/searchbnf.conf b/dist/saaws/default/searchbnf.conf deleted file mode 100644 index 2b074fb3fe..0000000000 --- a/dist/saaws/default/searchbnf.conf +++ /dev/null @@ -1,26 +0,0 @@ -[dnstwist-command] -syntax = dnstwist ()* -shortdesc = Perform word permutations on a domain, or list of domains -description = Perform domain permutations on a domain, provided list of domains or domains part of Splunk_SA_CIM lookups -usage = public -maintainer = Splunk Security Research -example1 = |dnstwist domainlist=domains.csv -comment1 = Performs word premutation on a list of domains provided under DA-ESS-ContentUpdate/lookup/domains.csv -example2 = |dnstwist domain=www.splunk.com -comment2 = Performs word premutation on a single domain -example3 = |dnstwist populate_from_cim=true -comment3 = Performs word premutation on cim_corporate_email_domains.csv and cim_corporate_web_domains.csv from Splunk_SA_CIM - -[dnstwist-options] -syntax = domainlist= | domain= | populate_from_cim= -description = Prove the name of a lookup file with the list of domains, or individual domain you want to create permutations of. - -# runstory functionality was migrated to: https://github.com/splunk/analytic_story_execution -# [runstory-command] -# syntax = runstory -# shortdesc = Run an analytic story -# description = Run all the detection searches in an analytic story -# maintainer = Splunk Security Research -# example1 = | runstory "Malicious PowerShell" -# example2 = | runstory "AWS Cryptomining" -# usage = public diff --git a/dist/saaws/default/transforms.conf b/dist/saaws/default/transforms.conf index 597edcde1d..5ece708b26 100644 --- a/dist/saaws/default/transforms.conf +++ b/dist/saaws/default/transforms.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security_content -# On Date: 2021-03-30T19:36:01 UTC +# On Date: 2021-04-12T22:03:03 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/dist/saaws/default/usage_searches.conf b/dist/saaws/default/usage_searches.conf deleted file mode 100644 index 0c8aa32c0a..0000000000 --- a/dist/saaws/default/usage_searches.conf +++ /dev/null @@ -1,73 +0,0 @@ -[escu-metrics-usage] -action.email.useNSSubject = 1 -alert.digest_mode = True -alert.suppress = 0 -alert.track = 0 -auto_summarize.dispatch.earliest_time = -1d@h -dispatchAs = user -search = index=_audit sourcetype="audittrail" \ -"ESCU - "\ -`comment("Find all the search names in the audittrail.")`\ -| stats count(search) by search savedsearch_name user\ -| eval usage=(if(savedsearch_name=="","Adhoc","Scheduled")) \ -`comment("If the savedsearch_name field in the audittrail is empty, the search was run adhoc. Otherwise it was run as a scheduled search")`\ -| rex field=search "\"(?.*)\""\ -`comment("Extract the name of the search from the search string")`\ -| table savedsearch_name count(search) usage user | join savedsearch_name max=0 type=left [search sourcetype="manifests" | spath searches{} | mvexpand searches{} | spath input=searches{} | table category search_name | rename search_name as savedsearch_name | dedup savedsearch_name] | search category=* - -[escu-metrics-search] -action.email.useNSSubject = 1 -alert.suppress = 0 -alert.track = 0 -auto_summarize.dispatch.earliest_time = -1d@h -enableSched = 1 -cron_schedule = 0 0 * * * -dispatch.earliest_time = -4h@h -dispatch.latest_time = -1h@h -search = index=_audit action=search | transaction search_id maxspan=3m | search ESCU | stats sum(total_run_time) avg(total_run_time) max(total_run_time) sum(result_count) - -[escu-metrics-search-events] -action.email.useNSSubject = 1 -alert.digest_mode = True -alert.suppress = 0 -alert.track = 0 -auto_summarize.dispatch.earliest_time = -1d@h -cron_schedule = 0 0 * * * -enableSched = 1 -dispatch.earliest_time = -4h@h -dispatch.latest_time = -1h@h -search = [search index=_audit sourcetype="audittrail" \"ESCU NOT "index=_audit" | where search !="" | dedup search_id | rex field=search "\"(?.*)\"" | rex field=_raw "user=(?[a-zA-Z0-9_\-]+)" | eval usage=if(savedsearch_name!="", "scheduled", "adhoc") | eval savedsearch_name=if(savedsearch_name != "", savedsearch_name, search_name) | table savedsearch_name search_id user _time usage | outputlookup escu_search_id.csv | table search_id] index=_audit total_run_time event_count result_count NOT "index=_audit" | lookup escu_search_id.csv search_id | stats count(savedsearch_name) AS search_count avg(total_run_time) AS search_avg_run_time sum(total_run_time) AS search_total_run_time sum(result_count) AS search_total_results earliest(_time) AS firsts latest(_time) AS lasts by savedsearch_name user usage| eval first_run=strftime(firsts, "%B %d %Y") | eval last_run=strftime(lasts, "%B %d %Y") - -[escu-metrics-search-longest-runtime] -action.email.useNSSubject = 1 -alert.digest_mode = True -alert.suppress = 0 -alert.track = 0 -auto_summarize.dispatch.earliest_time = -1d@h -enableSched = 1 -cron_schedule = 0 0 * * * -disabled = 1 -dispatch.earliest_time = -4h@h -dispatch.latest_time = -1h@h -search = index=_* ESCU [search index=_* action=search latest=-2h earliest=-1d| transaction search_id maxspan=3m | search ESCU | stats values(total_run_time) AS run by search_id | sort -run | head 1| table search_id] | table search search_id - -[escu-metrics-usage-search] -action.email.useNSSubject = 1 -alert.digest_mode = True -alert.suppress = 0 -alert.track = 0 -auto_summarize.dispatch.earliest_time = -1d@h -cron_schedule = 0 0 * * * -dispatch.earliest_time = -4h@h -dispatch.latest_time = -1h@h -enableSched = 1 -dispatchAs = user -search = index=_audit sourcetype="audittrail" \ -"ESCU - "\ -`comment("Find all the search names in the audittrail. Ignore the last few minutes so we can exclude this search's text from the result.")`\ -| stats count(search) by search savedsearch_name user\ -| eval usage=(if(savedsearch_name=="","Adhoc","Scheduled")) \ -`comment("If the savedsearch_name field in the audittrail is empty, the search was run adhoc. Otherwise it was run as a scheduled search")`\ -| rex field=search "\"(?.*)\""\ -`comment("Extract the name of the search from the search string")`\ -| table savedsearch_name count(search) usage user | join savedsearch_name max=0 type=left [search sourcetype="manifests" | spath searches{} | mvexpand searches{} | spath input=searches{} | table category search_name | rename search_name as savedsearch_name | dedup savedsearch_name] | search category=* diff --git a/dist/saaws/default/use_case_library.conf b/dist/saaws/default/use_case_library.conf index 5ccf913ebb..f003970623 100644 --- a/dist/saaws/default/use_case_library.conf +++ b/dist/saaws/default/use_case_library.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security_content -# On Date: 2021-03-30T19:36:01 UTC +# On Date: 2021-04-12T22:03:03 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -14,7 +14,7 @@ version = 1 references = ["https://rhinosecuritylabs.com/aws/aws-privilege-escalation-methods-mitigation/", "https://www.cyberark.com/resources/threat-research-blog/the-cloud-shadow-admin-threat-10-permissions-to-protect", "https://labs.bishopfox.com/tech-blog/privilege-escalation-in-aws"] maintainers = [{"company": "Splunk", "email": "-", "name": "Bhavin Patel"}] spec_version = 3 -searches = ["ESCU - AWS CreateLoginProfile - Rule", "ESCU - AWS UpdateLoginProfile - Rule", "ESCU - AWS CreateAccessKey - Rule", "ESCU - AWS Create Policy Version to allow all resources - Rule", "ESCU - AWS SetDefaultPolicyVersion - Rule"] +searches = ["ESCU - AWS Create Policy Version to allow all resources - Rule", "ESCU - AWS UpdateLoginProfile - Rule", "ESCU - AWS SetDefaultPolicyVersion - Rule", "ESCU - AWS CreateAccessKey - Rule", "ESCU - AWS CreateLoginProfile - Rule"] description = This analytic story contains detections that query your AWS Cloudtrail for activities related to privilege escalation. narrative = Amazon Web Services provides a neat feature called Identity and Access Management (IAM) that enables organizations to manage various AWS services and resources in a secure way. All IAM users have roles, groups and policies associated with them which governs and sets permissions to allow a user to access specific restrictions.\ However, if these IAM policies are misconfigured and have specific combinations of weak permissions; it can allow attackers to escalate their privileges and further compromise the organization. Rhino Security Labs have published comprehensive blogs detailing various AWS Escalation methods. By using this as an inspiration, Splunk’s research team wants to highlight how these attack vectors look in AWS Cloudtrail logs and provide you with detection queries to uncover these potentially malicious events via this Analytic Story. \ @@ -26,7 +26,7 @@ version = 2 references = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] maintainers = [{"company": "Splunk", "email": "-", "name": "Bhavin Patel"}] spec_version = 3 -searches = ["ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Get Process Info - Response Task", "ESCU - Get Notable History - Response Task", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Get DNS traffic ratio - Response Task", "ESCU - Get DNS Server History for a host - Response Task", "ESCU - AWS Network ACL Details from ID - Response Task", "ESCU - Get Process Responsible For The DNS Traffic - Response Task", "ESCU - Get All AWS Activity From IP Address - Response Task", "ESCU - AWS Network Interface details via resourceId - Response Task", "ESCU - Get Process Information For Port Activity - Response Task"] +searches = ["ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - AWS Network Interface details via resourceId - Response Task", "ESCU - Get All AWS Activity From IP Address - Response Task", "ESCU - AWS Network ACL Details from ID - Response Task"] description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and operational/risk auditing of your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Management Console, AWS Command Line Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable to attacks. This analytic story contains detection searches that leverage CloudTrail logs from AWS to check for bad configurations and malicious activity in your AWS network access controls. @@ -37,7 +37,7 @@ version = 1 references = ["https://aws.amazon.com/security-hub/features/"] maintainers = [{"company": "Splunk", "email": "-", "name": "Bhavin Patel"}] spec_version = 3 -searches = ["ESCU - Detect Spike in AWS Security Hub Alerts for EC2 Instance - Rule", "ESCU - Get EC2 Instance Details by instanceId - Response Task", "ESCU - Get EC2 Launch Details - Response Task", "ESCU - AWS Investigate User Activities By ARN - Response Task"] +searches = ["ESCU - Detect Spike in AWS Security Hub Alerts for EC2 Instance - Rule", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Get EC2 Instance Details by instanceId - Response Task", "ESCU - Get EC2 Launch Details - Response Task"] description = This story is focused around detecting Security Hub alerts generated from AWS narrative = AWS Security Hub collects and consolidates findings from AWS security services enabled in your environment, such as intrusion detection findings from Amazon GuardDuty, vulnerability scans from Amazon Inspector, S3 bucket policy findings from Amazon Macie, publicly accessible and cross-account resources from IAM Access Analyzer, and resources lacking WAF coverage from AWS Firewall Manager. @@ -48,7 +48,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = [{"company": "Splunk", "email": "-", "name": "David Dorsey"}] spec_version = 3 -searches = ["ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Abnormally High Number Of Cloud Instances Launched - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created In Previously Unused Region - Rule", "ESCU - Investigate AWS activities via region name - Response Task", "ESCU - Get EC2 Launch Details - Response Task", "ESCU - Get EC2 Instance Details by instanceId - Response Task", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - AWS Investigate Security Hub alerts by dest - Response Task", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created In Previously Unused Region - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Abnormally High Number Of Cloud Instances Launched - Rule", "ESCU - Get EC2 Instance Details by instanceId - Response Task", "ESCU - Get EC2 Launch Details - Response Task", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - AWS Investigate Security Hub alerts by dest - Response Task", "ESCU - Investigate AWS activities via region name - Response Task"] description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Azure. It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -62,7 +62,7 @@ version = 1 references = ["https://www.cyberark.com/resources/threat-research-blog/golden-saml-newly-discovered-attack-technique-forges-authentication-to-cloud-apps", "https://www.fireeye.com/content/dam/fireeye-www/blog/pdfs/wp-m-unc2452-2021-000343-01.pdf", "https://us-cert.cisa.gov/ncas/alerts/aa21-008a"] maintainers = [{"company": "Splunk", "email": "-", "name": "Rod Soto"}] spec_version = 3 -searches = ["ESCU - O365 Added Service Principal - Rule", "ESCU - O365 Excessive SSO logon errors - Rule", "ESCU - O365 New Federated Domain Added - Rule", "ESCU - AWS SAML Update identity provider - Rule", "ESCU - AWS SAML Access by Provider User and Principal - Rule", "ESCU - O365 Add App Role Assignment Grant User - Rule"] +searches = ["ESCU - O365 Excessive SSO logon errors - Rule", "ESCU - AWS SAML Update identity provider - Rule", "ESCU - O365 New Federated Domain Added - Rule", "ESCU - O365 Add App Role Assignment Grant User - Rule", "ESCU - O365 Added Service Principal - Rule", "ESCU - AWS SAML Access by Provider User and Principal - Rule"] description = This analytical story addresses events that indicate abuse of cloud federated credentials. These credentials are usually extracted from endpoint desktop or servers specially those servers that provide federation services such as Windows Active Directory Federation Services. Identity Federation relies on objects such as Oauth2 tokens, cookies or SAML assertions in order to provide seamless access between cloud and perimeter environments. If these objects are either hijacked or forged then attackers will be able to pivot into victim's cloud environements. narrative = This story is composed of detection searches based on endpoint that addresses the use of Mimikatz, Escalation of Privileges and Abnormal processes that may indicate the extraction of Federated directory objects such as passwords, Oauth2 tokens, certificates and keys. Cloud environment (AWS, Azure) related events are also addressed in specific cloud environment detection searches. @@ -73,7 +73,7 @@ version = 1 references = ["https://i.blackhat.com/USA-20/Thursday/us-20-Bienstock-My-Cloud-Is-APTs-Cloud-Investigating-And-Defending-Office-365.pdf"] maintainers = [{"company": "Splunk", "email": "-", "name": "Patrick Bareiss"}] spec_version = 3 -searches = ["ESCU - O365 Added Service Principal - Rule", "ESCU - O365 Disable MFA - Rule", "ESCU - O365 Excessive SSO logon errors - Rule", "ESCU - O365 New Federated Domain Added - Rule", "ESCU - O365 Suspicious Admin Email Forwarding - Rule", "ESCU - O365 PST export alert - Rule", "ESCU - O365 Suspicious Rights Delegation - Rule", "ESCU - O365 Add App Role Assignment Grant User - Rule", "ESCU - O365 Suspicious User Email Forwarding - Rule", "ESCU - O365 Excessive Authentication Failures Alert - Rule", "ESCU - O365 Bypass MFA via Trusted IP - Rule"] +searches = ["ESCU - O365 Disable MFA - Rule", "ESCU - O365 Excessive SSO logon errors - Rule", "ESCU - O365 Excessive Authentication Failures Alert - Rule", "ESCU - O365 Suspicious Admin Email Forwarding - Rule", "ESCU - O365 Bypass MFA via Trusted IP - Rule", "ESCU - O365 PST export alert - Rule", "ESCU - O365 Suspicious Rights Delegation - Rule", "ESCU - O365 New Federated Domain Added - Rule", "ESCU - O365 Add App Role Assignment Grant User - Rule", "ESCU - O365 Suspicious User Email Forwarding - Rule", "ESCU - O365 Added Service Principal - Rule"] description = This story is focused around detecting Office 365 Attacks. narrative = More and more companies are using Microsofts Office 365 cloud offering. Therefore, we see more and more attacks against Office 365. This story provides various detections for Office 365 attacks. @@ -84,7 +84,7 @@ version = 1 references = ["https://rhinosecuritylabs.com/aws/s3-ransomware-part-1-attack-vector/", "https://github.com/d1vious/git-wild-hunt", "https://www.youtube.com/watch?v=PgzNib37g0M"] maintainers = [{"company": "David Dorsey, Splunk", "email": "-", "name": "Rod Soto"}] spec_version = 3 -searches = ["ESCU - AWS Detect Users creating keys with encrypt policy without MFA - Rule", "ESCU - AWS Detect Users with KMS keys performing encryption S3 - Rule", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - AWS Detect Users creating keys with encrypt policy without MFA - Rule", "ESCU - AWS Detect Users with KMS keys performing encryption S3 - Rule"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware. These searches include cloud related objects that may be targeted by malicious actors via cloud providers own encryption features. narrative = Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise.Cloud ransomware can be deployed by obtaining high privilege credentials from targeted users or resources. @@ -95,7 +95,7 @@ version = 1 references = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] maintainers = [{"company": "Splunk", "email": "-", "name": "Bhavin Patel"}] spec_version = 3 -searches = ["ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - AWS Investigate User Activities By ARN - Response Task"] +searches = ["ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - AWS Investigate User Activities By ARN - Response Task"] description = Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. narrative = It is important to monitor and control who has access to your AWS infrastructure. Detecting suspicious logins to your AWS infrastructure will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any EC2 instances created by the attacker. @@ -106,7 +106,7 @@ version = 2 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] maintainers = [{"company": "Splunk", "email": "-", "name": "Bhavin Patel"}] spec_version = 3 -searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect New Open S3 Buckets over AWS CLI - Rule", "ESCU - Investigate AWS activities via region name - Response Task", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - AWS S3 Bucket details via bucketName - Response Task", "ESCU - Get All AWS Activity From IP Address - Response Task", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect New Open S3 Buckets over AWS CLI - Rule", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - AWS S3 Bucket details via bucketName - Response Task", "ESCU - Get All AWS Activity From IP Address - Response Task", "ESCU - Investigate AWS activities via region name - Response Task"] description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. narrative = As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\ Amazon's "shared responsibility" model dictates that the company has responsibility for the environment outside of the VM and the customer is responsible for the security inside of the S3 container. As such, it's important to stay vigilant for activities that may belie suspicious behavior inside of your environment.\ @@ -119,7 +119,7 @@ version = 1 references = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/", "https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] maintainers = [{"company": "Splunk", "email": "-", "name": "Rico Valdez"}] spec_version = 3 -searches = ["ESCU - Detect AWS Console Login by New User - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - Investigate AWS User Activities by user field - Response Task", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - Detect AWS Console Login by New User - Rule", "ESCU - Investigate AWS User Activities by user field - Response Task"] description = Monitor your cloud authentication events. Searches within this Analytic Story leverage the recent cloud updates to the Authentication data model to help you stay aware of and investigate suspicious login activity. narrative = It is important to monitor and control who has access to your cloud infrastructure. Detecting suspicious logins will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any compute activity whether legitimate or otherwise.\ This Analytic Story has data model versions of cloud searches leveraging Authentication data, including those looking for suspicious login activity, and cross-account activity for AWS. @@ -131,7 +131,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = [{"company": "Splunk", "email": "-", "name": "David Dorsey"}] spec_version = 3 -searches = ["ESCU - Abnormally High Number Of Cloud Instances Launched - Rule", "ESCU - Cloud Instance Modified By Previously Unseen User - Rule", "ESCU - Abnormally High Number Of Cloud Instances Destroyed - Rule", "ESCU - Get All AWS Activity From IP Address - Response Task", "ESCU - AWS Investigate User Activities By ARN - Response Task"] +searches = ["ESCU - Abnormally High Number Of Cloud Instances Launched - Rule", "ESCU - Cloud Instance Modified By Previously Unseen User - Rule", "ESCU - Abnormally High Number Of Cloud Instances Destroyed - Rule", "ESCU - AWS Investigate User Activities By ARN - Response Task", "ESCU - Get All AWS Activity From IP Address - Response Task"] description = Monitor your cloud infrastructure provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your cloud environment. narrative = Monitoring your cloud infrastructure logs allows you enable governance, compliance, and risk auditing. It is crucial for a company to monitor events and actions taken in the their cloud environments to ensure that your instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your cloud compute instances and helps you respond and investigate those activities. @@ -142,7 +142,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = [{"company": "Splunk", "email": "-", "name": "David Dorsey"}] spec_version = 3 -searches = ["ESCU - Cloud Provisioning Activity From Previously Unseen Region - Rule", "ESCU - Cloud Provisioning Activity From Previously Unseen Country - Rule", "ESCU - Cloud Provisioning Activity From Previously Unseen IP Address - Rule", "ESCU - Cloud Provisioning Activity From Previously Unseen City - Rule", "ESCU - Get Notable History - Response Task"] +searches = ["ESCU - Cloud Provisioning Activity From Previously Unseen Region - Rule", "ESCU - Cloud Provisioning Activity From Previously Unseen IP Address - Rule", "ESCU - Cloud Provisioning Activity From Previously Unseen Country - Rule", "ESCU - Cloud Provisioning Activity From Previously Unseen City - Rule"] description = Monitor your cloud infrastructure provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your cloud environment. narrative = Because most enterprise cloud infrastructure activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where it is impossible to add specific IPs to an allow list because they vary.\ This Analytic Story was designed to provide you with flexibility in the precision you employ in specifying legitimate geographic regions. It can be as specific as an IP address or a city, or as broad as a region (think state) or an entire country. By determining how precise you want your geographical locations to be and monitoring for new locations that haven't previously accessed your environment, you can detect adversaries as they begin to probe your environment. Since there are legitimate reasons for activities from unfamiliar locations, this is not a standalone indicator. Nevertheless, location can be a relevant piece of information that you may wish to investigate further. @@ -154,7 +154,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] maintainers = [{"company": "Splunk", "email": "-", "name": "David Dorsey"}] spec_version = 3 -searches = ["ESCU - Abnormally High Number Of Cloud Security Group API Calls - Rule", "ESCU - Cloud API Calls From Previously Unseen User Roles - Rule", "ESCU - Abnormally High Number Of Cloud Infrastructure API Calls - Rule", "ESCU - AWS Investigate User Activities By ARN - Response Task"] +searches = ["ESCU - Abnormally High Number Of Cloud Infrastructure API Calls - Rule", "ESCU - Cloud API Calls From Previously Unseen User Roles - Rule", "ESCU - Abnormally High Number Of Cloud Security Group API Calls - Rule", "ESCU - AWS Investigate User Activities By ARN - Response Task"] description = Detect and investigate suspicious activities by users and roles in your cloud environments. narrative = It seems obvious that it is critical to monitor and control the users who have access to your cloud infrastructure. Nevertheless, it's all too common for enterprises to lose track of ad-hoc accounts, leaving their servers vulnerable to attack. In fact, this was the very oversight that led to Tesla's cryptojacking attack in February, 2018.\ In addition to compromising the security of your data, when bad actors leverage your compute resources, it can incur monumental costs, since you will be billed for any new instances and increased bandwidth usage. @@ -659,14 +659,6 @@ known_false_positives = not defined earliest_time_offset = 14400 latest_time_offset = 0 -[savedsearch://ESCU - All backup logs for host - Response Task] -type = investigation -explanation = none -how_to_implement = The successfully implement this search you must first send your backup logs to Splunk. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - [savedsearch://ESCU - Amazon EKS Kubernetes activity by src ip - Response Task] type = investigation explanation = none @@ -675,40 +667,6 @@ known_false_positives = not defined earliest_time_offset = 14400 latest_time_offset = 0 -[savedsearch://ESCU - DNS Hijack Enrichment - Response Task] -type = investigation -explanation = none -how_to_implement = If Splunk>Phantom is also configured in your environment, a Playbook called "DNS Hijack Enrichment" can be configured to run when any results are found by this detection search. The playbook takes in the DNS record changed and uses Geoip, whois, Censys and PassiveTotal to detect if DNS issuers changed. To use this integration, install the Phantom App for Splunk `https://splunkbase.splunk.com/app/3411/`, add the correct hostname to the "Phantom Instance" field in the Adaptive Response Actions when configuring this detection search, and set the corresponding Playbook to active. \ -(Playbook Link:`https://my.phantom.us/4.2/playbook/dns-hijack-enrichment/`).\ - -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Domain Certificate Investigation - Response Task] -type = investigation -explanation = none -how_to_implement = To successfully implement this phantom playbook, you must integrate Enterprise Security with Phantom. Configure this playbook in the correlation search `Detect DNS requests to Phishing Sites leveraging EvilGinx2` ,as an adaptive response action. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Excessive Account Lockouts Enrichment And Response - Response Task] -type = investigation -explanation = none -how_to_implement = Import playbook into phantom -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - GCP Kubernetes activity by src ip - Response Task] -type = investigation -explanation = none -how_to_implement = You must install the GCP App for Splunk (version 2.0.0 or later), then configure stackdriver and set a Pub/Sub subscription to be imported to Splunk. You must also install Cloud Infrastructure data model.Customize the macro kubernetes_gcp_scan_fingerprint_attack_detection to filter out FPs. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - [savedsearch://ESCU - Get All AWS Activity From City - Response Task] type = investigation explanation = none @@ -741,38 +699,6 @@ known_false_positives = not defined earliest_time_offset = 14400 latest_time_offset = 0 -[savedsearch://ESCU - Get Backup Logs For Endpoint - Response Task] -type = investigation -explanation = none -how_to_implement = You must be ingesting your backup logs. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Get Certificate logs for a domain - Response Task] -type = investigation -explanation = none -how_to_implement = You must be ingesting your certificates or SSL logs from your network traffic into your Certificates datamodel. Please note the wildcard(*) before domain in the search syntax, we use to match for all domain and subdomain combinations -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Get DNS Server History for a host - Response Task] -type = investigation -explanation = none -how_to_implement = To successfully implement this search, you must be ingesting your DNS traffic -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Get DNS traffic ratio - Response Task] -type = investigation -explanation = none -how_to_implement = You must be ingesting your network traffic -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - [savedsearch://ESCU - Get EC2 Instance Details by instanceId - Response Task] type = investigation explanation = none @@ -789,126 +715,6 @@ known_false_positives = not defined earliest_time_offset = 14400 latest_time_offset = 0 -[savedsearch://ESCU - Get Email Info - Response Task] -type = investigation -explanation = none -how_to_implement = To successfully implement this search you must be ingesting your email logs or capturing unencrypted network traffic which contains email communications. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Get Emails From Specific Sender - Response Task] -type = investigation -explanation = none -how_to_implement = To successfully implement this search you must ingest your email logs or capture unencrypted email communications within network traffic, and populate the Email data model. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Get First Occurrence and Last Occurrence of a MAC Address - Response Task] -type = investigation -explanation = none -how_to_implement = To successfully implement this search, you must be ingesting the logs from your DHCP server. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Get History Of Email Sources - Response Task] -type = investigation -explanation = none -how_to_implement = To successfully implement this search you must ingest your email logs or capture unencrypted email communications within network traffic, and populate the Email data model. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Get Logon Rights Modifications For Endpoint - Response Task] -type = investigation -explanation = none -how_to_implement = To successfully implement this search you must be ingesting your Windows event logs -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Get Logon Rights Modifications For User - Response Task] -type = investigation -explanation = none -how_to_implement = To successfully implement this search you must be ingesting your Windows event logs -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Get Notable History - Response Task] -type = investigation -explanation = none -how_to_implement = If you are using Enterprise Security you are likely already creating notable events with your correlation rules. No additional configuration is necessary. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Get Outbound Emails to Hidden Cobra Threat Actors - Response Task] -type = investigation -explanation = none -how_to_implement = To successfully implement this search you must ingest your email logs or capture unencrypted email communications within network traffic, and populate the Email data model. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Get Parent Process Info - Response Task] -type = investigation -explanation = none -how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Get Process File Activity - Response Task] -type = investigation -explanation = none -how_to_implement = To successfully implement this search you must be ingesting endpoint data and populating the Endpoint data model. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Get Process Info - Response Task] -type = investigation -explanation = none -how_to_implement = To successfully implement this search you must be ingesting endpoint data and populating the Endpoint data model. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Get Process Information For Port Activity - Response Task] -type = investigation -explanation = none -how_to_implement = To successfully implement this search you must be ingesting endpoint data that associates processes with network events and populate the Endpoint Datamodel -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Get Process Responsible For The DNS Traffic - Response Task] -type = investigation -explanation = none -how_to_implement = You must be ingesting endpoint data that associates processes with network events into the Endpoint datamodel. This can come from endpoint protection products such as carbon black, or endpoint data sources such as Sysmon. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Get Sysmon WMI Activity for Host - Response Task] -type = investigation -explanation = none -how_to_implement = To successfully implement this search, you must be collecting Sysmon data using Sysmon version 6.1 or greater and have Sysmon configured to generate events for WMI activity. In addition, you must have at least version 6.0.4 of the Sysmon TA installed to properly parse the fields. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Get Web Session Information via session id - Response Task] -type = investigation -explanation = none -how_to_implement = This search leverages data extracted from Stream:HTTP. You must configure the HTTP stream using the Splunk Stream App on your Splunk Stream deployment server. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - [savedsearch://ESCU - Investigate AWS User Activities by user field - Response Task] type = investigation explanation = none @@ -925,94 +731,6 @@ known_false_positives = not defined earliest_time_offset = 14400 latest_time_offset = 0 -[savedsearch://ESCU - Investigate Failed Logins for Multiple Destinations - Response Task] -type = investigation -explanation = none -how_to_implement = To successfully implement this search you need to be ingesting authentication logs from your various systems and populating the Authentication data model. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Investigate Network Traffic From src ip - Response Task] -type = investigation -explanation = none -how_to_implement = To successfully implement this search, you must be ingesting your web-traffic logs and populating the web data model. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Investigate Okta Activity by IP Address - Response Task] -type = investigation -explanation = none -how_to_implement = You must be ingesting Okta logs -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Investigate Okta Activity by app - Response Task] -type = investigation -explanation = none -how_to_implement = You must be ingesting Okta logs -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Investigate Pass the Hash Attempts - Response Task] -type = investigation -explanation = none -how_to_implement = To successfully implement this search you need be ingesting windows security logs. This search uses an input macro named `wineventlog_security`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Security logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Investigate Pass the Ticket Attempts - Response Task] -type = investigation -explanation = none -how_to_implement = To successfully implement this search you need to be ingesting windows security logs. This search uses an input macro named `wineventlog_security`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Security logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Investigate Previous Unseen User - Response Task] -type = investigation -explanation = none -how_to_implement = To successfully implement this search you need to be ingesting authentication logs from your various systems and populating the Authentication data model. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Investigate Successful Remote Desktop Authentications - Response Task] -type = investigation -explanation = none -how_to_implement = You must be populating the Authentication data model with security events from your Windows event logs. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Investigate Suspicious Strings in HTTP Header - Response Task] -type = investigation -explanation = none -how_to_implement = This particular search leverages data extracted from Stream:HTTP. You must configure the http stream using the Splunk Stream App on your Splunk Stream deployment server to extract the cs_content_type field. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Investigate User Activities In Okta - Response Task] -type = investigation -explanation = none -how_to_implement = You must be ingesting Okta logs -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Investigate Web POSTs From src - Response Task] -type = investigation -explanation = none -how_to_implement = To successfully implement this search, you must be ingesting your web-traffic logs and populating the web data model. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - ### END RESPONSE TASKS ### ### BASELINES ### @@ -1046,157 +764,6 @@ how_to_implement = You must have Enterprise Security 6.0 or later, if not you wi known_false_positives = not defined providing_technologies = none -[savedsearch://ESCU - Baseline of API Calls per User ARN] -type = support -explanation = This search establishes, on a per-hour basis, the average and the standard deviation of the number of API calls made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. -how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Baseline of Command Line Length - MLTK] -type = support -explanation = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the length of the command lines observed for each user in the environment. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies outliers in the length of the command line. -how_to_implement = You must be ingesting endpoint data and populating the Endpoint data model. In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. Depending on the number of users in your environment, you may also need to adjust the value for max_inputs in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data. More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Baseline of DNS Query Length - MLTK] -type = support -explanation = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the length of the DNS queries for each DNS record type observed in the environment. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search, which uses it to identify outliers in the length of the DNS query. -how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data. More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK] -type = support -explanation = This search is used to build a Machine Learning Toolkit (MLTK) model for how many RunInstances users do in the environment. By default, the search uses the last 90 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies subsequent outliers in the number of RunInstances performed by a user in a small time window. -how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.\ -In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. Depending on the number of users in your environment, you may also need to adjust the value for max_inputs in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data.\ -More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Baseline of Excessive AWS Instances Terminated by User - MLTK] -type = support -explanation = This search is used to build a Machine Learning Toolkit (MLTK) model for how many TerminateInstances users do in the environment. By default, the search uses the last 90 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies subsequent outliers in the number of TerminateInstances performed by a user in a small time window. -how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.\ -In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. Depending on the number of users in your environment, you may also need to adjust the value for max_inputs in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data.\ -More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Baseline of Network ACL Activity by ARN] -type = support -explanation = This search establishes, on a per-hour basis, the average and the standard deviation of the number of API calls that were related to network ACLs made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. -how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. To add or remove API event names for network ACLs, edit the macro `network_acl_events`. -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Baseline of S3 Bucket deletion activity by ARN] -type = support -explanation = This search establishes, on a per-hour basis, the average and standard deviation for the number of API calls related to deleting an S3 bucket by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. -how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Baseline of SMB Traffic - MLTK] -type = support -explanation = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the number of SMB connections observed each hour for every day of week. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search to identify outliers in the number of SMB connections for that hour and day of the week. -how_to_implement = You must be ingesting network traffic and populating the Network_Traffic data model. In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. To improve your results, you may consider adding "src" to the by clause, which will build the model for each unique source in your enviornment. However, if you have a large number of hosts in your environment, this search may be very resource intensive. In this case, you may need to raise the value of max_inputs and/or max_groups in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data. More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Baseline of Security Group Activity by ARN] -type = support -explanation = This search establishes, on a per-hour basis, the average and the standard deviation for the number of API calls related to security groups made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. -how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. To add or remove API event names for security groups, edit the macro `security_group_api_calls`. -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Baseline of blocked outbound traffic from AWS] -type = support -explanation = This search establishes, on a per-hour basis, the average and the standard deviation of the number of outbound connections blocked in your VPC flow logs by each source IP address (IP address of your EC2 instances). Also recorded is the number of data points for each source IP. This table outputs to a lookup file to allow the detection search to operate quickly. -how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your `VPC flow logs.`. -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Count of Unique IPs Connecting to Ports] -type = support -explanation = The search counts the number of times a connection was observed to each destination port, and the number of unique source IPs connecting to them. -how_to_implement = To successfully implement this search, you must be ingesting network traffic, and populating the Network_Traffic data model. -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Count of assets by category] -type = support -explanation = This search shows you every asset category you have and the assets that belong to those categories. -how_to_implement = To successfully implement this search you must first leverage the Assets and Identity framework in Enterprise Security to populate your assets_by_str.csv file which should then be mapped to the Identity_Management data model. The Identity_Management data model will contain a list of known authorized company assets. Ensure that all inventoried systems are constantly vetted and updated. -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Create a list of approved AWS service accounts] -type = support -explanation = This search looks for successful API activity in CloudTrail within the last 30 days, filters out known users from the identity table, and outputs values of users into `aws_service_accounts.csv` lookup file. -how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the service account entires in `aws_service_accounts.csv`, which is a lookup file created as a result of running this support search. Please remove the entries of service accounts that are not legitimate. -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - DNSTwist Domain Names] -type = support -explanation = This search creates permutations of your existing domains, removes the valid domain names and stores them in a specified lookup file so they can be checked for in the associated detection searches. -how_to_implement = To successfully implement this search you need to update the file called domains.csv in the DA-ESS-SOC/lookup directory. Or `cim_corporate_email_domains.csv` and `cim_corporate_web_domains.csv` from **Splunk\_SA\_CIM**. -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Discover DNS records] -type = support -explanation = The search takes corporate and common cloud provider domains configured under `cim_corporate_email_domains.csv`, `cim_corporate_web_domains.csv`, and `cloud_domains.csv` finds their responses across the last 30 days from data in the `Network_Resolution ` datamodel, then stores the output under the `discovered_dns_records.csv` lookup -how_to_implement = To successfully implement this search, you must be ingesting DNS logs, and populating the Network_Resolution data model. Also make sure that the cim_corporate_web_domains and cim_corporate_email_domains lookups are populated with the domains owned by your corporation -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Identify Systems Creating Remote Desktop Traffic] -type = support -explanation = This search counts the numbers of times the system has generated remote desktop traffic. -how_to_implement = To successfully implement this search, you must ingest network traffic and populate the Network_Traffic data model. -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Identify Systems Receiving Remote Desktop Traffic] -type = support -explanation = This search counts the numbers of times the system has created remote desktop traffic -how_to_implement = To successfully implement this search you must ingest network traffic and populate the Network_Traffic data model. If a system receives a lot of remote desktop traffic, you can apply the category common_rdp_destination to it. -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Identify Systems Using Remote Desktop] -type = support -explanation = This search counts the numbers of times the remote desktop process, mstsc.exe, has run on each system. -how_to_implement = To successfully implement this search you must be ingesting endpoint data that records process activity. -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Monitor Successful Backups] -type = support -explanation = This search is intended to give you a feel for how often successful backups are conducted in your environment. Fluctuations in these numbers will allow you to determine when you should investigate. -how_to_implement = To successfully implement this search you must be ingesting your backup logs. -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Monitor Unsuccessful Backups] -type = support -explanation = This search is intended to give you a feel for how often backup failures happen in your environments. Fluctuations in these numbers will allow you to determine when you should investigate. -how_to_implement = To successfully implement this search you must be ingesting your backup logs. -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Previously Seen AWS Cross Account Activity] -type = support -explanation = This search looks for **AssumeRole** events where the requesting account differs from the requested account, then writes these relationships to a lookup file. -how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Validate the user name entries in `previously_seen_aws_cross_account_activity.csv`, a lookup file created by this support search. -known_false_positives = not defined -providing_technologies = none - [savedsearch://ESCU - Previously Seen AWS Cross Account Activity - Initial] type = support explanation = This search looks for **AssumeRole** events where the requesting account differs from the requested account, then writes these relationships to a lookup file. @@ -1211,20 +778,6 @@ how_to_implement = You must install and configure the Splunk Add-on for AWS (ver known_false_positives = not defined providing_technologies = none -[savedsearch://ESCU - Previously Seen AWS Provisioning Activity Sources] -type = support -explanation = This search builds a table of the first and last times seen for every IP address (along with its physical location) previously associated with cloud-provisioning activity. This is broadly defined as any event that runs or creates something. -how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Previously Seen AWS Regions] -type = support -explanation = This search looks for CloudTrail events where an AWS instance is started and creates a baseline of most recent time (latest) and the first time (earliest) we've seen this region in our dataset grouped by the value awsRegion for the last 30 days -how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. -known_false_positives = not defined -providing_technologies = none - [savedsearch://ESCU - Previously Seen Cloud API Calls Per User Role - Initial] type = support explanation = This search builds a table of the first and last times seen for every user role and command combination. This is broadly defined as any event that runs or creates something. This table is then cached. @@ -1323,48 +876,6 @@ how_to_implement = You must be ingesting the approrpiate cloud infrastructure lo known_false_positives = not defined providing_technologies = none -[savedsearch://ESCU - Previously Seen EC2 AMIs] -type = support -explanation = This search builds a table of previously seen AMIs used to launch EC2 instances -how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Previously Seen EC2 Instance Types] -type = support -explanation = This search builds a table of previously seen EC2 instance types -how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Previously Seen EC2 Launches By User] -type = support -explanation = This search builds a table of previously seen ARNs that have launched a EC2 instance. -how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Previously Seen EC2 Modifications By User] -type = support -explanation = This search builds a table of previously seen ARNs that have launched a EC2 instance. -how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. To add or remove APIs that modify an EC2 instance, edit the macro `ec2_modification_api_calls`. -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Previously Seen Running Windows Services - Initial] -type = support -explanation = This collects the services that have been started across your entire enterprise. -how_to_implement = While this search does not require you to adhere to Splunk CIM, you must be ingesting your Windows security-event logs for it to execute successfully. Please ensure that the Splunk Add-on for Microsoft Windows is version 8.0.0 or above. -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Previously Seen Running Windows Services - Update] -type = support -explanation = This search returns the first and last time a Windows service was seen across your enterprise within the last hour. It then updates this information with historical data and filters out Windows services pairs that have not been seen within the specified time window. This updated table is then cached. -how_to_implement = While this search does not require you to adhere to Splunk CIM, you must be ingesting your Windows security-event logs for it to execute successfully. Please ensure that the Splunk Add-on for Microsoft Windows is version 8.0.0 or above. -known_false_positives = not defined -providing_technologies = none - [savedsearch://ESCU - Previously Seen Users In CloudTrail - Update] type = support explanation = This search looks for CloudTrail events where a user logs into the console, then updates the baseline of the latest and earliest times, City, Region, and Country we have encountered this user in our dataset, grouped by user, within the last hour. @@ -1379,74 +890,4 @@ how_to_implement = You must install and configure the Splunk Add-on for AWS (ver known_false_positives = not defined providing_technologies = none -[savedsearch://ESCU - Previously Seen Zoom Child Processes - Initial] -type = support -explanation = This search returns the first and last time a process was seen per endpoint with a parent process of zoom.exe (Windows) or zoom.us (macOS). This table is then cached. -how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints, to populate the Endpoint data model in the Processes node. -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Previously Seen Zoom Child Processes - Update] -type = support -explanation = This search returns the first and last time a process was seen per endpoint with a parent process of zoom.exe (Windows) or zoom.us (macOS) within the last hour. It then updates this information with historical data and filters out proces_name and endpoint pairs that have not been seen within the specified time window. This updated table is outputed to disk. -how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints, to populate the Endpoint data model in the Processes node. -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Previously seen API call per user roles in CloudTrail] -type = support -explanation = This search looks for successful API calls made by different user roles, then creates a baseline of the earliest and latest times we have encountered this user role. It also returns the name of the API call in our dataset--grouped by user role and name of the API call--that occurred within the last 30 days. In this support search, we are only looking for events where the user identity is Assumed Role. -how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the user role entries in `previously_seen_api_calls_from_user_roles.csv`, which is a lookup file created as a result of running this support search. -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Previously seen S3 bucket access by remote IP] -type = support -explanation = This search looks for successful access to S3 buckets from remote IP addresses, then creates a baseline of the earliest and latest times we have encountered this remote IP within the last 30 days. In this support search, we are only looking for S3 access events where the HTTP response code from AWS is "200" -how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your S3 access-logs inputs. You must validate the remote IP and bucket name entries in `previously_seen_S3_access_from_remote_ip.csv`, which is a lookup file created as a result of running this support search. -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Previously seen command line arguments] -type = support -explanation = This search looks for command-line arguments where `cmd.exe /c` is used to execute a program, then creates a baseline of the earliest and latest times we have encountered this command-line argument in our dataset within the last 30 days. -how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must be ingesting logs with both the process name and command line from your endpoints. The complete process name with command-line arguments are mapped to the "process" field in the Endpoint data model. -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Previously seen users in CloudTrail] -type = support -explanation = This search looks for CloudTrail events where a user logs into the console, then creates a baseline of the latest and earliest times, City, Region, and Country we have encountered this user in our dataset, grouped by ARN, within the last 30 days. NOTE - This baseline search is deprecated and has been updated to use the Authentication Datamodel -how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the user name entries in `previously_seen_users_console_logins_cloudtrail`, which is a lookup file created as a result of running this support search. -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Systems Ready for Spectre-Meltdown Windows Patch] -type = support -explanation = Some AV applications can cause the Spectre/Meltdown patch for Windows not to install successfully. This registry key is supposed to be created by the AV engine when it has been patched to be able to handle the Windows patch. If this key has been written, the system can then be patched for Spectre and Meltdown. -how_to_implement = You need to be ingesting logs with both the process name and command-line from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Update previously seen users in CloudTrail] -type = support -explanation = This search looks for CloudTrail events where a user logs into the console, then updates the baseline of the latest and earliest times, City, Region, and Country we have encountered this user in our dataset, grouped by ARN, within the last hour. NOTE - This baseline search is deprecated and has been updated to use the Authentication Datamodel -how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the user name entries in `previously_seen_users_console_logins_cloudtrail`, which is a lookup file created as a result of running this support search. -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Windows Updates Install Failures] -type = support -explanation = This search is intended to give you a feel for how often Windows updates fail to install in your environment. Fluctuations in these numbers will allow you to determine when you should be concerned. -how_to_implement = You must be ingesting your Windows Update Logs -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Windows Updates Install Successes] -type = support -explanation = This search is intended to give you a feel for how often successful Windows updates are applied in your environments. Fluctuations in these numbers will allow you to determine when you should be concerned. -how_to_implement = You must be ingesting your Windows Update Logs -known_false_positives = not defined -providing_technologies = none - ### END ESCU BASELINES ### \ No newline at end of file diff --git a/tests/cloud/aws_excessive_security_scanning.test.yml b/tests/cloud/aws_excessive_security_scanning.test.yml new file mode 100644 index 0000000000..8a5cfe19e1 --- /dev/null +++ b/tests/cloud/aws_excessive_security_scanning.test.yml @@ -0,0 +1,13 @@ +name: AWS Excessive Security Scanning Unit Test +tests: +- name: AWS Excessive Security Scanning + file: cloud/aws_excessive_security_scanning.yml + pass_condition: '| stats count | where count > 0' + earliest_time: '-24h' + latest_time: 'now' + attack_data: + - file_name: aws_cloudtrail_events.json + data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1526/aws_security_scanner/aws_security_scanner.json + sourcetype: aws:cloudtrail + source: aws_cloudtrail + update_timestamp: True diff --git a/tests/endpoint/malicious_powershell_executed_as_a_service.test.yml b/tests/endpoint/malicious_powershell_executed_as_a_service.test.yml new file mode 100644 index 0000000000..b2d93a1a8f --- /dev/null +++ b/tests/endpoint/malicious_powershell_executed_as_a_service.test.yml @@ -0,0 +1,12 @@ +name: Malicious Powershell Executed As A Service Unit Test +tests: +- name: Malicious Powershell Executed As A Service + file: endpoint/malicious_powershell_executed_as_a_service.yml + pass_condition: '| stats count | where count > 0' + earliest_time: '-24h' + latest_time: 'now' + attack_data: + - file_name: windows-system.log + data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1569.002/atomic_red_team/windows-system.log + source: WinEventLog:System + sourcetype: WinEventLog