From 4ac5dc4dff1937106316168f9d73e4b5506b3ff5 Mon Sep 17 00:00:00 2001 From: Rod Soto Date: Tue, 19 May 2020 14:20:10 -0400 Subject: [PATCH 01/14] k8sScan --- .../kubernetes_azure_scan_fingerprint.yml | 18 +++++++++++++ ...zure_scan_fingerprint_detection_filter.yml | 3 +++ stories/kubernetes_scanning_activity.yml | 27 ++++++++----------- 3 files changed, 32 insertions(+), 16 deletions(-) create mode 100644 detections/kubernetes_azure_scan_fingerprint.yml create mode 100644 macros/kubernetes_azure_scan_fingerprint_detection_filter.yml diff --git a/detections/kubernetes_azure_scan_fingerprint.yml b/detections/kubernetes_azure_scan_fingerprint.yml new file mode 100644 index 0000000000..1dc3988edc --- /dev/null +++ b/detections/kubernetes_azure_scan_fingerprint.yml @@ -0,0 +1,18 @@ +author: "Rod Soto, Splunk" +date: "2020-05-19" +description: "This search provides information of unauthenticated requests via source IP user agent, request URI and response status data against Kubernetes cluster in Azure" +how_to_implement: "You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics" +id: c5e5bd5c-1013-4841-8b23-e7b3253c840a +known_false_positives: "Not all unauthenticated requests are malicious, but source IPs, userAgent, verb, request URI and response status will provide context." +name: "Azure AKS Kubernetes cluster scan detection" +references: [] +search: "sourcetype=mscs:storage:blob:json category=kube-audit | spath input=properties.log | search responseStatus.code=401 | table sourceIPs{} userAgent verb requestURI responseStatus.reason |`kubernetes_aws_scan_fingerprint_detection`" +tags: + analytics_story: + - "Kubernetes Scanning Activity" + asset_type: "Azure AKS Kubernetes cluster" + kill_chain_phases: + - Reconnaissance + security_domain: threat +type: ESCU +version: 1 diff --git a/macros/kubernetes_azure_scan_fingerprint_detection_filter.yml b/macros/kubernetes_azure_scan_fingerprint_detection_filter.yml new file mode 100644 index 0000000000..1c98d00ea1 --- /dev/null +++ b/macros/kubernetes_azure_scan_fingerprint_detection_filter.yml @@ -0,0 +1,3 @@ +definition: search * +description: Use this macro to add additional filters +name: kubernetes_azure_scan_fingerprint_detection diff --git a/stories/kubernetes_scanning_activity.yml b/stories/kubernetes_scanning_activity.yml index be38a9c8a1..4a9f4de4f7 100644 --- a/stories/kubernetes_scanning_activity.yml +++ b/stories/kubernetes_scanning_activity.yml @@ -1,20 +1,15 @@ -name: Kubernetes Scanning Activity +author: "Rod Soto, Splunk" +date: "2020-04-15" +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." id: a9ef59cf-e981-4e66-9eef-bb049f695c09 -version: 1 -date: '2020-04-15' -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. -author: Rod Soto, Splunk -type: ESCU +name: "Kubernetes Scanning Activity" +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." references: -- https://github.com/splunk/cloud-datamodel-security-research + - "https://github.com/splunk/cloud-datamodel-security-research" tags: - analytics_story: Kubernetes Scanning Activity - usecase: Security Monitoring + analytics_story: "Kubernetes Scanning Activity" category: - - Cloud Security + - "Cloud Security" + usecase: "Security Monitoring" +type: ESCU +version: 1 From 5cdd5ac784f0b5e459d8622ccf078f40fbe0254e Mon Sep 17 00:00:00 2001 From: Rod Soto Date: Wed, 20 May 2020 14:41:09 -0400 Subject: [PATCH 02/14] fixedawsmacrosnametoaz --- detections/kubernetes_azure_scan_fingerprint.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/detections/kubernetes_azure_scan_fingerprint.yml b/detections/kubernetes_azure_scan_fingerprint.yml index 1dc3988edc..991e86871d 100644 --- a/detections/kubernetes_azure_scan_fingerprint.yml +++ b/detections/kubernetes_azure_scan_fingerprint.yml @@ -6,7 +6,7 @@ id: c5e5bd5c-1013-4841-8b23-e7b3253c840a known_false_positives: "Not all unauthenticated requests are malicious, but source IPs, userAgent, verb, request URI and response status will provide context." name: "Azure AKS Kubernetes cluster scan detection" references: [] -search: "sourcetype=mscs:storage:blob:json category=kube-audit | spath input=properties.log | search responseStatus.code=401 | table sourceIPs{} userAgent verb requestURI responseStatus.reason |`kubernetes_aws_scan_fingerprint_detection`" +search: "sourcetype=mscs:storage:blob:json category=kube-audit | spath input=properties.log | search responseStatus.code=401 | table sourceIPs{} userAgent verb requestURI responseStatus.reason |`kubernetes_azure_scan_fingerprint_detection`" tags: analytics_story: - "Kubernetes Scanning Activity" From 0748085ecac1760bd04c077009aba0e210816680 Mon Sep 17 00:00:00 2001 From: Rod Soto Date: Wed, 20 May 2020 15:38:53 -0400 Subject: [PATCH 03/14] azpodscandetect --- .../kubernetes_azure_pod_scan_fingerprint.yml | 18 ++++++++++++++++++ ...e_pod_scan_fingerprint_detection_filter.yml | 3 +++ 2 files changed, 21 insertions(+) create mode 100644 detections/kubernetes_azure_pod_scan_fingerprint.yml create mode 100644 macros/kubernetes_azure_pod_scan_fingerprint_detection_filter.yml diff --git a/detections/kubernetes_azure_pod_scan_fingerprint.yml b/detections/kubernetes_azure_pod_scan_fingerprint.yml new file mode 100644 index 0000000000..68d2c2b6c0 --- /dev/null +++ b/detections/kubernetes_azure_pod_scan_fingerprint.yml @@ -0,0 +1,18 @@ +author: "Rod Soto, Splunk" +date: "2020-05-20" +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" +how_to_implement: "You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics" +id: 86aad3e0-732f-4f66-bbbc-70df448e461d +known_false_positives: "Not all unauthenticated requests are malicious, but source IPs, userAgent, verb, request URI and response status will provide context." +name: "Azure AKS Kubernetes cluster pod scan detection" +references: [] +search: "sourcetype=mscs:storage:blob:json category=kube-audit | spath input=properties.log | search responseStatus.code=401 | table sourceIPs{} userAgent verb requestURI responseStatus.reason properties.pod |`kubernetes_azure_pod_scan_fingerprint_detection`" +tags: + analytics_story: + - "Kubernetes Scanning Activity" + asset_type: "Azure AKS Kubernetes cluster" + kill_chain_phases: + - Reconnaissance + security_domain: threat +type: ESCU +version: 1 diff --git a/macros/kubernetes_azure_pod_scan_fingerprint_detection_filter.yml b/macros/kubernetes_azure_pod_scan_fingerprint_detection_filter.yml new file mode 100644 index 0000000000..a1e8b5991e --- /dev/null +++ b/macros/kubernetes_azure_pod_scan_fingerprint_detection_filter.yml @@ -0,0 +1,3 @@ +definition: search * +description: Use this macro to add additional filters +name: kubernetes_azure_pod_scan_fingerprint_detection From 2e7d50b6d017026d34c35843bdca36c342deac4b Mon Sep 17 00:00:00 2001 From: Rod Soto Date: Wed, 20 May 2020 19:09:29 -0400 Subject: [PATCH 04/14] newstoryconfsecazk8s --- ...es_azure_detect_sensitive_object_access.yml | 18 ++++++++++++++++++ ...tes_azure_detect_sensitve_object_access.yml | 3 +++ ...rnetes_sensitive_object_access_activity.yml | 15 +++++++++++++++ 3 files changed, 36 insertions(+) create mode 100644 detections/kubernetes_azure_detect_sensitive_object_access.yml create mode 100644 macros/kubernetes_azure_detect_sensitve_object_access.yml create mode 100644 stories/kubernetes_sensitive_object_access_activity.yml diff --git a/detections/kubernetes_azure_detect_sensitive_object_access.yml b/detections/kubernetes_azure_detect_sensitive_object_access.yml new file mode 100644 index 0000000000..1ecaf84d75 --- /dev/null +++ b/detections/kubernetes_azure_detect_sensitive_object_access.yml @@ -0,0 +1,18 @@ +author: "Rod Soto, Splunk" +date: "2020-05-20" +description: "This search provides information on Kubernetes accounts accessing sensitve objects such as configmpas or secrets" +how_to_implement: "You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics" +id: 1bba382b-07fd-4ffa-b390-8002739b76e8 +known_false_positives: "Sensitive object access is not necessarily malicious but user and object context can provide guidance for detection." +name: "Azure AKS Kubernetes cluster senstive object access detection" +references: [] +search: "sourcetype=mscs:storage:blob:json index=azure_test category=kube-audit | spath input=properties.log| search objectRef.resource=secrets OR configmaps |table user.username user.groups{} objectRef.resource objectRef.namespace objectRef.name annotations.authorization.k8s.io/reason |dedup user.username user.groups{} |`kubernetes_azure_detect_sensitve_object_access`" +tags: + analytics_story: + - "Kubernetes Sensitive Object Access Activity" + asset_type: "Azure AKS Kubernetes cluster" + kill_chain_phases: + - Lateral Movement + security_domain: threat +type: ESCU +version: 1 diff --git a/macros/kubernetes_azure_detect_sensitve_object_access.yml b/macros/kubernetes_azure_detect_sensitve_object_access.yml new file mode 100644 index 0000000000..d176d9b8fd --- /dev/null +++ b/macros/kubernetes_azure_detect_sensitve_object_access.yml @@ -0,0 +1,3 @@ +definition: search * +description: Use this macro to add additional filters +name: kubernetes_azure_detect_sensitve_object_access diff --git a/stories/kubernetes_sensitive_object_access_activity.yml b/stories/kubernetes_sensitive_object_access_activity.yml new file mode 100644 index 0000000000..d40e1be34e --- /dev/null +++ b/stories/kubernetes_sensitive_object_access_activity.yml @@ -0,0 +1,15 @@ +author: "Rod Soto, Splunk" +date: "2020-05-20" +description: "This story addresses detection 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." +id: 2574e6d9-7254-4751-8925-0447deeec8ea +name: "Kubernetes Sensitive Object Access Activity" +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." +references: + - https://www.splunk.com/en_us/blog/security/approaching-kubernetes-security-detecting-kubernetes-scan-with-splunk.html +tags: + analytics_story: "Kubernetes Sensitive Object Access Activity" + category: + - "Cloud Security" + usecase: "Security Monitoring" +type: ESCU +version: 1 From 6086fa8e2b0cc5e38479c090cac8d710c92d213e Mon Sep 17 00:00:00 2001 From: Rod Soto Date: Thu, 21 May 2020 18:41:32 -0400 Subject: [PATCH 05/14] azk8srolesto --- ...etes_azure_detect_sensitive_role_access.yml | 18 ++++++++++++++++++ ...etes_azure_detect_sensitive_role_access.yml | 3 +++ stories/kubernetes_sensitive_role_activity.yml | 15 +++++++++++++++ 3 files changed, 36 insertions(+) create mode 100644 detections/kubernetes_azure_detect_sensitive_role_access.yml create mode 100644 macros/kubernetes_azure_detect_sensitive_role_access.yml create mode 100644 stories/kubernetes_sensitive_role_activity.yml diff --git a/detections/kubernetes_azure_detect_sensitive_role_access.yml b/detections/kubernetes_azure_detect_sensitive_role_access.yml new file mode 100644 index 0000000000..b29d57a5b3 --- /dev/null +++ b/detections/kubernetes_azure_detect_sensitive_role_access.yml @@ -0,0 +1,18 @@ +author: "Rod Soto, Splunk" +date: "2020-05-20" +description: "This search provides information on Kubernetes accounts accessing sensitve objects such as configmpas or secrets" +how_to_implement: "You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics" +id: f27349e5-1641-4f6a-9e68-30402be0ad4c +known_false_positives: "Sensitive role resource access is necessary for cluster operation, however source IP, namespace and user group may indicate possible malicious use. " +name: "Azure AKS Kubernetes cluster sensitive role access detection" +references: [] +search: "sourcetype=mscs:storage:blob:json index=azure_test category=kube-audit | spath input=properties.log| search objectRef.resource=clusterroles OR clusterrolebindings | table sourceIPs{} user.username user.groups{} objectRef.namespace requestURI annotations.authorization.k8s.io/reason | dedup user.username user.groups{} |`kubernetes_azure_detect_sensitive_role_access`" +tags: + analytics_story: + - "Kubernetes Sensitive Role Activity" + asset_type: "Azure AKS Kubernetes cluster" + kill_chain_phases: + - Lateral Movement + security_domain: threat +type: ESCU +version: 1 diff --git a/macros/kubernetes_azure_detect_sensitive_role_access.yml b/macros/kubernetes_azure_detect_sensitive_role_access.yml new file mode 100644 index 0000000000..612dfd2272 --- /dev/null +++ b/macros/kubernetes_azure_detect_sensitive_role_access.yml @@ -0,0 +1,3 @@ +definition: search * +description: Use this macro to add additional filters +name: kubernetes_azure_detect_sensitive_role_access diff --git a/stories/kubernetes_sensitive_role_activity.yml b/stories/kubernetes_sensitive_role_activity.yml new file mode 100644 index 0000000000..7d52e04e08 --- /dev/null +++ b/stories/kubernetes_sensitive_role_activity.yml @@ -0,0 +1,15 @@ +author: "Rod Soto, Splunk" +date: "2020-05-20" +description: "This story addresses detection and response around Sensitive Role usage within a Kubernetes clusters against cluster resources and namespaces." +id: 2574e6d9-7254-4751-8925-0447deeec8ea +name: "Kubernetes Sensitive Object Access Activity" +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." +references: + - https://www.splunk.com/en_us/blog/security/approaching-kubernetes-security-detecting-kubernetes-scan-with-splunk.html +tags: + analytics_story: "Kubernetes Sensitive Object Access Activity" + category: + - "Cloud Security" + usecase: "Security Monitoring" +type: ESCU +version: 1 From b4577d54c83b863ebfe1f8d2fa038d073f0257d5 Mon Sep 17 00:00:00 2001 From: Rod Soto Date: Thu, 21 May 2020 18:52:12 -0400 Subject: [PATCH 06/14] fixedazk8srolesto --- detections/kubernetes_azure_detect_sensitive_role_access.yml | 2 +- stories/kubernetes_sensitive_object_access_activity.yml | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/detections/kubernetes_azure_detect_sensitive_role_access.yml b/detections/kubernetes_azure_detect_sensitive_role_access.yml index b29d57a5b3..7c229c6a61 100644 --- a/detections/kubernetes_azure_detect_sensitive_role_access.yml +++ b/detections/kubernetes_azure_detect_sensitive_role_access.yml @@ -6,7 +6,7 @@ id: f27349e5-1641-4f6a-9e68-30402be0ad4c known_false_positives: "Sensitive role resource access is necessary for cluster operation, however source IP, namespace and user group may indicate possible malicious use. " name: "Azure AKS Kubernetes cluster sensitive role access detection" references: [] -search: "sourcetype=mscs:storage:blob:json index=azure_test category=kube-audit | spath input=properties.log| search objectRef.resource=clusterroles OR clusterrolebindings | table sourceIPs{} user.username user.groups{} objectRef.namespace requestURI annotations.authorization.k8s.io/reason | dedup user.username user.groups{} |`kubernetes_azure_detect_sensitive_role_access`" +search: "sourcetype=mscs:storage:blob:json category=kube-audit | spath input=properties.log| search objectRef.resource=clusterroles OR clusterrolebindings | table sourceIPs{} user.username user.groups{} objectRef.namespace requestURI annotations.authorization.k8s.io/reason | dedup user.username user.groups{} |`kubernetes_azure_detect_sensitive_role_access`" tags: analytics_story: - "Kubernetes Sensitive Role Activity" diff --git a/stories/kubernetes_sensitive_object_access_activity.yml b/stories/kubernetes_sensitive_object_access_activity.yml index d40e1be34e..1ff38bbbb2 100644 --- a/stories/kubernetes_sensitive_object_access_activity.yml +++ b/stories/kubernetes_sensitive_object_access_activity.yml @@ -1,6 +1,6 @@ author: "Rod Soto, Splunk" date: "2020-05-20" -description: "This story addresses detection 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." +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." id: 2574e6d9-7254-4751-8925-0447deeec8ea name: "Kubernetes Sensitive Object Access Activity" 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." From 8e44ca15caa728151838ba721bef8304ebca4109 Mon Sep 17 00:00:00 2001 From: Rod Soto Date: Tue, 26 May 2020 22:18:16 -0400 Subject: [PATCH 07/14] RBACauth --- ...e_detect_RBAC_authorizations_by_account.yml | 18 ++++++++++++++++++ ...es_azure_detect_sensitive_object_access.yml | 2 +- ...re_detect_RBAC_authorization_by_account.yml | 3 +++ 3 files changed, 22 insertions(+), 1 deletion(-) create mode 100644 detections/kubernetes_azure_detect_RBAC_authorizations_by_account.yml create mode 100644 macros/kubernetes_azure_detect_RBAC_authorization_by_account.yml diff --git a/detections/kubernetes_azure_detect_RBAC_authorizations_by_account.yml b/detections/kubernetes_azure_detect_RBAC_authorizations_by_account.yml new file mode 100644 index 0000000000..900f3640b4 --- /dev/null +++ b/detections/kubernetes_azure_detect_RBAC_authorizations_by_account.yml @@ -0,0 +1,18 @@ +author: "Rod Soto, Splunk" +date: "2020-05-26" +description: "This search provides information on Kubernetes RBAC authorizations by accounts" +how_to_implement: "You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics" +id: 47af7d20-0607-4079-97d7-7a29af58b54e +known_false_positives: "Not all RBAC Authorications are malicious. RBAC authorizations can uncover malicious activity specially if sensitive Roles have been granted." +name: "Azure AKS Kubernetes RBAC authorizations by account" +references: [] +search: "sourcetype:mscs:storage:blob:json category=kube-audit | spath input=properties.log | search annotations.authorization.k8s.io/reason=* | table sourceIPs{} user.username userAgent annotations.authorization.k8s.io/reason |stats count by user.username annotations.authorization.k8s.io/reason | rare user.username annotations.authorization.k8s.io/reason |`kubernetes_azure_detect_RBAC_authorization_by_account`" +tags: + analytics_story: + - "Kubernetes Sensitive Role Activity" + asset_type: "Azure AKS Kubernetes cluster" + kill_chain_phases: + - Lateral Movement + security_domain: threat +type: ESCU +version: 1 diff --git a/detections/kubernetes_azure_detect_sensitive_object_access.yml b/detections/kubernetes_azure_detect_sensitive_object_access.yml index 1ecaf84d75..78dc53a010 100644 --- a/detections/kubernetes_azure_detect_sensitive_object_access.yml +++ b/detections/kubernetes_azure_detect_sensitive_object_access.yml @@ -4,7 +4,7 @@ description: "This search provides information on Kubernetes accounts accessing how_to_implement: "You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics" id: 1bba382b-07fd-4ffa-b390-8002739b76e8 known_false_positives: "Sensitive object access is not necessarily malicious but user and object context can provide guidance for detection." -name: "Azure AKS Kubernetes cluster senstive object access detection" +name: "Azure AKS Kubernetes cluster sensitive object access detection" references: [] search: "sourcetype=mscs:storage:blob:json index=azure_test category=kube-audit | spath input=properties.log| search objectRef.resource=secrets OR configmaps |table user.username user.groups{} objectRef.resource objectRef.namespace objectRef.name annotations.authorization.k8s.io/reason |dedup user.username user.groups{} |`kubernetes_azure_detect_sensitve_object_access`" tags: diff --git a/macros/kubernetes_azure_detect_RBAC_authorization_by_account.yml b/macros/kubernetes_azure_detect_RBAC_authorization_by_account.yml new file mode 100644 index 0000000000..e4228376b0 --- /dev/null +++ b/macros/kubernetes_azure_detect_RBAC_authorization_by_account.yml @@ -0,0 +1,3 @@ +definition: search * +description: Use this macro to add additional filters +name: kubernetes_azure_detect_RBAC_authorization_by_account From 8c43f898c5234a02ea58ac2bf495b3efeec1dedc Mon Sep 17 00:00:00 2001 From: Rod Soto Date: Tue, 26 May 2020 22:21:45 -0400 Subject: [PATCH 08/14] fixed description RBAC --- .../kubernetes_azure_detect_RBAC_authorizations_by_account.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/detections/kubernetes_azure_detect_RBAC_authorizations_by_account.yml b/detections/kubernetes_azure_detect_RBAC_authorizations_by_account.yml index 900f3640b4..159446c803 100644 --- a/detections/kubernetes_azure_detect_RBAC_authorizations_by_account.yml +++ b/detections/kubernetes_azure_detect_RBAC_authorizations_by_account.yml @@ -1,6 +1,6 @@ author: "Rod Soto, Splunk" date: "2020-05-26" -description: "This search provides information on Kubernetes RBAC authorizations by accounts" +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" how_to_implement: "You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics" id: 47af7d20-0607-4079-97d7-7a29af58b54e known_false_positives: "Not all RBAC Authorications are malicious. RBAC authorizations can uncover malicious activity specially if sensitive Roles have been granted." From 1bbc7d1728c805c2fd3537a553670d4cf9c1b815 Mon Sep 17 00:00:00 2001 From: Rod Soto Date: Tue, 26 May 2020 22:40:16 -0400 Subject: [PATCH 09/14] fixedanemsaddedservaccount --- ...es_azure_detect_sensitive_object_access.yml | 2 +- ...rvice_accounts_forbidden_failure_access.yml | 18 ++++++++++++++++++ ...s_azure_detect_sensitive_object_access.yml} | 2 +- ...rvice_accounts_forbidden_failure_access.yml | 3 +++ 4 files changed, 23 insertions(+), 2 deletions(-) create mode 100644 detections/kubernetes_azure_detect_service_accounts_forbidden_failure_access.yml rename macros/{kubernetes_azure_detect_sensitve_object_access.yml => kubernetes_azure_detect_sensitive_object_access.yml} (58%) create mode 100644 macros/kubernetes_azure_detect_service_accounts_forbidden_failure_access.yml diff --git a/detections/kubernetes_azure_detect_sensitive_object_access.yml b/detections/kubernetes_azure_detect_sensitive_object_access.yml index 78dc53a010..b24ed7a2b2 100644 --- a/detections/kubernetes_azure_detect_sensitive_object_access.yml +++ b/detections/kubernetes_azure_detect_sensitive_object_access.yml @@ -6,7 +6,7 @@ id: 1bba382b-07fd-4ffa-b390-8002739b76e8 known_false_positives: "Sensitive object access is not necessarily malicious but user and object context can provide guidance for detection." name: "Azure AKS Kubernetes cluster sensitive object access detection" references: [] -search: "sourcetype=mscs:storage:blob:json index=azure_test category=kube-audit | spath input=properties.log| search objectRef.resource=secrets OR configmaps |table user.username user.groups{} objectRef.resource objectRef.namespace objectRef.name annotations.authorization.k8s.io/reason |dedup user.username user.groups{} |`kubernetes_azure_detect_sensitve_object_access`" +search: "sourcetype=mscs:storage:blob:json index=azure_test category=kube-audit | spath input=properties.log| search objectRef.resource=secrets OR configmaps |table user.username user.groups{} objectRef.resource objectRef.namespace objectRef.name annotations.authorization.k8s.io/reason |dedup user.username user.groups{} |`kubernetes_azure_detect_sensitive_object_access`" tags: analytics_story: - "Kubernetes Sensitive Object Access Activity" diff --git a/detections/kubernetes_azure_detect_service_accounts_forbidden_failure_access.yml b/detections/kubernetes_azure_detect_service_accounts_forbidden_failure_access.yml new file mode 100644 index 0000000000..f10824935e --- /dev/null +++ b/detections/kubernetes_azure_detect_service_accounts_forbidden_failure_access.yml @@ -0,0 +1,18 @@ +author: "Rod Soto, Splunk" +date: "2020-05-20" +description: "This search provides information on Kubernetes service accounts with failure or forbidden access status" +how_to_implement: "You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics" +id: 019690d7-420f-4da0-b320-f27b09961514 +known_false_positives: "This search can give false positives as there might be inherent issues with authentications and permissions at cluster." +name: "Azure AKS Kubernetes cluster sensitive object access detection" +references: [] +search: "sourcetype=mscs:storage:blob:json category=kube-audit | spath input=properties.log | search user.groups{}=system:serviceaccounts* responseStatus.reason=Forbidden | table sourceIPs{} user.username userAgent verb responseStatus.reason responseStatus.status properties.pod objectRef.namespace |`kubernetes_azure_detect_service_accounts_forbidden_failure_access`" +tags: + analytics_story: + - "Kubernetes Sensitive Object Access Activity" + asset_type: "Azure AKS Kubernetes cluster" + kill_chain_phases: + - Lateral Movement + security_domain: threat +type: ESCU +version: 1 diff --git a/macros/kubernetes_azure_detect_sensitve_object_access.yml b/macros/kubernetes_azure_detect_sensitive_object_access.yml similarity index 58% rename from macros/kubernetes_azure_detect_sensitve_object_access.yml rename to macros/kubernetes_azure_detect_sensitive_object_access.yml index d176d9b8fd..8fac13d818 100644 --- a/macros/kubernetes_azure_detect_sensitve_object_access.yml +++ b/macros/kubernetes_azure_detect_sensitive_object_access.yml @@ -1,3 +1,3 @@ definition: search * description: Use this macro to add additional filters -name: kubernetes_azure_detect_sensitve_object_access +name: kubernetes_azure_detect_sensitive_object_access diff --git a/macros/kubernetes_azure_detect_service_accounts_forbidden_failure_access.yml b/macros/kubernetes_azure_detect_service_accounts_forbidden_failure_access.yml new file mode 100644 index 0000000000..9cef6c37b8 --- /dev/null +++ b/macros/kubernetes_azure_detect_service_accounts_forbidden_failure_access.yml @@ -0,0 +1,3 @@ +definition: search * +description: Use this macro to add additional filters +name: kubernetes_azure_detect_service_accounts_forbidden_failure_access From 46803f5ea0b815cafd2ad938470d7b5a666afdfe Mon Sep 17 00:00:00 2001 From: Rod Soto Date: Tue, 26 May 2020 23:16:07 -0400 Subject: [PATCH 10/14] svacconpodnasp --- ...ctive_service_accounts_by_pod_namespace.yml | 18 ++++++++++++++++++ ...ctive_service_accounts_by_pod_namespace.yml | 3 +++ 2 files changed, 21 insertions(+) create mode 100644 detections/kubernetes_azure_detect_most_active_service_accounts_by_pod_namespace.yml create mode 100644 macros/kubernetes_azure_detect_most_active_service_accounts_by_pod_namespace.yml diff --git a/detections/kubernetes_azure_detect_most_active_service_accounts_by_pod_namespace.yml b/detections/kubernetes_azure_detect_most_active_service_accounts_by_pod_namespace.yml new file mode 100644 index 0000000000..5354724a71 --- /dev/null +++ b/detections/kubernetes_azure_detect_most_active_service_accounts_by_pod_namespace.yml @@ -0,0 +1,18 @@ +author: "Rod Soto, Splunk" +date: "2020-05-26" +description: "This search provides information on Kubernetes service accounts,accessing pods and namespaces by IP address and verb" +how_to_implement: "You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics" +id: 55a2264a-b7f0-45e5-addd-1e5ab3415c72 +known_false_positives: "Not all service accounts interactions are malicious. Analyst must consider IP and verb context when trying to detect maliciousness." +name: "Azure AKS Kubernetes detect most active service accounts by pod and namespaces" +references: [] +search: "sourcetype:mscs:storage:blob:json category=kube-audit | spath input=properties.log | search user.groups{}=system:serviceaccounts* | table sourceIPs{} user.username userAgent verb responseStatus.reason responseStatus.status properties.pod objectRef.namespace | top sourceIPs{} user.username verb responseStatus.status properties.pod objectRef.namespace |`kubernetes_azure_detect_most_active_service_accounts_by_pod_namespace`" +tags: + analytics_story: + - "Kubernetes Sensitive Role Activity" + asset_type: "Azure AKS Kubernetes cluster" + kill_chain_phases: + - Lateral Movement + security_domain: threat +type: ESCU +version: 1 diff --git a/macros/kubernetes_azure_detect_most_active_service_accounts_by_pod_namespace.yml b/macros/kubernetes_azure_detect_most_active_service_accounts_by_pod_namespace.yml new file mode 100644 index 0000000000..27e7a530a7 --- /dev/null +++ b/macros/kubernetes_azure_detect_most_active_service_accounts_by_pod_namespace.yml @@ -0,0 +1,3 @@ +definition: search * +description: Use this macro to add additional filters +name: kubernetes_azure_detect_most_active_service_accounts_by_pod_namespace From 50f3fdbbee9c8dc7d9e1bcb3e08d570f8c720a55 Mon Sep 17 00:00:00 2001 From: Rod Soto Date: Tue, 26 May 2020 23:42:26 -0400 Subject: [PATCH 11/14] kubectlcalls --- ...s_azure_detect_suspicious_kubectl_calls.yml | 18 ++++++++++++++++++ ...s_azure_detect_suspicious_kubectl_calls.yml | 3 +++ 2 files changed, 21 insertions(+) create mode 100644 detections/kubernetes_azure_detect_suspicious_kubectl_calls.yml create mode 100644 macros/kubernetes_azure_detect_suspicious_kubectl_calls.yml diff --git a/detections/kubernetes_azure_detect_suspicious_kubectl_calls.yml b/detections/kubernetes_azure_detect_suspicious_kubectl_calls.yml new file mode 100644 index 0000000000..8ad5c8d80e --- /dev/null +++ b/detections/kubernetes_azure_detect_suspicious_kubectl_calls.yml @@ -0,0 +1,18 @@ +author: "Rod Soto, Splunk" +date: "2020-05-26" +description: "This search provides information on Kubectl calls with IP, verb namespace and object access context" +how_to_implement: "You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics" +id: 4b6d1ba8-0000-4cec-87e6-6cbbd71651b5 +known_false_positives: "Kubectl calls are not malicious by nature. However source IP, verb and Object can reveal potential malicious activity, specially suspicious IPs and sensitive objects such as configmaps or secrets" +name: "Azure AKS Kubernetes detect suspicious kubectl calls" +references: [] +search: "sourcetype=mscs:storage:blob:json category=kube-audit | spath input=properties.log| search objectRef.resource=secrets OR configmaps |table user.username user.groups{} objectRef.resource objectRef.namespace objectRef.name annotations.authorization.k8s.io/reason |dedup user.username user.groups{} |`kubernetes_azure_detect_suspicious_kubectl_calls`" +tags: + analytics_story: + - "Kubernetes Sensitive Object Access Activity" + asset_type: "Azure AKS Kubernetes cluster" + kill_chain_phases: + - Lateral Movement + security_domain: threat +type: ESCU +version: 1 diff --git a/macros/kubernetes_azure_detect_suspicious_kubectl_calls.yml b/macros/kubernetes_azure_detect_suspicious_kubectl_calls.yml new file mode 100644 index 0000000000..ac101e0a94 --- /dev/null +++ b/macros/kubernetes_azure_detect_suspicious_kubectl_calls.yml @@ -0,0 +1,3 @@ +definition: search * +description: Use this macro to add additional filters +name: kubernetes_azure_detect_suspicious_kubectl_calls From 9f2710bfde17c128d9bb75978caddf764a68eaa9 Mon Sep 17 00:00:00 2001 From: bpatel Date: Wed, 3 Jun 2020 13:10:30 -0700 Subject: [PATCH 12/14] updating files to make sure validate passes --- ...tive_service_accounts_by_pod_namespace.yml | 4 +- ..._detect_rbac_authorization_by_account.yml} | 4 +- ...s_azure_detect_sensitive_object_access.yml | 4 +- ...tes_azure_detect_sensitive_role_access.yml | 4 +- ...vice_accounts_forbidden_failure_access.yml | 4 +- ..._azure_detect_suspicious_kubectl_calls.yml | 4 +- .../kubernetes_azure_pod_scan_fingerprint.yml | 4 +- .../kubernetes_azure_scan_fingerprint.yml | 4 +- macros/kubernetes_azure.yml | 3 + ...e_detect_RBAC_authorization_by_account.yml | 2 +- ...tive_service_accounts_by_pod_namespace.yml | 2 +- ...s_azure_detect_sensitive_object_access.yml | 2 +- ...tes_azure_detect_sensitive_role_access.yml | 2 +- ...vice_accounts_forbidden_failure_access.yml | 2 +- ..._azure_detect_suspicious_kubectl_calls.yml | 2 +- ..._pod_scan_fingerprint_detection_filter.yml | 2 +- ...ernetes_azure_scan_fingerprint_filter.yml} | 2 +- package/default/analytic_stories.conf | 172 ++++++---- ...l_investigate_pass_the_ticket_attempts.xml | 2 +- package/default/macros.conf | 70 +++- package/default/savedsearches.conf | 320 +++++++++++++++++- package/default/transforms.conf | 2 +- package/default/use_case_library.conf | 234 +++++++++---- .../kubernetes_sensitive_role_activity.yml | 4 +- 24 files changed, 686 insertions(+), 169 deletions(-) rename detections/{kubernetes_azure_detect_RBAC_authorizations_by_account.yml => kubernetes_azure_detect_rbac_authorization_by_account.yml} (92%) create mode 100644 macros/kubernetes_azure.yml rename macros/{kubernetes_azure_scan_fingerprint_detection_filter.yml => kubernetes_azure_scan_fingerprint_filter.yml} (60%) diff --git a/detections/kubernetes_azure_detect_most_active_service_accounts_by_pod_namespace.yml b/detections/kubernetes_azure_detect_most_active_service_accounts_by_pod_namespace.yml index 5354724a71..2545cacc05 100644 --- a/detections/kubernetes_azure_detect_most_active_service_accounts_by_pod_namespace.yml +++ b/detections/kubernetes_azure_detect_most_active_service_accounts_by_pod_namespace.yml @@ -4,9 +4,9 @@ description: "This search provides information on Kubernetes service accounts,ac how_to_implement: "You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics" id: 55a2264a-b7f0-45e5-addd-1e5ab3415c72 known_false_positives: "Not all service accounts interactions are malicious. Analyst must consider IP and verb context when trying to detect maliciousness." -name: "Azure AKS Kubernetes detect most active service accounts by pod and namespaces" +name: "Kubernetes Azure detect most active service accounts by pod namespace" references: [] -search: "sourcetype:mscs:storage:blob:json category=kube-audit | spath input=properties.log | search user.groups{}=system:serviceaccounts* | table sourceIPs{} user.username userAgent verb responseStatus.reason responseStatus.status properties.pod objectRef.namespace | top sourceIPs{} user.username verb responseStatus.status properties.pod objectRef.namespace |`kubernetes_azure_detect_most_active_service_accounts_by_pod_namespace`" +search: "sourcetype:mscs:storage:blob:json category=kube-audit | spath input=properties.log | search user.groups{}=system:serviceaccounts* | table sourceIPs{} user.username userAgent verb responseStatus.reason responseStatus.status properties.pod objectRef.namespace | top sourceIPs{} user.username verb responseStatus.status properties.pod objectRef.namespace |`kubernetes_azure_detect_most_active_service_accounts_by_pod_namespace_filter`" tags: analytics_story: - "Kubernetes Sensitive Role Activity" diff --git a/detections/kubernetes_azure_detect_RBAC_authorizations_by_account.yml b/detections/kubernetes_azure_detect_rbac_authorization_by_account.yml similarity index 92% rename from detections/kubernetes_azure_detect_RBAC_authorizations_by_account.yml rename to detections/kubernetes_azure_detect_rbac_authorization_by_account.yml index 159446c803..9186dfae04 100644 --- a/detections/kubernetes_azure_detect_RBAC_authorizations_by_account.yml +++ b/detections/kubernetes_azure_detect_rbac_authorization_by_account.yml @@ -4,9 +4,9 @@ description: "This search provides information on Kubernetes RBAC authorizations how_to_implement: "You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics" id: 47af7d20-0607-4079-97d7-7a29af58b54e known_false_positives: "Not all RBAC Authorications are malicious. RBAC authorizations can uncover malicious activity specially if sensitive Roles have been granted." -name: "Azure AKS Kubernetes RBAC authorizations by account" +name: "Kubernetes Azure detect RBAC authorization by account" references: [] -search: "sourcetype:mscs:storage:blob:json category=kube-audit | spath input=properties.log | search annotations.authorization.k8s.io/reason=* | table sourceIPs{} user.username userAgent annotations.authorization.k8s.io/reason |stats count by user.username annotations.authorization.k8s.io/reason | rare user.username annotations.authorization.k8s.io/reason |`kubernetes_azure_detect_RBAC_authorization_by_account`" +search: "sourcetype:mscs:storage:blob:json category=kube-audit | spath input=properties.log | search annotations.authorization.k8s.io/reason=* | table sourceIPs{} user.username userAgent annotations.authorization.k8s.io/reason |stats count by user.username annotations.authorization.k8s.io/reason | rare user.username annotations.authorization.k8s.io/reason |`kubernetes_azure_detect_rbac_authorization_by_account_filter`" tags: analytics_story: - "Kubernetes Sensitive Role Activity" diff --git a/detections/kubernetes_azure_detect_sensitive_object_access.yml b/detections/kubernetes_azure_detect_sensitive_object_access.yml index b24ed7a2b2..2726aea834 100644 --- a/detections/kubernetes_azure_detect_sensitive_object_access.yml +++ b/detections/kubernetes_azure_detect_sensitive_object_access.yml @@ -4,9 +4,9 @@ description: "This search provides information on Kubernetes accounts accessing how_to_implement: "You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics" id: 1bba382b-07fd-4ffa-b390-8002739b76e8 known_false_positives: "Sensitive object access is not necessarily malicious but user and object context can provide guidance for detection." -name: "Azure AKS Kubernetes cluster sensitive object access detection" +name: "Kubernetes Azure detect sensitive object access" references: [] -search: "sourcetype=mscs:storage:blob:json index=azure_test category=kube-audit | spath input=properties.log| search objectRef.resource=secrets OR configmaps |table user.username user.groups{} objectRef.resource objectRef.namespace objectRef.name annotations.authorization.k8s.io/reason |dedup user.username user.groups{} |`kubernetes_azure_detect_sensitive_object_access`" +search: "`kubernetes_azure` category=kube-audit | spath input=properties.log| search objectRef.resource=secrets OR configmaps |table user.username user.groups{} objectRef.resource objectRef.namespace objectRef.name annotations.authorization.k8s.io/reason |dedup user.username user.groups{} |`kubernetes_azure_detect_sensitive_object_access_filter`" tags: analytics_story: - "Kubernetes Sensitive Object Access Activity" diff --git a/detections/kubernetes_azure_detect_sensitive_role_access.yml b/detections/kubernetes_azure_detect_sensitive_role_access.yml index 7c229c6a61..0201873217 100644 --- a/detections/kubernetes_azure_detect_sensitive_role_access.yml +++ b/detections/kubernetes_azure_detect_sensitive_role_access.yml @@ -4,9 +4,9 @@ description: "This search provides information on Kubernetes accounts accessing how_to_implement: "You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics" id: f27349e5-1641-4f6a-9e68-30402be0ad4c known_false_positives: "Sensitive role resource access is necessary for cluster operation, however source IP, namespace and user group may indicate possible malicious use. " -name: "Azure AKS Kubernetes cluster sensitive role access detection" +name: "Kubernetes Azure detect sensitive role access" references: [] -search: "sourcetype=mscs:storage:blob:json category=kube-audit | spath input=properties.log| search objectRef.resource=clusterroles OR clusterrolebindings | table sourceIPs{} user.username user.groups{} objectRef.namespace requestURI annotations.authorization.k8s.io/reason | dedup user.username user.groups{} |`kubernetes_azure_detect_sensitive_role_access`" +search: "`kubernetes_azure` category=kube-audit | spath input=properties.log| search objectRef.resource=clusterroles OR clusterrolebindings | table sourceIPs{} user.username user.groups{} objectRef.namespace requestURI annotations.authorization.k8s.io/reason | dedup user.username user.groups{} |`kubernetes_azure_detect_sensitive_role_access_filter`" tags: analytics_story: - "Kubernetes Sensitive Role Activity" diff --git a/detections/kubernetes_azure_detect_service_accounts_forbidden_failure_access.yml b/detections/kubernetes_azure_detect_service_accounts_forbidden_failure_access.yml index f10824935e..f13081df0e 100644 --- a/detections/kubernetes_azure_detect_service_accounts_forbidden_failure_access.yml +++ b/detections/kubernetes_azure_detect_service_accounts_forbidden_failure_access.yml @@ -4,9 +4,9 @@ description: "This search provides information on Kubernetes service accounts wi how_to_implement: "You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics" id: 019690d7-420f-4da0-b320-f27b09961514 known_false_positives: "This search can give false positives as there might be inherent issues with authentications and permissions at cluster." -name: "Azure AKS Kubernetes cluster sensitive object access detection" +name: "Kubernetes Azure detect service accounts forbidden failure access" references: [] -search: "sourcetype=mscs:storage:blob:json category=kube-audit | spath input=properties.log | search user.groups{}=system:serviceaccounts* responseStatus.reason=Forbidden | table sourceIPs{} user.username userAgent verb responseStatus.reason responseStatus.status properties.pod objectRef.namespace |`kubernetes_azure_detect_service_accounts_forbidden_failure_access`" +search: "`kubernetes_azure` category=kube-audit | spath input=properties.log | search user.groups{}=system:serviceaccounts* responseStatus.reason=Forbidden | table sourceIPs{} user.username userAgent verb responseStatus.reason responseStatus.status properties.pod objectRef.namespace |`kubernetes_azure_detect_service_accounts_forbidden_failure_access_filter`" tags: analytics_story: - "Kubernetes Sensitive Object Access Activity" diff --git a/detections/kubernetes_azure_detect_suspicious_kubectl_calls.yml b/detections/kubernetes_azure_detect_suspicious_kubectl_calls.yml index 8ad5c8d80e..f16bacfe26 100644 --- a/detections/kubernetes_azure_detect_suspicious_kubectl_calls.yml +++ b/detections/kubernetes_azure_detect_suspicious_kubectl_calls.yml @@ -4,9 +4,9 @@ description: "This search provides information on Kubectl calls with IP, verb na how_to_implement: "You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics" id: 4b6d1ba8-0000-4cec-87e6-6cbbd71651b5 known_false_positives: "Kubectl calls are not malicious by nature. However source IP, verb and Object can reveal potential malicious activity, specially suspicious IPs and sensitive objects such as configmaps or secrets" -name: "Azure AKS Kubernetes detect suspicious kubectl calls" +name: "Kubernetes Azure detect suspicious kubectl calls" references: [] -search: "sourcetype=mscs:storage:blob:json category=kube-audit | spath input=properties.log| search objectRef.resource=secrets OR configmaps |table user.username user.groups{} objectRef.resource objectRef.namespace objectRef.name annotations.authorization.k8s.io/reason |dedup user.username user.groups{} |`kubernetes_azure_detect_suspicious_kubectl_calls`" +search: "`kubernetes_azure` category=kube-audit | spath input=properties.log| search objectRef.resource=secrets OR configmaps |table user.username user.groups{} objectRef.resource objectRef.namespace objectRef.name annotations.authorization.k8s.io/reason |dedup user.username user.groups{} |`kubernetes_azure_detect_suspicious_kubectl_calls_filter`" tags: analytics_story: - "Kubernetes Sensitive Object Access Activity" diff --git a/detections/kubernetes_azure_pod_scan_fingerprint.yml b/detections/kubernetes_azure_pod_scan_fingerprint.yml index 68d2c2b6c0..4dad0447e8 100644 --- a/detections/kubernetes_azure_pod_scan_fingerprint.yml +++ b/detections/kubernetes_azure_pod_scan_fingerprint.yml @@ -4,9 +4,9 @@ description: "This search provides information of unauthenticated requests via s how_to_implement: "You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics" id: 86aad3e0-732f-4f66-bbbc-70df448e461d known_false_positives: "Not all unauthenticated requests are malicious, but source IPs, userAgent, verb, request URI and response status will provide context." -name: "Azure AKS Kubernetes cluster pod scan detection" +name: "Kubernetes Azure pod scan fingerprint" references: [] -search: "sourcetype=mscs:storage:blob:json category=kube-audit | spath input=properties.log | search responseStatus.code=401 | table sourceIPs{} userAgent verb requestURI responseStatus.reason properties.pod |`kubernetes_azure_pod_scan_fingerprint_detection`" +search: "`kubernetes_azure` category=kube-audit | spath input=properties.log | search responseStatus.code=401 | table sourceIPs{} userAgent verb requestURI responseStatus.reason properties.pod |`kubernetes_azure_pod_scan_fingerprint_filter`" tags: analytics_story: - "Kubernetes Scanning Activity" diff --git a/detections/kubernetes_azure_scan_fingerprint.yml b/detections/kubernetes_azure_scan_fingerprint.yml index 991e86871d..d35cf6ce49 100644 --- a/detections/kubernetes_azure_scan_fingerprint.yml +++ b/detections/kubernetes_azure_scan_fingerprint.yml @@ -4,9 +4,9 @@ description: "This search provides information of unauthenticated requests via s how_to_implement: "You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics" id: c5e5bd5c-1013-4841-8b23-e7b3253c840a known_false_positives: "Not all unauthenticated requests are malicious, but source IPs, userAgent, verb, request URI and response status will provide context." -name: "Azure AKS Kubernetes cluster scan detection" +name: "Kubernetes Azure scan fingerprint" references: [] -search: "sourcetype=mscs:storage:blob:json category=kube-audit | spath input=properties.log | search responseStatus.code=401 | table sourceIPs{} userAgent verb requestURI responseStatus.reason |`kubernetes_azure_scan_fingerprint_detection`" +search: "`kubernetes_azure` category=kube-audit | spath input=properties.log | search responseStatus.code=401 | table sourceIPs{} userAgent verb requestURI responseStatus.reason |`kubernetes_azure_scan_fingerprint_filter`" tags: analytics_story: - "Kubernetes Scanning Activity" diff --git a/macros/kubernetes_azure.yml b/macros/kubernetes_azure.yml new file mode 100644 index 0000000000..2a23d362e5 --- /dev/null +++ b/macros/kubernetes_azure.yml @@ -0,0 +1,3 @@ +definition: sourcetype=mscs:storage:blob:json +description: customer specific splunk configurations(eg- index, source, sourcetype) for Kubernetes data from Azure. Replace the macro definition with configurations for your Splunk Environmnent. +name: kubernetes_azure diff --git a/macros/kubernetes_azure_detect_RBAC_authorization_by_account.yml b/macros/kubernetes_azure_detect_RBAC_authorization_by_account.yml index e4228376b0..964e8e2e04 100644 --- a/macros/kubernetes_azure_detect_RBAC_authorization_by_account.yml +++ b/macros/kubernetes_azure_detect_RBAC_authorization_by_account.yml @@ -1,3 +1,3 @@ definition: search * description: Use this macro to add additional filters -name: kubernetes_azure_detect_RBAC_authorization_by_account +name: kubernetes_azure_detect_rbac_authorization_by_account_filter diff --git a/macros/kubernetes_azure_detect_most_active_service_accounts_by_pod_namespace.yml b/macros/kubernetes_azure_detect_most_active_service_accounts_by_pod_namespace.yml index 27e7a530a7..86245d47a6 100644 --- a/macros/kubernetes_azure_detect_most_active_service_accounts_by_pod_namespace.yml +++ b/macros/kubernetes_azure_detect_most_active_service_accounts_by_pod_namespace.yml @@ -1,3 +1,3 @@ definition: search * description: Use this macro to add additional filters -name: kubernetes_azure_detect_most_active_service_accounts_by_pod_namespace +name: kubernetes_azure_detect_most_active_service_accounts_by_pod_namespace_filter diff --git a/macros/kubernetes_azure_detect_sensitive_object_access.yml b/macros/kubernetes_azure_detect_sensitive_object_access.yml index 8fac13d818..dce2bd7be8 100644 --- a/macros/kubernetes_azure_detect_sensitive_object_access.yml +++ b/macros/kubernetes_azure_detect_sensitive_object_access.yml @@ -1,3 +1,3 @@ definition: search * description: Use this macro to add additional filters -name: kubernetes_azure_detect_sensitive_object_access +name: kubernetes_azure_detect_sensitive_object_access_filter diff --git a/macros/kubernetes_azure_detect_sensitive_role_access.yml b/macros/kubernetes_azure_detect_sensitive_role_access.yml index 612dfd2272..54bf94d705 100644 --- a/macros/kubernetes_azure_detect_sensitive_role_access.yml +++ b/macros/kubernetes_azure_detect_sensitive_role_access.yml @@ -1,3 +1,3 @@ definition: search * description: Use this macro to add additional filters -name: kubernetes_azure_detect_sensitive_role_access +name: kubernetes_azure_detect_sensitive_role_access_filter diff --git a/macros/kubernetes_azure_detect_service_accounts_forbidden_failure_access.yml b/macros/kubernetes_azure_detect_service_accounts_forbidden_failure_access.yml index 9cef6c37b8..0483b01baa 100644 --- a/macros/kubernetes_azure_detect_service_accounts_forbidden_failure_access.yml +++ b/macros/kubernetes_azure_detect_service_accounts_forbidden_failure_access.yml @@ -1,3 +1,3 @@ definition: search * description: Use this macro to add additional filters -name: kubernetes_azure_detect_service_accounts_forbidden_failure_access +name: kubernetes_azure_detect_service_accounts_forbidden_failure_access_filter diff --git a/macros/kubernetes_azure_detect_suspicious_kubectl_calls.yml b/macros/kubernetes_azure_detect_suspicious_kubectl_calls.yml index ac101e0a94..9f57d71281 100644 --- a/macros/kubernetes_azure_detect_suspicious_kubectl_calls.yml +++ b/macros/kubernetes_azure_detect_suspicious_kubectl_calls.yml @@ -1,3 +1,3 @@ definition: search * description: Use this macro to add additional filters -name: kubernetes_azure_detect_suspicious_kubectl_calls +name: kubernetes_azure_detect_suspicious_kubectl_calls_filter diff --git a/macros/kubernetes_azure_pod_scan_fingerprint_detection_filter.yml b/macros/kubernetes_azure_pod_scan_fingerprint_detection_filter.yml index a1e8b5991e..0b2ca96cbb 100644 --- a/macros/kubernetes_azure_pod_scan_fingerprint_detection_filter.yml +++ b/macros/kubernetes_azure_pod_scan_fingerprint_detection_filter.yml @@ -1,3 +1,3 @@ definition: search * description: Use this macro to add additional filters -name: kubernetes_azure_pod_scan_fingerprint_detection +name: kubernetes_azure_pod_scan_fingerprint_detection_filter diff --git a/macros/kubernetes_azure_scan_fingerprint_detection_filter.yml b/macros/kubernetes_azure_scan_fingerprint_filter.yml similarity index 60% rename from macros/kubernetes_azure_scan_fingerprint_detection_filter.yml rename to macros/kubernetes_azure_scan_fingerprint_filter.yml index 1c98d00ea1..caed65bae0 100644 --- a/macros/kubernetes_azure_scan_fingerprint_detection_filter.yml +++ b/macros/kubernetes_azure_scan_fingerprint_filter.yml @@ -1,3 +1,3 @@ definition: search * description: Use this macro to add additional filters -name: kubernetes_azure_scan_fingerprint_detection +name: kubernetes_azure_scan_fingerprint_filter diff --git a/package/default/analytic_stories.conf b/package/default/analytic_stories.conf index 492b5aa4ab..f35a4eccd3 100644 --- a/package/default/analytic_stories.conf +++ b/package/default/analytic_stories.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-14T08:00:44 UTC +# On Date: 2020-06-03T20:09:14 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 Cross Account Activity From Previously Unseen Account - Rule"] mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - AWS Investigate User Activities By Source User"] +investigative_searches = ["ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By Source User"] support_searches = ["ESCU - Previously Seen AWS Cross Account Activity"] data_models = [] providing_technologies = none @@ -34,8 +34,8 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["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"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details"] -support_searches = ["ESCU - Previously Seen EC2 AMIs", "ESCU - Previously Seen EC2 Launches By User", "ESCU - Previously Seen EC2 Instance Types", "ESCU - Previously Seen AWS Regions"] +investigative_searches = ["ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] +support_searches = ["ESCU - Previously Seen EC2 Instance Types", "ESCU - Previously Seen EC2 Launches By User", "ESCU - Previously Seen EC2 AMIs", "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. @@ -53,8 +53,8 @@ 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"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC"]} -investigative_searches = ["ESCU - AWS Network ACL Details from ID", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio"] -support_searches = ["ESCU - Baseline of Network ACL Activity by ARN", "ESCU - Baseline of blocked outbound traffic from AWS"] +investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Process Info", "ESCU - Get DNS traffic ratio"] +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. @@ -69,7 +69,7 @@ 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"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Country"] +investigative_searches = ["ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From City"] support_searches = ["ESCU - Previously Seen AWS Provisioning Activity Sources"] data_models = [] providing_technologies = none @@ -86,8 +86,8 @@ 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"], "nist": ["DE.CM", "DE.DP", "ID.AM", "PR.AC"]} -investigative_searches = ["ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History", "ESCU - Get Notable Info"] -support_searches = ["ESCU - Baseline of API Calls per User ARN", "ESCU - Baseline of Security Group Activity by ARN", "ESCU - Create a list of approved AWS service accounts", "ESCU - Previously seen API call per user roles in CloudTrail"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Investigate AWS User Activities by user field"] +support_searches = ["ESCU - Baseline of Security Group Activity by ARN", "ESCU - Baseline of API Calls per User ARN", "ESCU - Create a list of approved AWS service accounts", "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. @@ -105,7 +105,7 @@ version = 1 reference = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] detection_searches = ["ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Short Lived Windows Accounts - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078", "T1136"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Logon Rights Modifications For User"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] support_searches = [] data_models = ["Change"] providing_technologies = none @@ -121,7 +121,7 @@ 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"], "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 - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web POSTs From src", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web POSTs From src", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -150,7 +150,7 @@ 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"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable History"] support_searches = ["ESCU - Count of assets by category"] data_models = ["Network_Sessions"] providing_technologies = none @@ -166,7 +166,7 @@ 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 Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Email Info"] +investigative_searches = ["ESCU - Get Emails From Specific Sender", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Email Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] support_searches = ["ESCU - DNSTwist Domain Names"] data_models = ["Email", "Network_Resolution", "Web"] providing_technologies = none @@ -184,8 +184,8 @@ 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 - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get Notable Info", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details"] -support_searches = ["ESCU - Previously Seen Cloud Compute Instance Types", "ESCU - Previously Seen Cloud Compute Creations By User", "ESCU - Previously Seen Cloud Compute Images", "ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK", "ESCU - Previously Seen Cloud Regions"] +investigative_searches = ["ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] +support_searches = ["ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK", "ESCU - Previously Seen Cloud Compute Instance Types", "ESCU - Previously Seen Cloud Compute Creations By User", "ESCU - Previously Seen Cloud Compute Images", "ESCU - Previously Seen Cloud Regions"] data_models = ["Cloud_Infrastructure"] 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. @@ -203,7 +203,7 @@ 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"], "nist": ["DE.DP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From src ip"] +investigative_searches = ["ESCU - Investigate Web Activity From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -221,7 +221,7 @@ 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": ["T1043", "T1074", "T1114"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -239,7 +239,7 @@ 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": ["T1043", "T1048", "T1095"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - AWS Network ACL Details from ID", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Parent Process Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Process Info", "ESCU - Get DNS traffic ratio"] 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 @@ -307,7 +307,7 @@ 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 Name Used by Dragonfly Threat Actors - 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": ["T1031", "T1043", "T1050", "T1053", "T1059", "T1064", "T1078", "T1086", "T1089", "T1103", "T1112", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.AT", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Registry Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process File Activity"] +investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process File Activity", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Process Registry Activity"] support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Previously seen command line arguments"] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -326,7 +326,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] detection_searches = ["ESCU - Large Volume of DNS ANY Queries - Rule"] mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -367,7 +367,7 @@ 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"], "mitre_attack": ["T1043"], "nist": ["DE.AE", "DE.CM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio"] +investigative_searches = ["ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Change_Analysis", "Network_Resolution"] providing_technologies = none @@ -383,7 +383,7 @@ 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": ["T1031", "T1050", "T1059", "T1089", "T1112"], "nist": ["DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Previously seen command line arguments"] data_models = ["Endpoint"] providing_technologies = none @@ -399,7 +399,7 @@ 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 13", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1041"], "nist": ["DE.CM", "DE.DP", "PR.IP"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Investigate Web Activity From src ip"] +investigative_searches = ["ESCU - Investigate Web Activity From src ip", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] support_searches = [] data_models = ["Network_Resolution", "Web"] providing_technologies = none @@ -415,7 +415,7 @@ 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": ["T1043", "T1059", "T1072", "T1087", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Add Prohibited Processes to Enterprise Security"] data_models = ["Email", "Endpoint", "Network_Traffic"] providing_technologies = none @@ -433,7 +433,7 @@ 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": ["T1043", "T1059", "T1064", "T1076"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Baseline of DNS Query Length - MLTK", "ESCU - Previously seen command line arguments"] data_models = ["Endpoint", "Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -452,7 +452,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -468,7 +468,7 @@ version = 1 reference = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] detection_searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery", "Reconnaissance"], "mitre_attack": ["T1082"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -496,25 +496,57 @@ modification_date = 2020-04-15 id = a9ef59cf-e981-4e66-9eef-bb049f695c09 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 scan detection - Rule"] +detection_searches = ["ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster 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"]} -investigative_searches = ["ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable Info", "ESCU - Get Notable History"] 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. +[Kubernetes Sensitive Object Access Activity] +category = Cloud Security +creation_date = 2020-05-20 +modification_date = 2020-05-20 +id = 2574e6d9-7254-4751-8925-0447deeec8ea +version = 1 +reference = ["https://www.splunk.com/en_us/blog/security/approaching-kubernetes-security-detecting-kubernetes-scan-with-splunk.html"] +detection_searches = ["ESCU - Kubernetes Azure detect sensitive object access - Rule", "ESCU - Kubernetes Azure detect service accounts forbidden failure access - Rule", "ESCU - Kubernetes Azure detect suspicious kubectl calls - Rule"] +mappings = {"kill_chain_phases": ["Lateral Movement"]} +investigative_searches = [] +support_searches = [] +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. + +[Kubernetes Sensitive Object Access Activity] +category = Cloud Security +creation_date = 2020-05-20 +modification_date = 2020-05-20 +id = 2574e6d9-7254-4751-8925-0447deeec8ew +version = 1 +reference = ["https://www.splunk.com/en_us/blog/security/approaching-kubernetes-security-detecting-kubernetes-scan-with-splunk.html"] +detection_searches = ["ESCU - Kubernetes Azure detect sensitive object access - Rule", "ESCU - Kubernetes Azure detect service accounts forbidden failure access - Rule", "ESCU - Kubernetes Azure detect suspicious kubectl calls - Rule"] +mappings = {"kill_chain_phases": ["Lateral Movement"]} +investigative_searches = [] +support_searches = [] +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 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. + [Lateral Movement] category = Adversary Tactics creation_date = 2020-02-04 modification_date = 2020-02-04 id = 399d65dc-1f08-499b-a259-aad9051f38ad version = 2 -reference = ["https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis", "https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] +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 - 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 9"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053", "T1075", "T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -534,7 +566,7 @@ 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 - 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"], "mitre_attack": ["T1064", "T1086"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -559,8 +591,8 @@ version = 1 reference = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] 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 - All backup logs for host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] -support_searches = ["ESCU - Monitor Successful Backups", "ESCU - Monitor Unsuccessful Backups"] +investigative_searches = ["ESCU - All backup logs for host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History"] +support_searches = ["ESCU - Monitor Unsuccessful Backups", "ESCU - Monitor Successful 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. @@ -575,7 +607,7 @@ 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"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = ["ESCU - Add Prohibited Processes to Enterprise Security"] data_models = ["Endpoint"] providing_technologies = none @@ -592,7 +624,7 @@ version = 1 reference = ["https://learn.cisecurity.org/20-controls-download"] detection_searches = ["ESCU - No Windows Updates in a time frame - Rule"] mappings = {"cis20": ["CIS 18"], "nist": ["PR.MA"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Updates"] providing_technologies = none @@ -610,7 +642,7 @@ version = 1 reference = ["https://technet.microsoft.com/library/bb490939.aspx", "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": ["T1059", "T1089"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Previously seen command line arguments"] data_models = ["Endpoint"] providing_technologies = none @@ -627,8 +659,8 @@ 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 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1064", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] -support_searches = ["ESCU - Previously Seen Running Windows Services", "ESCU - Previously seen command line arguments"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] +support_searches = ["ESCU - Previously seen command line arguments", "ESCU - Previously Seen Running Windows Services"] 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. @@ -670,7 +702,7 @@ 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", "T1064", "T1086", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = ["ESCU - Baseline of Command Line Length - MLTK", "ESCU - Previously seen command line arguments"] data_models = ["Endpoint"] providing_technologies = none @@ -713,7 +745,7 @@ 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 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "PR.AC"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -729,7 +761,7 @@ 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 - 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 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 - 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"], "mitre_attack": ["T1036", "T1043", "T1047", "T1048", "T1053", "T1070", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = ["ESCU - Baseline of Command Line Length - MLTK", "ESCU - Baseline of SMB Traffic - MLTK"] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -745,7 +777,7 @@ version = 1 reference = ["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"] detection_searches = ["ESCU - Detect New Login Attempts to Routers - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] support_searches = [] data_models = ["Authentication"] providing_technologies = none @@ -762,7 +794,7 @@ version = 1 reference = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] detection_searches = ["ESCU - SQL Injection with Long URLs - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -779,7 +811,7 @@ 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": ["T1059", "T1076", "T1082"], "nist": ["DE.AE", "DE.CM", "ID.AM", "ID.RA", "PR.AC", "PR.DS", "PR.IP", "PR.MA", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = ["ESCU - Add Prohibited Processes to Enterprise Security"] data_models = ["Endpoint", "Network_Traffic", "Web"] providing_technologies = none @@ -800,7 +832,7 @@ version = 1 reference = ["https://meltdownattack.com/"] detection_searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule"] mappings = {"cis20": ["CIS 4"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] support_searches = ["ESCU - Systems Ready for Spectre-Meltdown Windows Patch"] data_models = ["Vulnerabilities"] providing_technologies = none @@ -816,7 +848,7 @@ version = 1 reference = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] detection_searches = ["ESCU - Open Redirect in Splunk Web - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -841,7 +873,7 @@ 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"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From src ip"] +investigative_searches = ["ESCU - Investigate Web Activity From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -860,8 +892,8 @@ 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 - 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"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details"] -support_searches = ["ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK", "ESCU - Baseline of Excessive AWS Instances Terminated by User - MLTK", "ESCU - Previously Seen EC2 Launches By User", "ESCU - Previously Seen AWS Regions"] +investigative_searches = ["ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] +support_searches = ["ESCU - Previously Seen EC2 Launches By User", "ESCU - Baseline of Excessive AWS Instances Terminated by User - MLTK", "ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK", "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. @@ -877,7 +909,7 @@ 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"], "nist": ["DE.AE", "DE.DP"]} investigative_searches = ["ESCU - AWS Investigate User Activities By ARN"] -support_searches = ["ESCU - Previously seen users in CloudTrail", "ESCU - Update previously seen users in CloudTrail"] +support_searches = ["ESCU - Update previously seen users in CloudTrail", "ESCU - Previously seen users in CloudTrail"] data_models = [] 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. @@ -892,7 +924,7 @@ 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 - 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"], "nist": ["DE.CM", "DE.DP", "PR.AC", "PR.DS"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Investigate AWS activities via region name"] +investigative_searches = ["ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get All AWS Activity From IP Address", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] support_searches = ["ESCU - Previously seen S3 bucket access by remote IP", "ESCU - Baseline of S3 Bucket deletion activity by ARN"] data_models = [] providing_technologies = none @@ -910,7 +942,7 @@ 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": ["Command and Control"], "nist": ["PR.AC"]} -investigative_searches = ["ESCU - AWS Network ACL Details from ID", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio"] +investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Process Info", "ESCU - Get DNS traffic ratio"] support_searches = ["ESCU - Baseline of blocked outbound traffic from AWS"] data_models = [] providing_technologies = none @@ -929,7 +961,7 @@ 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", "T1059", "T1064"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = ["ESCU - Baseline of Command Line Length - MLTK", "ESCU - Previously seen command line arguments"] data_models = ["Endpoint"] providing_technologies = none @@ -945,7 +977,7 @@ 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": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = ["ESCU - Baseline of DNS Query Length - MLTK"] data_models = ["Network_Resolution"] providing_technologies = none @@ -961,7 +993,7 @@ 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"], "nist": ["DE.AE", "PR.IP"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Email Info"] +investigative_searches = ["ESCU - Get Emails From Specific Sender", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Email Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] support_searches = ["ESCU - DNSTwist Domain Names"] data_models = ["Email", "UEBA"] providing_technologies = none @@ -981,7 +1013,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1059", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = ["ESCU - Baseline of Command Line Length - MLTK", "ESCU - Previously seen command line arguments"] data_models = ["Endpoint"] providing_technologies = none @@ -999,7 +1031,7 @@ 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 Credentails 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"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate Okta Activity by app", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate User Activities In Okta"] +investigative_searches = ["ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by app"] support_searches = [] data_models = [] providing_technologies = none @@ -1017,7 +1049,7 @@ 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", "T1084"], "nist": ["PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1035,7 +1067,7 @@ 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": ["T1015", "T1042", "T1103", "T1112", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1053,7 +1085,7 @@ 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"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId"] support_searches = ["ESCU - Previously Seen EC2 Modifications By User"] data_models = [] providing_technologies = none @@ -1070,7 +1102,7 @@ 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": ["T1015", "T1036", "T1085"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = ["ESCU - Baseline of Command Line Length - MLTK"] data_models = ["Endpoint"] providing_technologies = none @@ -1088,7 +1120,7 @@ version = 1 reference = ["https://www.monkey.org/~dugsong/dsniff/"] detection_searches = ["ESCU - Protocols passing authentication in cleartext - Rule"] mappings = {"cis20": ["CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] support_searches = [] data_models = ["Network_Traffic"] providing_technologies = none @@ -1104,7 +1136,7 @@ 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 Web Session Information via session id", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender"] +investigative_searches = ["ESCU - Get Emails From Specific Sender", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Web Session Information via session id"] support_searches = [] data_models = [] providing_technologies = none @@ -1125,7 +1157,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Defense_Evasion"] detection_searches = ["ESCU - Disabling Remote User Account Control - 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"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1089", "T1112"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1141,7 +1173,7 @@ 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": ["T1042"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1161,7 +1193,7 @@ 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"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1178,7 +1210,7 @@ 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 - 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"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1053", "T1089", "T1103", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1194,7 +1226,7 @@ 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 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1015", "T1068"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1210,7 +1242,7 @@ 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 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = ["ESCU - Previously Seen Running Windows Services"] data_models = ["Endpoint"] providing_technologies = none diff --git a/package/default/data/ui/panels/workbench_panel_investigate_pass_the_ticket_attempts.xml b/package/default/data/ui/panels/workbench_panel_investigate_pass_the_ticket_attempts.xml index 02d2dff20d..3f5dff58ab 100644 --- a/package/default/data/ui/panels/workbench_panel_investigate_pass_the_ticket_attempts.xml +++ b/package/default/data/ui/panels/workbench_panel_investigate_pass_the_ticket_attempts.xml @@ -1,7 +1,7 @@ - `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 | where sum_count/max_count!=2 | rename new_user AS user + `wineventlog_security` EventCode=4768 OR EventCode=4769 | stats count BY user, dest, EventCode | stats max(count) AS max_count sum(count) AS sum_count BY user, dest | where sum_count/max_count!=2 diff --git a/package/default/macros.conf b/package/default/macros.conf index ec0c5df81e..ab9cb7acb0 100644 --- a/package/default/macros.conf +++ b/package/default/macros.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-14T08:00:44 UTC +# On Date: 2020-06-03T20:09:14 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -106,6 +106,42 @@ description = customer specific splunk configurations(eg- index, source, sourcet definition = lookup update=true is_windows_system_file filename as process_name OUTPUT systemFile | search systemFile=true description = This macro limits the output to process names that are in the Windows System directory +[kubernetes_azure] +definition = sourcetype=mscs:storage:blob:json +description = customer specific splunk configurations(eg- index, source, sourcetype) for Kubernetes data from Azure. Replace the macro definition with configurations for your Splunk Environmnent. + +[kubernetes_azure_detect_most_active_service_accounts_by_pod_namespace_filter] +definition = search * +description = Use this macro to add additional filters + +[kubernetes_azure_detect_rbac_authorization_by_account_filter] +definition = search * +description = Use this macro to add additional filters + +[kubernetes_azure_detect_sensitive_object_access_filter] +definition = search * +description = Use this macro to add additional filters + +[kubernetes_azure_detect_sensitive_role_access_filter] +definition = search * +description = Use this macro to add additional filters + +[kubernetes_azure_detect_service_accounts_forbidden_failure_access_filter] +definition = search * +description = Use this macro to add additional filters + +[kubernetes_azure_detect_suspicious_kubectl_calls_filter] +definition = search * +description = Use this macro to add additional filters + +[kubernetes_azure_pod_scan_fingerprint_detection_filter] +definition = search * +description = Use this macro to add additional filters + +[kubernetes_azure_scan_fingerprint_filter] +definition = search * +description = Use this macro to add additional filters + [netbackup] definition = sourcetype="netbackup_logs" description = customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. @@ -619,6 +655,38 @@ 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. +[kubernetes_azure_detect_rbac_authorization_by_account_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[kubernetes_azure_detect_most_active_service_accounts_by_pod_namespace_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[kubernetes_azure_detect_sensitive_object_access_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[kubernetes_azure_detect_sensitive_role_access_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[kubernetes_azure_detect_service_accounts_forbidden_failure_access_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[kubernetes_azure_detect_suspicious_kubectl_calls_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[kubernetes_azure_pod_scan_fingerprint_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[kubernetes_azure_scan_fingerprint_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + [large_volume_of_dns_any_queries_filter] definition = search * description = Update this macro to limit the output results to filter out false positives. diff --git a/package/default/savedsearches.conf b/package/default/savedsearches.conf index 84401dfc9c..dca4c2534a 100644 --- a/package/default/savedsearches.conf +++ b/package/default/savedsearches.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-14T08:00:44 UTC +# On Date: 2020-06-03T20:09:14 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -645,7 +645,7 @@ 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 from datamodel=Endpoint.Registry where Registry.registry_path=*Software\\Microsoft\\Powershell\\1\\ShellIds\\Microsoft.PowerShell* Registry.registry_key_name=ExecutionPolicy (Registry.registry_value_name=Unrestricted OR Registry.registry_value_name=Bypass) 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)` | `attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass_filter` +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Registry where Registry.registry_path=*Software\\Microsoft\\Powershell\\1\\ShellIds\\Microsoft.PowerShell* Registry.registry_key_name=ExecutionPolicy (Registry.registry_value_name=Unrestricted OR Registry.registry_value_name=Bypass) 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)` | `attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass_filter` [ESCU - Attempt To Stop Security Service - Rule] action.escu = 0 @@ -1872,7 +1872,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = `sysmon` EventCode=10 TargetImage=*lsass.exe (GrantedAccess=0x1010 OR GrantedAccess=0x1410) | stats count min(_time) as firstTime max(_time) as lastTime by Computer, SourceImage, SourceProcessId, TargetImage, TargetProcessId, EventCode, GrantedAccess | rename Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `detect_credential_dumping_through_LSAS`detect_credential_dumping_through_lsass_access_filter` +search = `sysmon` EventCode=10 TargetImage=*lsass.exe (GrantedAccess=0x1010 OR GrantedAccess=0x1410) | stats count min(_time) as firstTime max(_time) as lastTime by Computer, SourceImage, SourceProcessId, TargetImage, TargetProcessId, EventCode, GrantedAccess | rename Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `detect_credential_dumping_through_lsass_access_filter` [ESCU - Detect DNS requests to Phishing Sites leveraging EvilGinx2 - Rule] action.escu = 0 @@ -4168,6 +4168,318 @@ realtime_schedule = 0 is_visible = false search = | from datamodel Identity_Management.All_Identities | eval empStatus=case((now()-startDate)<604800, "Accounts created in last week") | search empStatus="Accounts created in last week"| `security_content_ctime(endDate)` | `security_content_ctime(startDate)`| table identity empStatus endDate startDate | `identify_new_user_accounts_filter` +[ESCU - Kubernetes Azure detect RBAC authorization by account - Rule] +action.escu = 0 +action.escu.enabled = 1 +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.escu.mappings = {"kill_chain_phases": ["Lateral Movement"]} +action.escu.data_models = [] +action.escu.eli5 = 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.escu.how_to_implement = You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics +action.escu.known_false_positives = Not all RBAC Authorications are malicious. RBAC authorizations can uncover malicious activity specially if sensitive Roles have been granted. +action.escu.creation_date = 2020-05-26 +action.escu.modification_date = 2020-05-26 +action.escu.confidence = high +action.escu.full_search_name = ESCU - Kubernetes Azure detect RBAC authorization by account - Rule +action.escu.search_type = detection +action.escu.providing_technologies = [] +action.escu.analytic_story = ["Kubernetes Sensitive Role Activity"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now +action.correlationsearch.enabled = 1 +action.correlationsearch.label = ESCU - Kubernetes Azure detect RBAC authorization by account - Rule +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 +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +disabled = true +enableSched = 1 +counttype = number of events +relation = greater than +quantity = 0 +realtime_schedule = 0 +is_visible = false +search = sourcetype:mscs:storage:blob:json category=kube-audit | spath input=properties.log | search annotations.authorization.k8s.io/reason=* | table sourceIPs{} user.username userAgent annotations.authorization.k8s.io/reason |stats count by user.username annotations.authorization.k8s.io/reason | rare user.username annotations.authorization.k8s.io/reason |`kubernetes_azure_detect_rbac_authorization_by_account_filter` + +[ESCU - Kubernetes Azure detect most active service accounts by pod namespace - Rule] +action.escu = 0 +action.escu.enabled = 1 +description = This search provides information on Kubernetes service accounts,accessing pods and namespaces by IP address and verb +action.escu.mappings = {"kill_chain_phases": ["Lateral Movement"]} +action.escu.data_models = [] +action.escu.eli5 = This search provides information on Kubernetes service accounts,accessing pods and namespaces by IP address and verb +action.escu.how_to_implement = You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics +action.escu.known_false_positives = Not all service accounts interactions are malicious. Analyst must consider IP and verb context when trying to detect maliciousness. +action.escu.creation_date = 2020-05-26 +action.escu.modification_date = 2020-05-26 +action.escu.confidence = high +action.escu.full_search_name = ESCU - Kubernetes Azure detect most active service accounts by pod namespace - Rule +action.escu.search_type = detection +action.escu.providing_technologies = [] +action.escu.analytic_story = ["Kubernetes Sensitive Role Activity"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now +action.correlationsearch.enabled = 1 +action.correlationsearch.label = ESCU - Kubernetes Azure detect most active service accounts by pod namespace - Rule +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 +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +disabled = true +enableSched = 1 +counttype = number of events +relation = greater than +quantity = 0 +realtime_schedule = 0 +is_visible = false +search = sourcetype:mscs:storage:blob:json category=kube-audit | spath input=properties.log | search user.groups{}=system:serviceaccounts* | table sourceIPs{} user.username userAgent verb responseStatus.reason responseStatus.status properties.pod objectRef.namespace | top sourceIPs{} user.username verb responseStatus.status properties.pod objectRef.namespace |`kubernetes_azure_detect_most_active_service_accounts_by_pod_namespace_filter` + +[ESCU - Kubernetes Azure detect sensitive object access - Rule] +action.escu = 0 +action.escu.enabled = 1 +description = This search provides information on Kubernetes accounts accessing sensitve objects such as configmpas or secrets +action.escu.mappings = {"kill_chain_phases": ["Lateral Movement"]} +action.escu.data_models = [] +action.escu.eli5 = This search provides information on Kubernetes accounts accessing sensitve objects such as configmpas or secrets +action.escu.how_to_implement = You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics +action.escu.known_false_positives = Sensitive object access is not necessarily malicious but user and object context can provide guidance for detection. +action.escu.creation_date = 2020-05-20 +action.escu.modification_date = 2020-05-20 +action.escu.confidence = high +action.escu.full_search_name = ESCU - Kubernetes Azure detect sensitive object access - Rule +action.escu.search_type = detection +action.escu.providing_technologies = [] +action.escu.analytic_story = ["Kubernetes Sensitive Object Access Activity"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now +action.correlationsearch.enabled = 1 +action.correlationsearch.label = ESCU - Kubernetes Azure detect sensitive object access - Rule +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 +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +disabled = true +enableSched = 1 +counttype = number of events +relation = greater than +quantity = 0 +realtime_schedule = 0 +is_visible = false +search = `kubernetes_azure` category=kube-audit | spath input=properties.log| search objectRef.resource=secrets OR configmaps |table user.username user.groups{} objectRef.resource objectRef.namespace objectRef.name annotations.authorization.k8s.io/reason |dedup user.username user.groups{} |`kubernetes_azure_detect_sensitive_object_access_filter` + +[ESCU - Kubernetes Azure detect sensitive role access - Rule] +action.escu = 0 +action.escu.enabled = 1 +description = This search provides information on Kubernetes accounts accessing sensitve objects such as configmpas or secrets +action.escu.mappings = {"kill_chain_phases": ["Lateral Movement"]} +action.escu.data_models = [] +action.escu.eli5 = This search provides information on Kubernetes accounts accessing sensitve objects such as configmpas or secrets +action.escu.how_to_implement = You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics +action.escu.known_false_positives = Sensitive role resource access is necessary for cluster operation, however source IP, namespace and user group may indicate possible malicious use. +action.escu.creation_date = 2020-05-20 +action.escu.modification_date = 2020-05-20 +action.escu.confidence = high +action.escu.full_search_name = ESCU - Kubernetes Azure detect sensitive role access - Rule +action.escu.search_type = detection +action.escu.providing_technologies = [] +action.escu.analytic_story = ["Kubernetes Sensitive Role Activity"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now +action.correlationsearch.enabled = 1 +action.correlationsearch.label = ESCU - Kubernetes Azure detect sensitive role access - Rule +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 +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +disabled = true +enableSched = 1 +counttype = number of events +relation = greater than +quantity = 0 +realtime_schedule = 0 +is_visible = false +search = `kubernetes_azure` category=kube-audit | spath input=properties.log| search objectRef.resource=clusterroles OR clusterrolebindings | table sourceIPs{} user.username user.groups{} objectRef.namespace requestURI annotations.authorization.k8s.io/reason | dedup user.username user.groups{} |`kubernetes_azure_detect_sensitive_role_access_filter` + +[ESCU - Kubernetes Azure detect service accounts forbidden failure access - Rule] +action.escu = 0 +action.escu.enabled = 1 +description = This search provides information on Kubernetes service accounts with failure or forbidden access status +action.escu.mappings = {"kill_chain_phases": ["Lateral Movement"]} +action.escu.data_models = [] +action.escu.eli5 = This search provides information on Kubernetes service accounts with failure or forbidden access status +action.escu.how_to_implement = You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics +action.escu.known_false_positives = This search can give false positives as there might be inherent issues with authentications and permissions at cluster. +action.escu.creation_date = 2020-05-20 +action.escu.modification_date = 2020-05-20 +action.escu.confidence = high +action.escu.full_search_name = ESCU - Kubernetes Azure detect service accounts forbidden failure access - Rule +action.escu.search_type = detection +action.escu.providing_technologies = [] +action.escu.analytic_story = ["Kubernetes Sensitive Object Access Activity"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now +action.correlationsearch.enabled = 1 +action.correlationsearch.label = ESCU - Kubernetes Azure detect service accounts forbidden failure access - Rule +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 +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +disabled = true +enableSched = 1 +counttype = number of events +relation = greater than +quantity = 0 +realtime_schedule = 0 +is_visible = false +search = `kubernetes_azure` category=kube-audit | spath input=properties.log | search user.groups{}=system:serviceaccounts* responseStatus.reason=Forbidden | table sourceIPs{} user.username userAgent verb responseStatus.reason responseStatus.status properties.pod objectRef.namespace |`kubernetes_azure_detect_service_accounts_forbidden_failure_access_filter` + +[ESCU - Kubernetes Azure detect suspicious kubectl calls - Rule] +action.escu = 0 +action.escu.enabled = 1 +description = This search provides information on Kubectl calls with IP, verb namespace and object access context +action.escu.mappings = {"kill_chain_phases": ["Lateral Movement"]} +action.escu.data_models = [] +action.escu.eli5 = This search provides information on Kubectl calls with IP, verb namespace and object access context +action.escu.how_to_implement = You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics +action.escu.known_false_positives = Kubectl calls are not malicious by nature. However source IP, verb and Object can reveal potential malicious activity, specially suspicious IPs and sensitive objects such as configmaps or secrets +action.escu.creation_date = 2020-05-26 +action.escu.modification_date = 2020-05-26 +action.escu.confidence = high +action.escu.full_search_name = ESCU - Kubernetes Azure detect suspicious kubectl calls - Rule +action.escu.search_type = detection +action.escu.providing_technologies = [] +action.escu.analytic_story = ["Kubernetes Sensitive Object Access Activity"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now +action.correlationsearch.enabled = 1 +action.correlationsearch.label = ESCU - Kubernetes Azure detect suspicious kubectl calls - Rule +schedule_window = auto +action.notable = 1 +action.notable.param.rule_description = This search provides information on 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 +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +disabled = true +enableSched = 1 +counttype = number of events +relation = greater than +quantity = 0 +realtime_schedule = 0 +is_visible = false +search = `kubernetes_azure` category=kube-audit | spath input=properties.log| search objectRef.resource=secrets OR configmaps |table user.username user.groups{} objectRef.resource objectRef.namespace objectRef.name annotations.authorization.k8s.io/reason |dedup user.username user.groups{} |`kubernetes_azure_detect_suspicious_kubectl_calls_filter` + +[ESCU - Kubernetes Azure pod scan fingerprint - Rule] +action.escu = 0 +action.escu.enabled = 1 +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.escu.mappings = {"kill_chain_phases": ["Reconnaissance"]} +action.escu.data_models = [] +action.escu.eli5 = 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.escu.how_to_implement = You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics +action.escu.known_false_positives = Not all unauthenticated requests are malicious, but source IPs, userAgent, verb, request URI and response status will provide context. +action.escu.creation_date = 2020-05-20 +action.escu.modification_date = 2020-05-20 +action.escu.confidence = high +action.escu.full_search_name = ESCU - Kubernetes Azure pod scan fingerprint - Rule +action.escu.search_type = detection +action.escu.providing_technologies = [] +action.escu.analytic_story = ["Kubernetes Scanning Activity"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now +action.correlationsearch.enabled = 1 +action.correlationsearch.label = ESCU - Kubernetes Azure pod scan fingerprint - Rule +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 +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +disabled = true +enableSched = 1 +counttype = number of events +relation = greater than +quantity = 0 +realtime_schedule = 0 +is_visible = false +search = `kubernetes_azure` category=kube-audit | spath input=properties.log | search responseStatus.code=401 | table sourceIPs{} userAgent verb requestURI responseStatus.reason properties.pod |`kubernetes_azure_pod_scan_fingerprint_filter` + +[ESCU - Kubernetes Azure scan fingerprint - Rule] +action.escu = 0 +action.escu.enabled = 1 +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.escu.mappings = {"kill_chain_phases": ["Reconnaissance"]} +action.escu.data_models = [] +action.escu.eli5 = This search provides information of unauthenticated requests via source IP user agent, request URI and response status data against Kubernetes cluster in Azure +action.escu.how_to_implement = You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics +action.escu.known_false_positives = Not all unauthenticated requests are malicious, but source IPs, userAgent, verb, request URI and response status will provide context. +action.escu.creation_date = 2020-05-19 +action.escu.modification_date = 2020-05-19 +action.escu.confidence = high +action.escu.full_search_name = ESCU - Kubernetes Azure scan fingerprint - Rule +action.escu.search_type = detection +action.escu.providing_technologies = [] +action.escu.analytic_story = ["Kubernetes Scanning Activity"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now +action.correlationsearch.enabled = 1 +action.correlationsearch.label = ESCU - Kubernetes Azure scan fingerprint - Rule +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 +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +disabled = true +enableSched = 1 +counttype = number of events +relation = greater than +quantity = 0 +realtime_schedule = 0 +is_visible = false +search = `kubernetes_azure` category=kube-audit | spath input=properties.log | search responseStatus.code=401 | table sourceIPs{} userAgent verb requestURI responseStatus.reason |`kubernetes_azure_scan_fingerprint_filter` + [ESCU - Large Volume of DNS ANY Queries - Rule] action.escu = 0 action.escu.enabled = 1 @@ -9536,7 +9848,7 @@ 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 | where sum_count/max_count!=2 | rename new_user AS user +search = `wineventlog_security` EventCode=4768 OR EventCode=4769 | stats count BY user, dest, EventCode | stats max(count) AS max_count sum(count) AS sum_count BY user, dest | where sum_count/max_count!=2 [ESCU - Investigate Previous Unseen User - Response Task] action.escu = 0 diff --git a/package/default/transforms.conf b/package/default/transforms.conf index 9d23f65600..f810386136 100644 --- a/package/default/transforms.conf +++ b/package/default/transforms.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-14T08:00:44 UTC +# On Date: 2020-06-03T20:09:14 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/use_case_library.conf b/package/default/use_case_library.conf index 3880ef279b..9a6b59f309 100644 --- a/package/default/use_case_library.conf +++ b/package/default/use_case_library.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-14T08:00:44 UTC +# On Date: 2020-06-03T20:09:14 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 = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - AWS Investigate User Activities By Source User"] +searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By Source User"] 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 = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details"] +searches = ["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", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] 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 = 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 = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio"] +searches = ["ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Process Info", "ESCU - Get DNS traffic ratio"] 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. @@ -52,7 +52,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Country"] +searches = ["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 City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From City"] 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 whitelist specific IPs (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. @@ -64,7 +64,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect API activity from users without MFA - 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", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Investigate AWS User Activities by user field"] 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. \ @@ -78,7 +78,7 @@ version = 1 references = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Identify New User Accounts - Rule", "ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Short Lived Windows Accounts - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Logon Rights Modifications For User"] +searches = ["ESCU - Identify New User Accounts - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Short Lived Windows Accounts - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. narrative = Monitoring user accounts within your enterprise is a critical analytic function that helps ensure that credential and access policies/procedures are properly implemented and are being enforced. Proactive ad-hoc hunting, as well as routine monitoring, can ensure user or system accounts are not being abused by unauthorized individuals or processes. In the event of a network event or breach, user-authentication logs are a key resource in determining if or how an account might have been compromised or co-opted, leading to suspicious or malicious activity. @@ -89,7 +89,7 @@ version = 1 references = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Suspicious Java Classes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web POSTs From src", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info"] +searches = ["ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Suspicious Java Classes - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web POSTs From src", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] 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.\ @@ -113,7 +113,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule", "ESCU - Get Notable Info", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable History"] 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. @@ -124,7 +124,7 @@ 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 = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Email Info"] +searches = ["ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Get Emails From Specific Sender", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Email Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] 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.\ @@ -137,7 +137,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get Notable Info", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details"] +searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] 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. \ @@ -151,7 +151,7 @@ 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 = "Jose Hernandez, Splunk" spec_version = 3 -searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From src ip"] +searches = ["ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] 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.\ @@ -164,7 +164,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] 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. \ @@ -177,7 +177,7 @@ 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 = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Excessive DNS Failures - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info"] +searches = ["ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Parent Process Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Process Info", "ESCU - Get DNS traffic ratio"] 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. @@ -201,7 +201,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - New container uploaded to AWS ECR - Rule", "ESCU - GCP GCR container uploaded - Rule", "ESCU - Investigate AWS ECR container listing activity"] +searches = ["ESCU - GCP GCR container uploaded - Rule", "ESCU - New container uploaded to AWS ECR - Rule", "ESCU - Investigate AWS ECR container listing activity"] 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. @@ -212,7 +212,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Creation of Shadow Copy - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Pass the Ticket Attempts"] +searches = ["ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Pass the Ticket Attempts"] 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.\ @@ -225,7 +225,7 @@ version = 2 references = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - Get Process Registry Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process File Activity"] +searches = ["ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process File Activity", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Process Registry Activity"] 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. \ @@ -239,7 +239,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History"] 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. @@ -251,7 +251,7 @@ 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 = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - DNS record changed - Rule", "ESCU - Get DNS Server History for a host"] +searches = ["ESCU - DNS record changed - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get DNS Server History for a host"] 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. \ @@ -270,7 +270,7 @@ 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 = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio"] +searches = ["ESCU - Detect USB device insertion - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] 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. @@ -281,7 +281,7 @@ 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 = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Attempt To Stop Security Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] 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 blacklist (which would prevent them from running). @@ -292,7 +292,7 @@ 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 = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Investigate Web Activity From src ip"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Investigate Web Activity From src ip", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] 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 blacklists. 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 blacklists 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. @@ -303,7 +303,7 @@ 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 = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Registry Keys Used For Persistence - 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 - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] 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.\ @@ -316,7 +316,7 @@ 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 = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] 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.\ @@ -330,7 +330,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Windows hosts file modification - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host"] +searches = ["ESCU - Windows hosts file modification - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] 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. @@ -341,7 +341,7 @@ version = 1 references = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint"] +searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History"] 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.\ @@ -366,18 +366,40 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Splunk" spec_version = 3 -searches = ["ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable Info"] +searches = ["ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - Kubernetes Azure scan fingerprint - Rule", "ESCU - Kubernetes Azure pod scan fingerprint - Rule", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable Info", "ESCU - Get Notable History"] 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. +[analytic_story://Kubernetes Sensitive Object Access Activity] +category = Cloud Security +last_updated = 2020-05-20 +version = 1 +references = ["https://www.splunk.com/en_us/blog/security/approaching-kubernetes-security-detecting-kubernetes-scan-with-splunk.html"] +maintainers = "Rod Soto, Splunk" +spec_version = 3 +searches = ["ESCU - Kubernetes Azure detect suspicious kubectl calls - Rule", "ESCU - Kubernetes Azure detect sensitive object access - Rule", "ESCU - Kubernetes Azure detect service accounts forbidden failure access - Rule"] +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. + +[analytic_story://Kubernetes Sensitive Object Access Activity] +category = Cloud Security +last_updated = 2020-05-20 +version = 1 +references = ["https://www.splunk.com/en_us/blog/security/approaching-kubernetes-security-detecting-kubernetes-scan-with-splunk.html"] +maintainers = "Rod Soto, Splunk" +spec_version = 3 +searches = ["ESCU - Kubernetes Azure detect suspicious kubectl calls - Rule", "ESCU - Kubernetes Azure detect sensitive object access - Rule", "ESCU - Kubernetes Azure detect service accounts forbidden failure access - Rule"] +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 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. + [analytic_story://Lateral Movement] category = Adversary Tactics last_updated = 2020-02-04 version = 2 -references = ["https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis", "https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] +references = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] 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.\ @@ -392,7 +414,7 @@ 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 = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - 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 - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +searches = ["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", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] 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: \ @@ -412,7 +434,7 @@ version = 1 references = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - All backup logs for host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - All backup logs for host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History"] 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. @@ -423,7 +445,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] 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. @@ -435,7 +457,7 @@ version = 1 references = ["https://learn.cisecurity.org/20-controls-download"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - No Windows Updates in a time frame - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - No Windows Updates in a time frame - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History"] description = Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches. 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.\ @@ -448,7 +470,7 @@ version = 1 references = ["https://technet.microsoft.com/library/bb490939.aspx", "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 = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Processes launching netsh - Rule", "ESCU - Processes created by netsh - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] 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`. @@ -460,7 +482,7 @@ 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 = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - First time seen command line argument - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +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 - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] 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.\ @@ -475,7 +497,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2019/04/spear-phishing-campaign-targets-ukraine-government.html"] maintainers = "Splunk Research Team, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious LNK file launching a process - Rule", "ESCU - Detect Oulook exe writing a zip file - Rule", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Detect Oulook exe writing a zip file - Rule", "ESCU - Suspicious LNK file launching a process - Rule", "ESCU - Get Parent Process Info"] description = Detect signs of malicious payloads that may indicate that your environment has been breached via a phishing attack. narrative = Despite its simplicity, phishing remains the most pervasive and dangerous cyberthreat. In fact, research shows that as many as [91% of all successful attacks](https://digitalguardian.com/blog/91-percent-cyber-attacks-start-phishing-email-heres-how-protect-against-phishing) are initiated via a phishing email. \ 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. Worse, because its success relies on the gullibility of humans, it's impossible to completely "automate" it out of your environment. However, you can use ES and ESCU to detect and investigate potentially malicious payloads injected into your environment subsequent to a phishing attack. \ @@ -493,7 +515,7 @@ 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 = "iDefense Cyber Espionage Team, iDefense" spec_version = 3 -searches = ["ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] 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.\ @@ -531,7 +553,7 @@ version = 1 references = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - TOR Traffic - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] 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. @@ -542,7 +564,7 @@ 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 = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Common Ransomware Notes - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] 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. @@ -553,7 +575,7 @@ 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 = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info"] +searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] 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. @@ -565,7 +587,7 @@ version = 1 references = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] 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. @@ -577,7 +599,7 @@ 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 = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - File with Samsam Extension - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Common Ransomware Notes - Rule", "ESCU - Batch File Write to System32 - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] 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.\ @@ -593,7 +615,7 @@ version = 1 references = ["https://meltdownattack.com/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info"] +searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] 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. @@ -604,7 +626,7 @@ version = 1 references = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Open Redirect in Splunk Web - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Open Redirect in Splunk Web - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History"] description = Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains. narrative = This Analytic Story is associated with CVE-2016-4859, an open-redirect vulnerability in the following versions of Splunk Enterprise:\ \ @@ -624,7 +646,7 @@ 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 = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From src ip"] +searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable History"] 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.\ @@ -638,7 +660,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "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 - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details"] +searches = ["ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] 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. @@ -649,7 +671,7 @@ version = 1 references = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect new user AWS Console Login - 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 - AWS Investigate User Activities By ARN"] +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"] 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. @@ -660,7 +682,7 @@ 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 = "Bhavin Patel, Splunk" 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 - Get Notable History", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Investigate AWS activities via region name"] +searches = ["ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get All AWS Activity From IP Address", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] 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.\ @@ -673,7 +695,7 @@ version = 1 references = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio"] +searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Process Info", "ESCU - Get DNS traffic ratio"] 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.\ @@ -687,7 +709,7 @@ 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 = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] 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. @@ -698,7 +720,7 @@ 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 = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Excessive DNS Failures - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Detection of DNS Tunnels - 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 - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info"] +searches = ["ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] 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. @@ -709,7 +731,7 @@ version = 1 references = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Email Info"] +searches = ["ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Get Emails From Specific Sender", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Email Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] 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: \ @@ -724,7 +746,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] 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 white-listing solutions via the mshta.exe process, which executes Microsoft HTML applications with the .hta suffix. In these cases, attackers use the trusted Windows utility to eproxy execution of malicious files, whether an .hta application, javascript, or VBScript.\ One example of a notable mshta.exe attack was the Kovter malware (https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5) that was implicated in ransomware and click-fraud attacks. Kovter utilized .hta to execute a series of javascript commands, each progressively more dangerous. According to the Mitre Parternship Network (https://attack.mitre.org/wiki/Technique/T1170), FIN7 has leveraged mshta.exe, as has the MuddyWater group, who used it to execute its POWERSTATS payload (which then used the utility to execute additional payloads).\ @@ -737,7 +759,7 @@ 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 = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate User Activities In Okta"] +searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by app"] 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. \ @@ -750,7 +772,7 @@ 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 = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Process Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - WMI Temporary Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Parent Process Info"] +searches = ["ESCU - WMI Temporary Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Process Execution via WMI - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] 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.\ @@ -763,7 +785,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Monitor Registry Keys for Print Monitors - 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 - Suspicious Changes to File Associations - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] 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.\ @@ -776,7 +798,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN"] +searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId"] 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. @@ -788,7 +810,7 @@ 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 = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] 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.\ @@ -801,7 +823,7 @@ version = 1 references = ["https://www.monkey.org/~dugsong/dsniff/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info"] +searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] 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. @@ -812,7 +834,7 @@ 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 = "Jim Apger, Splunk" spec_version = 3 -searches = ["ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Get Web Session Information via session id", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender"] +searches = ["ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Web Session Information via session id"] 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.\ @@ -828,7 +850,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Defense_Evasion"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] 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. @@ -839,7 +861,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] maintainers = "Rico Valdez, Splunk" 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 Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] 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. \ @@ -854,7 +876,7 @@ 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 = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Deleting Shadow Copies - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] 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). @@ -866,7 +888,7 @@ 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 = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Shim Database File Creation - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] 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. @@ -877,7 +899,7 @@ version = 2 references = ["https://attack.mitre.org/tactics/TA0004/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] 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. @@ -888,7 +910,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] maintainers = "Rico Valdez, Splunk" 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 Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] 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. @@ -1988,6 +2010,86 @@ annotations = {"cis20": ["CIS 16"], "mitre_attack": ["T1136"], "nist": ["PR.IP"] known_false_positives = If the Identity_Management data model is not updated regularly, this search could give you false positive alerts. Please consider this and investigate appropriately. providing_technologies = none +[savedsearch://ESCU - Kubernetes Azure detect RBAC authorization by account - Rule] +type = detection +asset_type = +confidence = medium +explanation = 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 +how_to_implement = You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics +annotations = {"kill_chain_phases": ["Lateral Movement"]} +known_false_positives = Not all RBAC Authorications are malicious. RBAC authorizations can uncover malicious activity specially if sensitive Roles have been granted. +providing_technologies = none + +[savedsearch://ESCU - Kubernetes Azure detect most active service accounts by pod namespace - Rule] +type = detection +asset_type = +confidence = medium +explanation = This search provides information on Kubernetes service accounts,accessing pods and namespaces by IP address and verb +how_to_implement = You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics +annotations = {"kill_chain_phases": ["Lateral Movement"]} +known_false_positives = Not all service accounts interactions are malicious. Analyst must consider IP and verb context when trying to detect maliciousness. +providing_technologies = none + +[savedsearch://ESCU - Kubernetes Azure detect sensitive object access - Rule] +type = detection +asset_type = +confidence = medium +explanation = This search provides information on Kubernetes accounts accessing sensitve objects such as configmpas or secrets +how_to_implement = You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics +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 = none + +[savedsearch://ESCU - Kubernetes Azure detect sensitive role access - Rule] +type = detection +asset_type = +confidence = medium +explanation = This search provides information on Kubernetes accounts accessing sensitve objects such as configmpas or secrets +how_to_implement = You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics +annotations = {"kill_chain_phases": ["Lateral Movement"]} +known_false_positives = Sensitive role resource access is necessary for cluster operation, however source IP, namespace and user group may indicate possible malicious use. +providing_technologies = none + +[savedsearch://ESCU - Kubernetes Azure detect service accounts forbidden failure access - Rule] +type = detection +asset_type = +confidence = medium +explanation = This search provides information on Kubernetes service accounts with failure or forbidden access status +how_to_implement = You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics +annotations = {"kill_chain_phases": ["Lateral Movement"]} +known_false_positives = This search can give false positives as there might be inherent issues with authentications and permissions at cluster. +providing_technologies = none + +[savedsearch://ESCU - Kubernetes Azure detect suspicious kubectl calls - Rule] +type = detection +asset_type = +confidence = medium +explanation = This search provides information on Kubectl calls with IP, verb namespace and object access context +how_to_implement = You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics +annotations = {"kill_chain_phases": ["Lateral Movement"]} +known_false_positives = Kubectl calls are not malicious by nature. However source IP, verb and Object can reveal potential malicious activity, specially suspicious IPs and sensitive objects such as configmaps or secrets +providing_technologies = none + +[savedsearch://ESCU - Kubernetes Azure pod scan fingerprint - Rule] +type = detection +asset_type = +confidence = medium +explanation = This search provides information of unauthenticated requests via source IP user agent, request URI and response status data against Kubernetes cluster pod in Azure +how_to_implement = You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics +annotations = {"kill_chain_phases": ["Reconnaissance"]} +known_false_positives = Not all unauthenticated requests are malicious, but source IPs, userAgent, verb, request URI and response status will provide context. +providing_technologies = none + +[savedsearch://ESCU - Kubernetes Azure scan fingerprint - Rule] +type = detection +asset_type = +confidence = medium +explanation = This search provides information of unauthenticated requests via source IP user agent, request URI and response status data against Kubernetes cluster in Azure +how_to_implement = You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics +annotations = {"kill_chain_phases": ["Reconnaissance"]} +known_false_positives = Not all unauthenticated requests are malicious, but source IPs, userAgent, verb, request URI and response status will provide context. +providing_technologies = none + [savedsearch://ESCU - Large Volume of DNS ANY Queries - Rule] type = detection asset_type = diff --git a/stories/kubernetes_sensitive_role_activity.yml b/stories/kubernetes_sensitive_role_activity.yml index 7d52e04e08..921b5d0bf7 100644 --- a/stories/kubernetes_sensitive_role_activity.yml +++ b/stories/kubernetes_sensitive_role_activity.yml @@ -1,13 +1,13 @@ author: "Rod Soto, Splunk" date: "2020-05-20" description: "This story addresses detection and response around Sensitive Role usage within a Kubernetes clusters against cluster resources and namespaces." -id: 2574e6d9-7254-4751-8925-0447deeec8ea +id: 2574e6d9-7254-4751-8925-0447deeec8ew name: "Kubernetes Sensitive Object Access Activity" 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." references: - https://www.splunk.com/en_us/blog/security/approaching-kubernetes-security-detecting-kubernetes-scan-with-splunk.html tags: - analytics_story: "Kubernetes Sensitive Object Access Activity" + analytics_story: "Kubernetes Sensitive Role Activity" category: - "Cloud Security" usecase: "Security Monitoring" From d7eae01713128167b17d05d5aadb1192645a4fb0 Mon Sep 17 00:00:00 2001 From: bpatel Date: Wed, 3 Jun 2020 13:28:25 -0700 Subject: [PATCH 13/14] add story to a single response task --- package/default/analytic_stories.conf | 156 +++++++++--------- package/default/es_investigations.conf | 130 ++++++++------- package/default/macros.conf | 2 +- package/default/savedsearches.conf | 4 +- package/default/transforms.conf | 2 +- package/default/use_case_library.conf | 136 +++++++-------- response_tasks/get_notable_info.yml | 2 + .../kubernetes_sensitive_role_activity.yml | 4 +- 8 files changed, 225 insertions(+), 211 deletions(-) diff --git a/package/default/analytic_stories.conf b/package/default/analytic_stories.conf index f35a4eccd3..06816275a9 100644 --- a/package/default/analytic_stories.conf +++ b/package/default/analytic_stories.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-06-03T20:09:14 UTC +# On Date: 2020-06-03T20:28:01 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 Cross Account Activity From Previously Unseen Account - Rule"] mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By Source User"] +investigative_searches = ["ESCU - AWS Investigate User Activities By Source User", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By AccessKeyId"] support_searches = ["ESCU - Previously Seen AWS Cross Account Activity"] data_models = [] providing_technologies = none @@ -34,8 +34,8 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["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"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] -support_searches = ["ESCU - Previously Seen EC2 Instance Types", "ESCU - Previously Seen EC2 Launches By User", "ESCU - Previously Seen EC2 AMIs", "ESCU - Previously Seen AWS Regions"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get EC2 Launch Details", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +support_searches = ["ESCU - Previously Seen AWS Regions", "ESCU - Previously Seen EC2 AMIs", "ESCU - Previously Seen EC2 Instance Types", "ESCU - Previously Seen EC2 Launches By User"] 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. @@ -53,7 +53,7 @@ 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"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC"]} -investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Process Info", "ESCU - Get DNS traffic ratio"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network ACL Details from ID", "ESCU - Get User Information from Identity Table"] support_searches = ["ESCU - Baseline of blocked outbound traffic from AWS", "ESCU - Baseline of Network ACL Activity by ARN"] data_models = [] providing_technologies = none @@ -69,7 +69,7 @@ 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"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From City"] +investigative_searches = ["ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Country"] support_searches = ["ESCU - Previously Seen AWS Provisioning Activity Sources"] data_models = [] providing_technologies = none @@ -86,8 +86,8 @@ 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"], "nist": ["DE.CM", "DE.DP", "ID.AM", "PR.AC"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Investigate AWS User Activities by user field"] -support_searches = ["ESCU - Baseline of Security Group Activity by ARN", "ESCU - Baseline of API Calls per User ARN", "ESCU - Create a list of approved AWS service accounts", "ESCU - Previously seen API call per user roles in CloudTrail"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable Info"] +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"] 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. @@ -105,7 +105,7 @@ version = 1 reference = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] detection_searches = ["ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Short Lived Windows Accounts - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078", "T1136"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Change"] providing_technologies = none @@ -121,7 +121,7 @@ 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"], "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 - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web POSTs From src", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Investigate Web POSTs From src", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Suspicious Strings in HTTP Header"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -150,7 +150,7 @@ 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"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address"] support_searches = ["ESCU - Count of assets by category"] data_models = ["Network_Sessions"] providing_technologies = none @@ -166,7 +166,7 @@ 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", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Email Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get User Information from Identity Table", "ESCU - Get Email Info"] support_searches = ["ESCU - DNSTwist Domain Names"] data_models = ["Email", "Network_Resolution", "Web"] providing_technologies = none @@ -184,8 +184,8 @@ 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 - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] -support_searches = ["ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK", "ESCU - Previously Seen Cloud Compute Instance Types", "ESCU - Previously Seen Cloud Compute Creations By User", "ESCU - Previously Seen Cloud Compute Images", "ESCU - Previously Seen Cloud Regions"] +investigative_searches = ["ESCU - Investigate Cloud Compute Instance Activities", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get EC2 Launch Details", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +support_searches = ["ESCU - Previously Seen Cloud Compute Creations By User", "ESCU - Previously Seen Cloud Compute Images", "ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK", "ESCU - Previously Seen Cloud Regions", "ESCU - Previously Seen Cloud Compute Instance Types"] data_models = ["Cloud_Infrastructure"] 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. @@ -203,7 +203,7 @@ 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"], "nist": ["DE.DP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable History", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = [] providing_technologies = none @@ -221,7 +221,7 @@ 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": ["T1043", "T1074", "T1114"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -239,8 +239,8 @@ 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": ["T1043", "T1048", "T1095"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Parent Process Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Process Info", "ESCU - Get DNS traffic ratio"] -support_searches = ["ESCU - Baseline of DNS Query Length - MLTK", "ESCU - Baseline of blocked outbound traffic from AWS"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network ACL Details from ID", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] +support_searches = ["ESCU - Baseline of blocked outbound traffic from AWS", "ESCU - Baseline of DNS Query Length - MLTK"] 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. @@ -289,7 +289,7 @@ 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 - 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 - 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", "T1064", "T1086"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Pass the Ticket Attempts"] +investigative_searches = ["ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Pass the Ticket Attempts"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -307,8 +307,8 @@ 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 Name Used by Dragonfly Threat Actors - 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": ["T1031", "T1043", "T1050", "T1053", "T1059", "T1064", "T1078", "T1086", "T1089", "T1103", "T1112", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.AT", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process File Activity", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Process Registry Activity"] -support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Previously seen command line arguments"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process File Activity", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Registry Activity", "ESCU - Get Parent Process Info"] +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. @@ -326,7 +326,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] detection_searches = ["ESCU - Large Volume of DNS ANY Queries - Rule"] mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -367,7 +367,7 @@ 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"], "mitre_attack": ["T1043"], "nist": ["DE.AE", "DE.CM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Change_Analysis", "Network_Resolution"] providing_technologies = none @@ -383,8 +383,8 @@ 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": ["T1031", "T1050", "T1059", "T1089", "T1112"], "nist": ["DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] -support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Previously seen command line arguments"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] +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. @@ -399,7 +399,7 @@ 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 13", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1041"], "nist": ["DE.CM", "DE.DP", "PR.IP"]} -investigative_searches = ["ESCU - Investigate Web Activity From src ip", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Network_Resolution", "Web"] providing_technologies = none @@ -415,8 +415,8 @@ 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": ["T1043", "T1059", "T1072", "T1087", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] -support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Add Prohibited Processes to Enterprise Security"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] +support_searches = ["ESCU - Add Prohibited Processes to Enterprise Security", "ESCU - Baseline of SMB Traffic - MLTK"] data_models = ["Email", "Endpoint", "Network_Traffic"] providing_technologies = none 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. @@ -433,8 +433,8 @@ 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": ["T1043", "T1059", "T1064", "T1076"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] -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 Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] +support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Previously seen command line arguments", "ESCU - Baseline of DNS Query Length - 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. @@ -452,7 +452,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -468,7 +468,7 @@ version = 1 reference = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] detection_searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery", "Reconnaissance"], "mitre_attack": ["T1082"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -498,7 +498,7 @@ 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 scan detection - Rule", "ESCU - Kubernetes Azure pod scan fingerprint - Rule", "ESCU - Kubernetes Azure scan fingerprint - Rule"] mappings = {"kill_chain_phases": ["Reconnaissance"]} -investigative_searches = ["ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Amazon EKS Kubernetes activity by src ip"] support_searches = [] data_models = [] providing_technologies = none @@ -514,28 +514,28 @@ version = 1 reference = ["https://www.splunk.com/en_us/blog/security/approaching-kubernetes-security-detecting-kubernetes-scan-with-splunk.html"] detection_searches = ["ESCU - Kubernetes Azure detect sensitive object access - Rule", "ESCU - Kubernetes Azure detect service accounts forbidden failure access - Rule", "ESCU - Kubernetes Azure detect suspicious kubectl calls - Rule"] mappings = {"kill_chain_phases": ["Lateral Movement"]} -investigative_searches = [] +investigative_searches = ["ESCU - Get Notable Info"] support_searches = [] 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. -[Kubernetes Sensitive Object Access Activity] +[Kubernetes Sensitive Role Activity] category = Cloud Security creation_date = 2020-05-20 modification_date = 2020-05-20 id = 2574e6d9-7254-4751-8925-0447deeec8ew version = 1 reference = ["https://www.splunk.com/en_us/blog/security/approaching-kubernetes-security-detecting-kubernetes-scan-with-splunk.html"] -detection_searches = ["ESCU - Kubernetes Azure detect sensitive object access - Rule", "ESCU - Kubernetes Azure detect service accounts forbidden failure access - Rule", "ESCU - Kubernetes Azure detect suspicious kubectl calls - Rule"] +detection_searches = ["ESCU - Kubernetes Azure detect RBAC authorization by account - Rule", "ESCU - Kubernetes Azure detect most active service accounts by pod namespace - Rule", "ESCU - Kubernetes Azure detect sensitive role access - Rule"] mappings = {"kill_chain_phases": ["Lateral Movement"]} -investigative_searches = [] +investigative_searches = ["ESCU - Get Notable Info"] support_searches = [] 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 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. +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 [Lateral Movement] category = Adversary Tactics @@ -546,7 +546,7 @@ 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 - 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 9"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053", "T1075", "T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -566,7 +566,7 @@ 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 - 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"], "mitre_attack": ["T1064", "T1086"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -591,7 +591,7 @@ version = 1 reference = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] 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 - All backup logs for host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - All backup logs for host", "ESCU - Get Risk Modifiers For User"] support_searches = ["ESCU - Monitor Unsuccessful Backups", "ESCU - Monitor Successful Backups"] data_models = [] providing_technologies = none @@ -607,7 +607,7 @@ 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"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Update Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] support_searches = ["ESCU - Add Prohibited Processes to Enterprise Security"] data_models = ["Endpoint"] providing_technologies = none @@ -624,7 +624,7 @@ version = 1 reference = ["https://learn.cisecurity.org/20-controls-download"] detection_searches = ["ESCU - No Windows Updates in a time frame - Rule"] mappings = {"cis20": ["CIS 18"], "nist": ["PR.MA"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Updates"] providing_technologies = none @@ -642,8 +642,8 @@ version = 1 reference = ["https://technet.microsoft.com/library/bb490939.aspx", "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": ["T1059", "T1089"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] -support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Previously seen command line arguments"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] +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. @@ -659,8 +659,8 @@ 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 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1064", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] -support_searches = ["ESCU - Previously seen command line arguments", "ESCU - Previously Seen Running Windows Services"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] +support_searches = ["ESCU - Previously Seen Running Windows Services", "ESCU - Previously seen command line arguments"] 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. @@ -702,7 +702,7 @@ 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", "T1064", "T1086", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] support_searches = ["ESCU - Baseline of Command Line Length - MLTK", "ESCU - Previously seen command line arguments"] data_models = ["Endpoint"] providing_technologies = none @@ -745,7 +745,7 @@ 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 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "PR.AC"]} -investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -761,7 +761,7 @@ 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 - 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 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 - 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"], "mitre_attack": ["T1036", "T1043", "T1047", "T1048", "T1053", "T1070", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Backup Logs For Endpoint"] support_searches = ["ESCU - Baseline of Command Line Length - MLTK", "ESCU - Baseline of SMB Traffic - MLTK"] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -777,7 +777,7 @@ version = 1 reference = ["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"] detection_searches = ["ESCU - Detect New Login Attempts to Routers - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Authentication"] providing_technologies = none @@ -794,7 +794,7 @@ version = 1 reference = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] detection_searches = ["ESCU - SQL Injection with Long URLs - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -811,7 +811,7 @@ 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": ["T1059", "T1076", "T1082"], "nist": ["DE.AE", "DE.CM", "ID.AM", "ID.RA", "PR.AC", "PR.DS", "PR.IP", "PR.MA", "PR.PT"]} -investigative_searches = ["ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Update Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Backup Logs For Endpoint"] support_searches = ["ESCU - Add Prohibited Processes to Enterprise Security"] data_models = ["Endpoint", "Network_Traffic", "Web"] providing_technologies = none @@ -832,7 +832,7 @@ version = 1 reference = ["https://meltdownattack.com/"] detection_searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule"] mappings = {"cis20": ["CIS 4"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] support_searches = ["ESCU - Systems Ready for Spectre-Meltdown Windows Patch"] data_models = ["Vulnerabilities"] providing_technologies = none @@ -848,7 +848,7 @@ version = 1 reference = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] detection_searches = ["ESCU - Open Redirect in Splunk Web - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = [] providing_technologies = none @@ -873,7 +873,7 @@ 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"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate Web Activity From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From src ip"] support_searches = [] data_models = [] providing_technologies = none @@ -892,8 +892,8 @@ 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 - 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"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] -support_searches = ["ESCU - Previously Seen EC2 Launches By User", "ESCU - Baseline of Excessive AWS Instances Terminated by User - MLTK", "ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK", "ESCU - Previously Seen AWS Regions"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get EC2 Launch Details", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +support_searches = ["ESCU - Previously Seen AWS Regions", "ESCU - Previously Seen EC2 Launches By User", "ESCU - Baseline of Excessive AWS Instances Terminated by User - MLTK", "ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK"] 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. @@ -924,8 +924,8 @@ 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 - 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"], "nist": ["DE.CM", "DE.DP", "PR.AC", "PR.DS"]} -investigative_searches = ["ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get All AWS Activity From IP Address", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] -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", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get Notable History", "ESCU - Investigate AWS activities via region name", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +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. @@ -942,7 +942,7 @@ 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": ["Command and Control"], "nist": ["PR.AC"]} -investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Process Info", "ESCU - Get DNS traffic ratio"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network ACL Details from ID", "ESCU - Get User Information from Identity Table"] support_searches = ["ESCU - Baseline of blocked outbound traffic from AWS"] data_models = [] providing_technologies = none @@ -961,7 +961,7 @@ 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", "T1059", "T1064"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] support_searches = ["ESCU - Baseline of Command Line Length - MLTK", "ESCU - Previously seen command line arguments"] data_models = ["Endpoint"] providing_technologies = none @@ -977,7 +977,7 @@ 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": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] support_searches = ["ESCU - Baseline of DNS Query Length - MLTK"] data_models = ["Network_Resolution"] providing_technologies = none @@ -993,7 +993,7 @@ 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"], "nist": ["DE.AE", "PR.IP"]} -investigative_searches = ["ESCU - Get Emails From Specific Sender", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Email Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get User Information from Identity Table", "ESCU - Get Email Info"] support_searches = ["ESCU - DNSTwist Domain Names"] data_models = ["Email", "UEBA"] providing_technologies = none @@ -1013,7 +1013,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1059", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] support_searches = ["ESCU - Baseline of Command Line Length - MLTK", "ESCU - Previously seen command line arguments"] data_models = ["Endpoint"] providing_technologies = none @@ -1031,7 +1031,7 @@ 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 Credentails 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"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by app"] +investigative_searches = ["ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by IP Address"] support_searches = [] data_models = [] providing_technologies = none @@ -1049,7 +1049,7 @@ 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", "T1084"], "nist": ["PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1067,7 +1067,7 @@ 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": ["T1015", "T1042", "T1103", "T1112", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1085,7 +1085,7 @@ 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"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId"] +investigative_searches = ["ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN"] support_searches = ["ESCU - Previously Seen EC2 Modifications By User"] data_models = [] providing_technologies = none @@ -1102,7 +1102,7 @@ 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": ["T1015", "T1036", "T1085"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] support_searches = ["ESCU - Baseline of Command Line Length - MLTK"] data_models = ["Endpoint"] providing_technologies = none @@ -1120,7 +1120,7 @@ version = 1 reference = ["https://www.monkey.org/~dugsong/dsniff/"] detection_searches = ["ESCU - Protocols passing authentication in cleartext - Rule"] mappings = {"cis20": ["CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Network_Traffic"] providing_technologies = none @@ -1136,7 +1136,7 @@ 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", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Web Session Information via session id"] +investigative_searches = ["ESCU - Get Web Session Information via session id", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = [] providing_technologies = none @@ -1157,7 +1157,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Defense_Evasion"] detection_searches = ["ESCU - Disabling Remote User Account Control - 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"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1089", "T1112"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1173,7 +1173,7 @@ 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": ["T1042"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1193,7 +1193,7 @@ 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"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1210,7 +1210,7 @@ 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 - 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"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1053", "T1089", "T1103", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1226,7 +1226,7 @@ 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 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1015", "T1068"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1242,7 +1242,7 @@ 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 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] support_searches = ["ESCU - Previously Seen Running Windows Services"] data_models = ["Endpoint"] providing_technologies = none diff --git a/package/default/es_investigations.conf b/package/default/es_investigations.conf index 385a5bdadd..a1bc55fb1c 100644 --- a/package/default/es_investigations.conf +++ b/package/default/es_investigations.conf @@ -3,79 +3,79 @@ 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", "panel://workbench_panel_aws_investigate_user_activities_by_accesskeyid", "panel://workbench_panel_aws_investigate_user_activities_by_source_user"] +panels = ["panel://workbench_panel_aws_investigate_user_activities_by_source_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_aws_investigate_user_activities_by_accesskeyid"] [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", "panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_ec2_launch_details"] +panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_ec2_launch_details", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_aws_network_acl_activity] 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_aws_network_acl_details_from_id", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_dns_traffic_ratio"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_info", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_get_user_information_from_identity_table"] [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_city", "panel://workbench_panel_get_all_aws_activity_from_region", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_all_aws_activity_from_country"] +panels = ["panel://workbench_panel_get_all_aws_activity_from_region", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_all_aws_activity_from_city", "panel://workbench_panel_get_all_aws_activity_from_country"] [panel_group://workbench_panel_group_aws_user_monitoring] label = AWS User Monitoring 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. disabled = 0 -panels = ["panel://workbench_panel_investigate_aws_user_activities_by_user_field", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info"] +panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_aws_user_activities_by_user_field", "panel://workbench_panel_get_notable_info"] [panel_group://workbench_panel_group_account_monitoring_and_controls] label = Account Monitoring and Controls description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. disabled = 0 -panels = ["panel://workbench_panel_get_logon_rights_modifications_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_logon_rights_modifications_for_user"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_logon_rights_modifications_for_user", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_logon_rights_modifications_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_apache_struts_vulnerability] 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_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_posts_from_src", "panel://workbench_panel_investigate_suspicious_strings_in_http_header", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_posts_from_src", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_suspicious_strings_in_http_header"] [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_first_occurrence_and_last_occurrence_of_a_mac_address", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info"] +panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_first_occurrence_and_last_occurrence_of_a_mac_address"] [panel_group://workbench_panel_group_brand_monitoring] 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_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_email_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_email_info"] [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_get_notable_history", "panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_investigate_user_activities_in_all_cloud_regions", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_investigate_cloud_compute_instance_activities", "panel://workbench_panel_investigate_user_activities_in_single_cloud_region", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_ec2_launch_details"] +panels = ["panel://workbench_panel_investigate_cloud_compute_instance_activities", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_ec2_launch_details", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_investigate_user_activities_in_single_cloud_region", "panel://workbench_panel_investigate_user_activities_in_all_cloud_regions", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_coldroot_macos_rat] 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_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_network_traffic_from_src_ip", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_src_ip"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_web_activity_from_src_ip", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_network_traffic_from_src_ip", "panel://workbench_panel_get_user_information_from_identity_table"] [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_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] [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_aws_network_acl_details_from_id", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_info", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_common_phishing_frameworks] label = Common Phishing Frameworks @@ -93,19 +93,19 @@ panels = ["panel://workbench_panel_investigate_aws_ecr_container_listing_activit 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_hash_attempts", "panel://workbench_panel_investigate_failed_logins_for_multiple_destinations", "panel://workbench_panel_investigate_previous_unseen_user", "panel://workbench_panel_investigate_pass_the_ticket_attempts"] +panels = ["panel://workbench_panel_investigate_failed_logins_for_multiple_destinations", "panel://workbench_panel_investigate_pass_the_hash_attempts", "panel://workbench_panel_investigate_previous_unseen_user", "panel://workbench_panel_investigate_pass_the_ticket_attempts"] [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_registry_activity", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_process_file_activity"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_file_activity", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_registry_activity", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_dns_amplification_attacks] label = DNS Amplification Attacks 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. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info"] [panel_group://workbench_panel_group_dns_hijacking] label = DNS Hijacking @@ -117,91 +117,103 @@ panels = ["panel://workbench_panel_get_dns_server_history_for_a_host"] 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_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_dns_traffic_ratio"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_disabling_security_tools] 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_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] [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 blacklists. disabled = 0 -panels = ["panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_investigate_web_activity_from_src_ip"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_web_activity_from_src_ip", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_user_information_from_identity_table"] [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_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_hidden_cobra_malware] 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_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_host_redirection] label = Host Redirection 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. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_server_history_for_a_host"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_jboss_vulnerability] label = JBoss Vulnerability 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. disabled = 0 -panels = ["panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_vulnerability_logs_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info"] [panel_group://workbench_panel_group_kubernetes_scanning_activity] 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_gcp_kubernetes_activity_by_src_ip", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_amazon_eks_kubernetes_activity_by_src_ip", "panel://workbench_panel_get_notable_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_gcp_kubernetes_activity_by_src_ip", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_amazon_eks_kubernetes_activity_by_src_ip"] + +[panel_group://workbench_panel_group_kubernetes_sensitive_object_access_activity] +label = Kubernetes Sensitive Object Access Activity +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. +disabled = 0 +panels = ["panel://workbench_panel_get_notable_info"] + +[panel_group://workbench_panel_group_kubernetes_sensitive_role_activity] +label = Kubernetes Sensitive Role Activity +description = This story addresses detection and response around Sensitive Role usage within a Kubernetes clusters against cluster resources and namespaces. +disabled = 0 +panels = ["panel://workbench_panel_get_notable_info"] [panel_group://workbench_panel_group_lateral_movement] 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_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] [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_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_monitor_backup_solution] label = Monitor Backup Solution 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. disabled = 0 -panels = ["panel://workbench_panel_all_backup_logs_for_host", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_all_backup_logs_for_host", "panel://workbench_panel_get_risk_modifiers_for_user"] [panel_group://workbench_panel_group_monitor_for_unauthorized_software] 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_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_monitor_for_updates] label = Monitor for Updates description = Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches. disabled = 0 -panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info"] [panel_group://workbench_panel_group_netsh_abuse] 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_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_orangeworm_attack_group] 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_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_phishing_payloads] label = Phishing Payloads @@ -213,61 +225,61 @@ panels = ["panel://workbench_panel_get_parent_process_info"] 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_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] [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_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] [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_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_backup_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_sysmon_wmi_activity_for_host", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_sysmon_wmi_activity_for_host", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_backup_logs_for_endpoint"] [panel_group://workbench_panel_group_router_and_infrastructure_security] label = Router and Infrastructure Security 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. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_sql_injection] label = SQL Injection 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. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_info"] [panel_group://workbench_panel_group_samsam_ransomware] 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_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_backup_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_backup_logs_for_endpoint"] [panel_group://workbench_panel_group_spectre_and_meltdown_vulnerabilities] label = Spectre And Meltdown Vulnerabilities description = Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_splunk_enterprise_vulnerability] label = Splunk Enterprise Vulnerability description = Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains. disabled = 0 -panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info"] [panel_group://workbench_panel_group_splunk_enterprise_vulnerability_cve_2018_11409] 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_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_network_traffic_from_src_ip", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_investigate_web_activity_from_src_ip"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_network_traffic_from_src_ip", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_investigate_web_activity_from_src_ip"] [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", "panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_ec2_launch_details"] +panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_ec2_launch_details", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_suspicious_aws_login_activities] label = Suspicious AWS Login Activities @@ -279,55 +291,55 @@ panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn"] 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", "panel://workbench_panel_aws_s3_bucket_details_via_bucketname", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_investigate_aws_activities_via_region_name"] +panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_aws_s3_bucket_details_via_bucketname", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table"] [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_aws_network_acl_details_from_id", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_dns_traffic_ratio"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_info", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_suspicious_command_line_executions] 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_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] [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_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] [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_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_email_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_email_info"] [panel_group://workbench_panel_group_suspicious_mshta_activity] 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_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] [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_okta_activity_by_app", "panel://workbench_panel_investigate_okta_activity_by_ip_address", "panel://workbench_panel_investigate_user_activities_in_okta"] +panels = ["panel://workbench_panel_investigate_okta_activity_by_app", "panel://workbench_panel_investigate_user_activities_in_okta", "panel://workbench_panel_investigate_okta_activity_by_ip_address"] [panel_group://workbench_panel_group_suspicious_wmi_use] 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_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_sysmon_wmi_activity_for_host", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_sysmon_wmi_activity_for_host", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] [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_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_unusual_aws_ec2_modifications] label = Unusual AWS EC2 Modifications @@ -339,55 +351,55 @@ panels = ["panel://workbench_panel_get_ec2_instance_details_by_instanceid", "pan 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_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_use_of_cleartext_protocols] label = Use of Cleartext Protocols description = Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. disabled = 0 -panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_web_fraud_detection] 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_web_session_information_via_session_id", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_emails_from_specific_sender"] +panels = ["panel://workbench_panel_get_web_session_information_via_session_id", "panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info"] [panel_group://workbench_panel_group_windows_defense_evasion_tactics] 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_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] [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_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] [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_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] [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_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] [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_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] [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_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] diff --git a/package/default/macros.conf b/package/default/macros.conf index ab9cb7acb0..d2e824a56d 100644 --- a/package/default/macros.conf +++ b/package/default/macros.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-06-03T20:09:14 UTC +# On Date: 2020-06-03T20:28:01 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/savedsearches.conf b/package/default/savedsearches.conf index dca4c2534a..13a435839d 100644 --- a/package/default/savedsearches.conf +++ b/package/default/savedsearches.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-06-03T20:09:14 UTC +# On Date: 2020-06-03T20:28:01 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -9312,7 +9312,7 @@ action.escu.full_search_name = ESCU - Get Notable Info description = This search queries the notable index to retrieve detailed information captured within the notable. Every notable has a unique ID associated with it, which is used to point us directly to the notable event under investigation. action.escu.creation_date = 2017-09-20 action.escu.modification_date = 2017-09-20 -action.escu.analytic_story = ["AWS Cryptomining", "AWS Network ACL Activity", "AWS User Monitoring", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Asset Tracking", "Brand Monitoring", "Cloud Cryptomining", "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 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 Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "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"] +action.escu.analytic_story = ["AWS Cryptomining", "AWS Network ACL Activity", "AWS User Monitoring", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Asset Tracking", "Brand Monitoring", "Cloud Cryptomining", "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 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 Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "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", "Kubernetes Sensitive Role Activity", "Kubernetes Sensitive Object Access Activity"] action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 action.escu.providing_technologies = [] diff --git a/package/default/transforms.conf b/package/default/transforms.conf index f810386136..5a6491027d 100644 --- a/package/default/transforms.conf +++ b/package/default/transforms.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-06-03T20:09:14 UTC +# On Date: 2020-06-03T20:28:01 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/use_case_library.conf b/package/default/use_case_library.conf index 9a6b59f309..1404585c4d 100644 --- a/package/default/use_case_library.conf +++ b/package/default/use_case_library.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-06-03T20:09:14 UTC +# On Date: 2020-06-03T20:28:01 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 = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By Source User"] +searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - AWS Investigate User Activities By Source User", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By AccessKeyId"] 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 = "David Dorsey, Splunk" spec_version = 3 -searches = ["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", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] +searches = ["ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get EC2 Launch Details", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] 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 = 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 = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Process Info", "ESCU - Get DNS traffic ratio"] +searches = ["ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network ACL Details from ID", "ESCU - Get User Information from Identity Table"] 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. @@ -52,7 +52,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["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 City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From City"] +searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Country"] 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 whitelist specific IPs (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. @@ -64,7 +64,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Investigate AWS User Activities by user field"] +searches = ["ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Get Notable History", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable Info"] 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. \ @@ -78,7 +78,7 @@ version = 1 references = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Identify New User Accounts - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Short Lived Windows Accounts - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] +searches = ["ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Short Lived Windows Accounts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. narrative = Monitoring user accounts within your enterprise is a critical analytic function that helps ensure that credential and access policies/procedures are properly implemented and are being enforced. Proactive ad-hoc hunting, as well as routine monitoring, can ensure user or system accounts are not being abused by unauthorized individuals or processes. In the event of a network event or breach, user-authentication logs are a key resource in determining if or how an account might have been compromised or co-opted, leading to suspicious or malicious activity. @@ -89,7 +89,7 @@ version = 1 references = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Suspicious Java Classes - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web POSTs From src", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] +searches = ["ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Suspicious Java Classes - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Investigate Web POSTs From src", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Suspicious Strings in HTTP Header"] 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.\ @@ -113,7 +113,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule", "ESCU - Get Notable Info", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable History"] +searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address"] 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. @@ -124,7 +124,7 @@ 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 = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Get Emails From Specific Sender", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Email Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] +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 Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get User Information from Identity Table", "ESCU - Get Email Info"] 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.\ @@ -137,7 +137,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] +searches = ["ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get EC2 Launch Details", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] 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. \ @@ -151,7 +151,7 @@ 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 = "Jose Hernandez, Splunk" spec_version = 3 -searches = ["ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] +searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable History", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get User Information from Identity Table"] 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.\ @@ -164,7 +164,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] 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. \ @@ -177,7 +177,7 @@ 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 = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Parent Process Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Process Info", "ESCU - Get DNS traffic ratio"] +searches = ["ESCU - Excessive DNS Failures - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - TOR Traffic - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network ACL Details from ID", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] 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. @@ -201,7 +201,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - GCP GCR container uploaded - Rule", "ESCU - New container uploaded to AWS ECR - Rule", "ESCU - Investigate AWS ECR container listing activity"] +searches = ["ESCU - New container uploaded to AWS ECR - Rule", "ESCU - GCP GCR container uploaded - Rule", "ESCU - Investigate AWS ECR container listing activity"] 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. @@ -212,7 +212,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Pass the Ticket Attempts"] +searches = ["ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Pass the Ticket Attempts"] 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.\ @@ -225,7 +225,7 @@ version = 2 references = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process File Activity", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Process Registry Activity"] +searches = ["ESCU - Suspicious Reg exe Process - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process File Activity", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Registry Activity", "ESCU - Get Parent Process Info"] 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. \ @@ -239,7 +239,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History"] +searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info"] 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. @@ -251,7 +251,7 @@ 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 = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - DNS record changed - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get DNS Server History for a host"] +searches = ["ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple 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"] 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. \ @@ -270,7 +270,7 @@ 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 = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect USB device insertion - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio", "ESCU - Get User Information from Identity Table"] 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. @@ -281,7 +281,7 @@ 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 = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Attempt To Stop Security Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Suspicious Reg exe Process - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] 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 blacklist (which would prevent them from running). @@ -292,7 +292,7 @@ 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 = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Investigate Web Activity From src ip", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] +searches = ["ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio", "ESCU - Get User Information from Identity Table"] 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 blacklists. 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 blacklists 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. @@ -303,7 +303,7 @@ 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 = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] 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.\ @@ -316,7 +316,7 @@ 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 = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] 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.\ @@ -330,7 +330,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Windows hosts file modification - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] +searches = ["ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] 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. @@ -341,7 +341,7 @@ version = 1 references = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info"] 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.\ @@ -366,7 +366,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Splunk" spec_version = 3 -searches = ["ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - Kubernetes Azure scan fingerprint - Rule", "ESCU - Kubernetes Azure pod scan fingerprint - Rule", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable Info", "ESCU - Get Notable History"] +searches = ["ESCU - Kubernetes Azure scan fingerprint - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Kubernetes Azure pod scan fingerprint - Rule", "ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Amazon EKS Kubernetes activity by src ip"] 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. @@ -377,20 +377,20 @@ version = 1 references = ["https://www.splunk.com/en_us/blog/security/approaching-kubernetes-security-detecting-kubernetes-scan-with-splunk.html"] maintainers = "Rod Soto, Splunk" spec_version = 3 -searches = ["ESCU - Kubernetes Azure detect suspicious kubectl calls - Rule", "ESCU - Kubernetes Azure detect sensitive object access - Rule", "ESCU - Kubernetes Azure detect service accounts forbidden failure access - Rule"] +searches = ["ESCU - Kubernetes Azure detect suspicious kubectl calls - Rule", "ESCU - Kubernetes Azure detect service accounts forbidden failure access - Rule", "ESCU - Kubernetes Azure detect sensitive object access - Rule", "ESCU - Get Notable Info"] 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. -[analytic_story://Kubernetes Sensitive Object Access Activity] +[analytic_story://Kubernetes Sensitive Role Activity] category = Cloud Security last_updated = 2020-05-20 version = 1 references = ["https://www.splunk.com/en_us/blog/security/approaching-kubernetes-security-detecting-kubernetes-scan-with-splunk.html"] maintainers = "Rod Soto, Splunk" spec_version = 3 -searches = ["ESCU - Kubernetes Azure detect suspicious kubectl calls - Rule", "ESCU - Kubernetes Azure detect sensitive object access - Rule", "ESCU - Kubernetes Azure detect service accounts forbidden failure access - Rule"] +searches = ["ESCU - Kubernetes Azure detect sensitive role access - Rule", "ESCU - Kubernetes Azure detect most active service accounts by pod namespace - Rule", "ESCU - Kubernetes Azure detect RBAC authorization by account - Rule", "ESCU - Get Notable Info"] 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 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. +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 [analytic_story://Lateral Movement] category = Adversary Tactics @@ -399,7 +399,7 @@ version = 2 references = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] 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.\ @@ -414,7 +414,7 @@ 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 = "David Dorsey, Splunk" spec_version = 3 -searches = ["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", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - 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 - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] 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: \ @@ -434,7 +434,7 @@ version = 1 references = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - All backup logs for host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History"] +searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - All backup logs for host", "ESCU - Get Risk Modifiers For User"] 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. @@ -445,7 +445,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Update Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] 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. @@ -457,7 +457,7 @@ version = 1 references = ["https://learn.cisecurity.org/20-controls-download"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - No Windows Updates in a time frame - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History"] +searches = ["ESCU - No Windows Updates in a time frame - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches. 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.\ @@ -470,7 +470,7 @@ version = 1 references = ["https://technet.microsoft.com/library/bb490939.aspx", "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 = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Processes launching netsh - Rule", "ESCU - Processes created by netsh - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] 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`. @@ -482,7 +482,7 @@ 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 = "David Dorsey, Splunk" 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 - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] +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 Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] 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.\ @@ -515,7 +515,7 @@ 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 = "iDefense Cyber Espionage Team, iDefense" spec_version = 3 -searches = ["ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Registry Keys Used For Persistence - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] 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.\ @@ -553,7 +553,7 @@ version = 1 references = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] +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 Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] 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. @@ -564,7 +564,7 @@ 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 = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Common Ransomware Notes - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Backup Logs For Endpoint"] 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. @@ -575,7 +575,7 @@ 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 = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] +searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] 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. @@ -587,7 +587,7 @@ version = 1 references = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable Info"] 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. @@ -599,7 +599,7 @@ 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 = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Common Ransomware Notes - Rule", "ESCU - Batch File Write to System32 - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Batch File Write to System32 - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Update Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Backup Logs For Endpoint"] 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.\ @@ -615,7 +615,7 @@ version = 1 references = ["https://meltdownattack.com/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] +searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] 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. @@ -626,7 +626,7 @@ version = 1 references = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Open Redirect in Splunk Web - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History"] +searches = ["ESCU - Open Redirect in Splunk Web - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains. narrative = This Analytic Story is associated with CVE-2016-4859, an open-redirect vulnerability in the following versions of Splunk Enterprise:\ \ @@ -646,7 +646,7 @@ 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 = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable History"] +searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From src ip"] 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.\ @@ -660,7 +660,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] +searches = ["ESCU - EC2 Instance Started In Previously Unseen Region - 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 - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get EC2 Launch Details", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] 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. @@ -671,7 +671,7 @@ version = 1 references = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] maintainers = "Bhavin Patel, Splunk" 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"] +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 - Detect new user AWS Console Login - Rule", "ESCU - AWS Investigate User Activities By ARN"] 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. @@ -682,7 +682,7 @@ 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 = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get All AWS Activity From IP Address", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] +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 - AWS Investigate User Activities By ARN", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get Notable History", "ESCU - Investigate AWS activities via region name", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] 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.\ @@ -695,7 +695,7 @@ version = 1 references = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Process Info", "ESCU - Get DNS traffic ratio"] +searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network ACL Details from ID", "ESCU - Get User Information from Identity Table"] 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.\ @@ -709,7 +709,7 @@ 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 = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] 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. @@ -720,7 +720,7 @@ 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 = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Excessive DNS Failures - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] 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. @@ -731,7 +731,7 @@ version = 1 references = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Get Emails From Specific Sender", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Email Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] +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 Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get User Information from Identity Table", "ESCU - Get Email Info"] 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: \ @@ -746,7 +746,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] 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 white-listing solutions via the mshta.exe process, which executes Microsoft HTML applications with the .hta suffix. In these cases, attackers use the trusted Windows utility to eproxy execution of malicious files, whether an .hta application, javascript, or VBScript.\ One example of a notable mshta.exe attack was the Kovter malware (https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5) that was implicated in ransomware and click-fraud attacks. Kovter utilized .hta to execute a series of javascript commands, each progressively more dangerous. According to the Mitre Parternship Network (https://attack.mitre.org/wiki/Technique/T1170), FIN7 has leveraged mshta.exe, as has the MuddyWater group, who used it to execute its POWERSTATS payload (which then used the utility to execute additional payloads).\ @@ -759,7 +759,7 @@ 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 = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by app"] +searches = ["ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by IP Address"] 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. \ @@ -772,7 +772,7 @@ 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 = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - WMI Temporary Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Process Execution via WMI - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Script Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - WMI Temporary Event Subscription - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Process Execution via WMI - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] 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.\ @@ -785,7 +785,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] 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.\ @@ -798,7 +798,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId"] +searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN"] 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. @@ -810,7 +810,7 @@ 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 = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] 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.\ @@ -823,7 +823,7 @@ version = 1 references = ["https://www.monkey.org/~dugsong/dsniff/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] +searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] 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. @@ -834,7 +834,7 @@ 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 = "Jim Apger, Splunk" spec_version = 3 -searches = ["ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Web Session Information via session id"] +searches = ["ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Get Web Session Information via session id", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Notable Info"] 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.\ @@ -850,7 +850,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Defense_Evasion"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Suspicious Reg exe Process - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] 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. @@ -861,7 +861,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] +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 Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] 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. \ @@ -876,7 +876,7 @@ 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 = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Deleting Shadow Copies - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Windows Event Log Cleared - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] 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). @@ -888,7 +888,7 @@ 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 = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] 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. @@ -899,7 +899,7 @@ version = 2 references = ["https://attack.mitre.org/tactics/TA0004/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] 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. @@ -910,7 +910,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] 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. diff --git a/response_tasks/get_notable_info.yml b/response_tasks/get_notable_info.yml index b51d7d48b7..90491c4aac 100644 --- a/response_tasks/get_notable_info.yml +++ b/response_tasks/get_notable_info.yml @@ -67,3 +67,5 @@ tags: - Windows Persistence Techniques - Windows Privilege Escalation - Windows Service Abuse + - Kubernetes Sensitive Role Activity + - Kubernetes Sensitive Object Access Activity diff --git a/stories/kubernetes_sensitive_role_activity.yml b/stories/kubernetes_sensitive_role_activity.yml index 921b5d0bf7..739bce3ae7 100644 --- a/stories/kubernetes_sensitive_role_activity.yml +++ b/stories/kubernetes_sensitive_role_activity.yml @@ -2,8 +2,8 @@ author: "Rod Soto, Splunk" date: "2020-05-20" description: "This story addresses detection and response around Sensitive Role usage within a Kubernetes clusters against cluster resources and namespaces." id: 2574e6d9-7254-4751-8925-0447deeec8ew -name: "Kubernetes Sensitive Object Access Activity" -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." +name: "Kubernetes Sensitive Role Activity" +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" references: - https://www.splunk.com/en_us/blog/security/approaching-kubernetes-security-detecting-kubernetes-scan-with-splunk.html tags: From 2f3d2d7a49317423086a17f8c20fc342e6fb2079 Mon Sep 17 00:00:00 2001 From: bpatel Date: Wed, 3 Jun 2020 13:35:28 -0700 Subject: [PATCH 14/14] remove conflicts conf files, generate will automatically create it --- package/default/analytic_stories.conf | 1252 --- package/default/es_investigations.conf | 1501 ---- package/default/macros.conf | 1033 --- package/default/savedsearches.conf | 10143 ----------------------- package/default/transforms.conf | 202 - package/default/use_case_library.conf | 3818 --------- 6 files changed, 17949 deletions(-) delete mode 100644 package/default/analytic_stories.conf delete mode 100644 package/default/es_investigations.conf delete mode 100644 package/default/macros.conf delete mode 100644 package/default/savedsearches.conf delete mode 100644 package/default/transforms.conf delete mode 100644 package/default/use_case_library.conf diff --git a/package/default/analytic_stories.conf b/package/default/analytic_stories.conf deleted file mode 100644 index 06816275a9..0000000000 --- a/package/default/analytic_stories.conf +++ /dev/null @@ -1,1252 +0,0 @@ -############# -# Automatically generated by generator.py in splunk/security-content -# On Date: 2020-06-03T20:28:01 UTC -# Author: Splunk Security Research -# Contact: research@splunk.com -############# - -### STORIES ### - -[AWS Cross Account Activity] -category = Cloud Security -creation_date = 2018-06-04 -modification_date = 2018-06-04 -id = 2f2f610a-d64d-48c2-b57c-967a2b49ab5a -version = 1 -reference = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] -detection_searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule"] -mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By Source User", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By AccessKeyId"] -support_searches = ["ESCU - Previously Seen AWS Cross Account Activity"] -data_models = [] -providing_technologies = none -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.\ -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. - -[AWS Cryptomining] -category = Cloud Security -creation_date = 2018-03-08 -modification_date = 2018-03-08 -id = ced74200-8465-4bc3-bd2c-9a782eec6750 -version = 1 -reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] -detection_searches = ["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"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get EC2 Launch Details", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] -support_searches = ["ESCU - Previously Seen AWS Regions", "ESCU - Previously Seen EC2 AMIs", "ESCU - Previously Seen EC2 Instance Types", "ESCU - Previously Seen EC2 Launches By User"] -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. -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. \ -hen 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. - -[AWS Network ACL Activity] -category = Cloud Security -creation_date = 2018-05-21 -modification_date = 2018-05-21 -id = 2e8948a5-5239-406b-b56b-6c50ff268af4 -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"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network ACL Details from ID", "ESCU - Get User Information from Identity Table"] -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. - -[AWS Suspicious Provisioning Activities] -category = Cloud Security -creation_date = 2018-03-16 -modification_date = 2018-03-16 -id = 3338b567-3804-4261-9889-cf0ca4753c7f -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"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Country"] -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 whitelist specific IPs (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. - -[AWS User Monitoring] -category = Cloud Security -creation_date = 2018-03-12 -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"], "nist": ["DE.CM", "DE.DP", "ID.AM", "PR.AC"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable Info"] -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"] -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. -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. \ -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. - -[Account Monitoring and Controls] -category = Best Practices -creation_date = 2017-09-06 -modification_date = 2017-09-06 -id = 8892a655-6205-55f7-abba-06460e38c8ae -version = 1 -reference = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] -detection_searches = ["ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Short Lived Windows Accounts - Rule"] -mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078", "T1136"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] -support_searches = [] -data_models = ["Change"] -providing_technologies = none -description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. -narrative = Monitoring user accounts within your enterprise is a critical analytic function that helps ensure that credential and access policies/procedures are properly implemented and are being enforced. Proactive ad-hoc hunting, as well as routine monitoring, can ensure user or system accounts are not being abused by unauthorized individuals or processes. In the event of a network event or breach, user-authentication logs are a key resource in determining if or how an account might have been compromised or co-opted, leading to suspicious or malicious activity. - -[Apache Struts Vulnerability] -category = Vulnerability -creation_date = 2018-12-06 -modification_date = 2018-12-06 -id = 2dcfd6a2-e7d2-4873-b6ba-adaf819d2a1e -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"], "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 - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Investigate Web POSTs From src", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Suspicious Strings in HTTP Header"] -support_searches = [] -data_models = ["Endpoint"] -providing_technologies = none -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.\ -This Analytic Story contains two different searches that help to identify activity that may be related to this issue. The first search looks for characteristics of the `Content-Type` header consistent with attempts to exploit the vulnerability. This should be a relatively pertinent indicator, as the `Content-Type` header is generally consistent and does not have a large degree of variation.\ -The second search looks for the execution of various commands typically entered on the command shell when an attacker first lands on a system. These commands are not generally executed on web servers during the course of day-to-day operation, but they may be used when the system is undergoing maintenance or troubleshooting.\ -First, it is helpful is to understand how often the notable event is generated, as well as the commonalities in some of these events. This may help determine whether this is a common occurrence that is of a lesser concern or a rare event that may require more extensive investigation. It can also help to understand whether the issue is restricted to a single user or system or is broader in scope.\ -hen looking at the target of the behavior illustrated by the event, you should note the sensitivity of the user and or/system to help determine the potential impact. It is also helpful to see what other events involving the target have occurred in the recent past. This can help tie different events together and give further situational awareness regarding the target.\ -Various types of information for external systems should be reviewed and (potentially) collected if the incident is, indeed, judged to be malicious. Information like this can be useful in generating your own threat intelligence to create alerts in the future.\ -Looking at the country, responsible party, and fully qualified domain names associated with the external IP address--as well as the registration information associated with those domain names, if they are frequently visited by others--can help you answer the question of "who," in regard to the external system. Answering that can help qualify the event and may serve useful for tracking. In addition, there are various sources that can provide some reputation information on the IP address or domain name, which can assist in determining if the event is malicious in nature. Finally, determining whether or not there are other events associated with the IP address may help connect some dots or show other events that should be brought into scope.\ -Gathering various data elements on the system of interest can sometimes help quickly determine that something suspicious may be happening. Some of these items include determining who else may have recently logged into the system, whether any unusual scheduled tasks exist, whether the system is communicating on suspicious ports, whether there are modifications to sensitive registry keys, and whether there are any known vulnerabilities on the system. This information can often highlight other activity commonly seen in attack scenarios or give more information about how the system may have been targeted.\ -hen a specific service or application is targeted, it is often helpful to know the associated version to help determine whether or not it is vulnerable to a specific exploit.\ -hen it is suspected there is an attack targeting a web server, it is helpful to look at some of the behavior of the web service to see if there is evidence that the service has been compromised. Some indications of this might be network connections to external resources, the web service spawning child processes that are not associated with typical behavior, and whether the service wrote any files that might be malicious in nature.\ -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. - -[Asset Tracking] -category = Best Practices -creation_date = 2017-09-13 -modification_date = 2017-09-13 -id = 91c676cf-0b23-438d-abee-f6335e1fce77 -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"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address"] -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. - -[Brand Monitoring] -category = Abuse -creation_date = 2017-12-19 -modification_date = 2017-12-19 -id = 91c676cf-0b23-438d-abee-f6335e1fce78 -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 Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get User Information from Identity Table", "ESCU - Get Email Info"] -support_searches = ["ESCU - DNSTwist Domain Names"] -data_models = ["Email", "Network_Resolution", "Web"] -providing_technologies = none -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.\ -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. - -[Cloud Cryptomining] -category = Cloud Security -creation_date = 2019-10-02 -modification_date = 2019-10-02 -id = 3b96d13c-fdc7-45dd-b3ad-c132b31cdd2a -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 - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule"] -mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Investigate Cloud Compute Instance Activities", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get EC2 Launch Details", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] -support_searches = ["ESCU - Previously Seen Cloud Compute Creations By User", "ESCU - Previously Seen Cloud Compute Images", "ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK", "ESCU - Previously Seen Cloud Regions", "ESCU - Previously Seen Cloud Compute Instance Types"] -data_models = ["Cloud_Infrastructure"] -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. -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. \ -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. - -[ColdRoot MacOS RAT] -category = Malware -creation_date = 2019-01-09 -modification_date = 2019-01-09 -id = bd91a2bc-d20b-4f44-a982-1bea98e86390 -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"], "nist": ["DE.DP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable History", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get User Information from Identity Table"] -support_searches = [] -data_models = [] -providing_technologies = none -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.\ -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. - -[Collection and Staging] -category = Adversary Tactics -creation_date = 2020-02-03 -modification_date = 2020-02-03 -id = 8e03c61e-13c4-4dcd-bfbe-5ce5a8dc031a -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": ["T1043", "T1074", "T1114"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -support_searches = [] -data_models = ["Endpoint", "Network_Traffic"] -providing_technologies = none -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. \ -Use the searches to detect and monitor suspicious behavior related to these activities. - -[Command and Control] -category = Adversary Tactics -creation_date = 2018-06-01 -modification_date = 2018-06-01 -id = 943773c6-c4de-4f38-89a8-0b92f98804d8 -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": ["T1043", "T1048", "T1095"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network ACL Details from ID", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -support_searches = ["ESCU - Baseline of blocked outbound traffic from AWS", "ESCU - Baseline of DNS Query Length - MLTK"] -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. - -[Common Phishing Frameworks] -category = Adversary Tactics -creation_date = 2019-04-29 -modification_date = 2019-04-29 -id = 9a64ab44-9214-4639-8163-7eaa2621bd61 -version = 1 -reference = ["https://github.com/kgretzky/evilginx2", "https://attack.mitre.org/techniques/T1192/", "https://breakdev.org/evilginx-advanced-phishing-with-two-factor-authentication-bypass/"] -detection_searches = ["ESCU - Detect DNS requests to Phishing Sites leveraging EvilGinx2 - Rule"] -mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1192"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Certificate logs for a domain"] -support_searches = [] -data_models = ["Network_Resolution"] -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. - -[Container Implantation Monitoring and Investigation] -category = Cloud Security -creation_date = 2020-02-20 -modification_date = 2020-02-20 -id = aa0e28b1-0521-4b6f-9d2a-7b87e34af246 -version = 1 -reference = ["https://github.com/splunk/cloud-datamodel-security-research"] -detection_searches = ["ESCU - GCP GCR container uploaded - Rule", "ESCU - New container uploaded to AWS ECR - Rule"] -mappings = {} -investigative_searches = ["ESCU - Investigate AWS ECR container listing activity"] -support_searches = [] -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. - -[Credential Dumping] -category = Adversary Tactics -creation_date = 2020-02-04 -modification_date = 2020-02-04 -id = 854d78bf-d0e2-4f4e-b05c-640905f86d7a -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 - 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 - 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", "T1064", "T1086"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Pass the Ticket Attempts"] -support_searches = [] -data_models = ["Endpoint"] -providing_technologies = none -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.\ -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. - -[DHS Report TA18-074A] -category = Malware -creation_date = 2020-01-22 -modification_date = 2020-01-22 -id = 0c016e5c-88be-4e2c-8c6c-c2b55b4fb4ef -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 Name Used by Dragonfly Threat Actors - 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": ["T1031", "T1043", "T1050", "T1053", "T1059", "T1064", "T1078", "T1086", "T1089", "T1103", "T1112", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.AT", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process File Activity", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Registry Activity", "ESCU - Get Parent Process Info"] -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. -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. \ -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. - -[DNS Amplification Attacks] -category = Abuse -creation_date = 2016-09-13 -modification_date = 2016-09-13 -id = e8afd39e-3294-11e6-b39d-a45e60c6700 -version = 1 -reference = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] -detection_searches = ["ESCU - Large Volume of DNS ANY Queries - Rule"] -mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info"] -support_searches = [] -data_models = ["Network_Resolution"] -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. - -[DNS Hijacking] -category = Adversary Tactics -creation_date = 2020-02-04 -modification_date = 2020-02-04 -id = 8169f17b-ef68-4b59-aa28-586907301221 -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"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get DNS Server History for a host"] -support_searches = ["ESCU - Discover DNS records"] -data_models = ["Network_Resolution"] -providing_technologies = none -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. \ -On January 22, 2019, the US Department of Homeland Security 2019's Cybersecurity and Infrastructure Security Agency (CISA) raised awareness of some high-profile DNS hijacking attacks against infrastructure, both in the United States and abroad. It issued Emergency Directive 19-01 (see https://cyber.dhs.gov/ed/19-01/), which summarized the activity and required government agencies to take the following four actions, all within 10 days: \ -1. For all .gov or other agency-managed domains, audit public DNS records on all authoritative and secondary DNS servers, verify that they resolve to the intended location or report them to CISA.\ -1. Update the passwords for all accounts on systems that can make changes to each agency 2019's DNS records.\ -1. Implement multi-factor authentication (MFA) for all accounts on systems that can make changes to each agency's 2019 DNS records or, if impossible, provide CISA with the names of systems, the reasons why MFA cannot be enabled within the required timeline, and an ETA for when it can be enabled.\ -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. - -[Data Protection] -category = Abuse -creation_date = 2017-09-14 -modification_date = 2017-09-14 -id = 91c676cf-0b23-438d-abee-f6335e1fce33 -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"], "mitre_attack": ["T1043"], "nist": ["DE.AE", "DE.CM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio", "ESCU - Get User Information from Identity Table"] -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. - -[Disabling Security Tools] -category = Adversary Tactics -creation_date = 2020-02-04 -modification_date = 2020-02-04 -id = fcc27099-46a0-46b0-a271-5c7dab56b6f1 -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": ["T1031", "T1050", "T1059", "T1089", "T1112"], "nist": ["DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -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 blacklist (which would prevent them from running). - -[Dynamic DNS] -category = Malware -creation_date = 2018-09-06 -modification_date = 2018-09-06 -id = 8169f17b-ef68-4b59-aae8-586907301221 -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 13", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1041"], "nist": ["DE.CM", "DE.DP", "PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio", "ESCU - Get User Information from Identity Table"] -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 blacklists. -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 blacklists 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. - -[Emotet Malware DHS Report TA18-201A ] -category = Malware -creation_date = 2020-01-27 -modification_date = 2020-01-27 -id = bb9f5ed2-916e-4364-bb6d-91c310efcf52 -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": ["T1043", "T1059", "T1072", "T1087", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -support_searches = ["ESCU - Add Prohibited Processes to Enterprise Security", "ESCU - Baseline of SMB Traffic - MLTK"] -data_models = ["Email", "Endpoint", "Network_Traffic"] -providing_technologies = none -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.\ -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. - -[Hidden Cobra Malware] -category = Malware -creation_date = 2020-01-22 -modification_date = 2020-01-22 -id = baf7580b-d4b4-4774-8173-7d198e9da335 -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": ["T1043", "T1059", "T1064", "T1076"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Previously seen command line arguments", "ESCU - Baseline of DNS Query Length - 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. -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.\ -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. - -[Host Redirection] -category = Abuse -creation_date = 2017-09-14 -modification_date = 2017-09-14 -id = 2e8948a5-5239-406b-b56b-6c50fe268af4 -version = 1 -reference = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] -detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule"] -mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] -support_searches = [] -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. - -[JBoss Vulnerability] -category = Vulnerability -creation_date = 2017-09-14 -modification_date = 2017-09-14 -id = 1f5294cb-b85f-4c2d-9c58-ffcf248f52bd -version = 1 -reference = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] -detection_searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule"] -mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery", "Reconnaissance"], "mitre_attack": ["T1082"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info"] -support_searches = [] -data_models = ["Web"] -providing_technologies = none -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.\ -hen looking at the target of the behavior uncovered by the event, you should note the sensitivity of the user and or/system to help determine the potential impact. It is also helpful to identify other recent events involving the target. This can help tie different events together and give further situational awareness regarding the target host.\ -Various types of information for external systems should be reviewed and, potentially, collected if the incident is, indeed, judged to be malicious. This data may be useful for generating your own threat intelligence, so you can create future alerts.\ -The following factors may assist you in determining whether the event is malicious: \ -1. Country of origin\ -1. Responsible party\ -1. Fully qualified domain names associated with the external IP address\ -1. Registration of fully qualified domain names associated with external IP address Determining whether it is a dynamic domain frequently visited by others and/or how third parties categorize it can also help you qualify and understand the event and possible motivation for the attack. In addition, there are various sources that may provide reputation information on the IP address or domain name, which can assist you in determining whether the event is malicious in nature. Finally, determining whether there are other events associated with the IP address may help connect data points or expose other historic events that might be brought back into scope.\ -Gathering various data on the system of interest can sometimes help quickly determine whether something suspicious is happening. Some of these items include determining who else may have logged into the system recently, whether any unusual scheduled tasks exist, whether the system is communicating on suspicious ports, whether there are modifications to sensitive registry keys, and/or whether there are any known vulnerabilities on the system. This information can often highlight other activity commonly seen in attack scenarios or give more information about how the system may have been targeted.\ -hen a specific service or application is targeted, it is often helpful to know the associated version, to help determine whether it is vulnerable to a specific exploit.\ -If you suspect an attack targeting a web server, it is helpful to look at some of the behavior of the web service to see if there is evidence that the service has been compromised. Some indications of this might be network connections to external resources, the web service spawning child processes that are not associated with typical behavior, and whether the service wrote any files that might be malicious in nature.\ -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. - -[Kubernetes Scanning Activity] -category = Cloud Security -creation_date = 2020-04-15 -modification_date = 2020-04-15 -id = a9ef59cf-e981-4e66-9eef-bb049f695c09 -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 scan detection - Rule", "ESCU - Kubernetes Azure pod scan fingerprint - Rule", "ESCU - Kubernetes Azure scan fingerprint - Rule"] -mappings = {"kill_chain_phases": ["Reconnaissance"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Amazon EKS Kubernetes activity by src ip"] -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. - -[Kubernetes Sensitive Object Access Activity] -category = Cloud Security -creation_date = 2020-05-20 -modification_date = 2020-05-20 -id = 2574e6d9-7254-4751-8925-0447deeec8ea -version = 1 -reference = ["https://www.splunk.com/en_us/blog/security/approaching-kubernetes-security-detecting-kubernetes-scan-with-splunk.html"] -detection_searches = ["ESCU - Kubernetes Azure detect sensitive object access - Rule", "ESCU - Kubernetes Azure detect service accounts forbidden failure access - Rule", "ESCU - Kubernetes Azure detect suspicious kubectl calls - Rule"] -mappings = {"kill_chain_phases": ["Lateral Movement"]} -investigative_searches = ["ESCU - Get Notable Info"] -support_searches = [] -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. - -[Kubernetes Sensitive Role Activity] -category = Cloud Security -creation_date = 2020-05-20 -modification_date = 2020-05-20 -id = 2574e6d9-7254-4751-8925-0447deeec8ew -version = 1 -reference = ["https://www.splunk.com/en_us/blog/security/approaching-kubernetes-security-detecting-kubernetes-scan-with-splunk.html"] -detection_searches = ["ESCU - Kubernetes Azure detect RBAC authorization by account - Rule", "ESCU - Kubernetes Azure detect most active service accounts by pod namespace - Rule", "ESCU - Kubernetes Azure detect sensitive role access - Rule"] -mappings = {"kill_chain_phases": ["Lateral Movement"]} -investigative_searches = ["ESCU - Get Notable Info"] -support_searches = [] -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 - -[Lateral Movement] -category = Adversary Tactics -creation_date = 2020-02-04 -modification_date = 2020-02-04 -id = 399d65dc-1f08-499b-a259-aad9051f38ad -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 - 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 9"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053", "T1075", "T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -support_searches = [] -data_models = ["Endpoint", "Network_Traffic"] -providing_technologies = none -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.\ -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. - -[Malicious PowerShell] -category = Adversary Tactics -creation_date = 2017-08-23 -modification_date = 2017-08-23 -id = 2c8ff66e-0b57-42af-8ad7-912438a403fc -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 - 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"], "mitre_attack": ["T1064", "T1086"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -support_searches = [] -data_models = ["Endpoint"] -providing_technologies = none -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: \ -1. Country of origin\ -1. Responsible party\ -1. Fully qualified domain names associated with the external IP address\ -1. Registration of fully qualified domain names associated with external IP addressDetermining whether it is a dynamic domain frequently visited by others and/or how third parties categorize it can also help you answer some questions surrounding the attacker and details related to the external system. In addition, there are various sources--such as VirusTotal— that can provide some reputation information on the IP address or domain name, which can assist in determining whether the event is malicious. Finally, determining whether there are other events associated with the IP address may help connect data points or show other events that should be brought into scope.\ -Gathering data on the system of interest can sometimes help you quickly determine whether something suspicious is happening. Some of these items include finding out who else may have recently logged into the system, whether any unusual scheduled tasks exist, whether the system is communicating on suspicious ports, whether there are modifications to sensitive registry keys, and whether there are any known vulnerabilities on the system. This information can often highlight other activity commonly seen in attack scenarios or give more information about how the system may have been targeted.\ -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. - -[Monitor Backup Solution] -category = Best Practices -creation_date = 2017-09-12 -modification_date = 2017-09-12 -id = abe807c7-1eb6-4304-ac32-6e7aacdb891d -version = 1 -reference = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] -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 Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - All backup logs for host", "ESCU - Get Risk Modifiers For User"] -support_searches = ["ESCU - Monitor Unsuccessful Backups", "ESCU - Monitor Successful 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. - -[Monitor for Unauthorized Software] -category = Best Practices -creation_date = 2017-09-15 -modification_date = 2017-09-15 -id = 8892a655-6205-43f7-abba-06460e38c8ae -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"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Update Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -support_searches = ["ESCU - Add Prohibited Processes to Enterprise Security"] -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. - -[Monitor for Updates] -category = Best Practices -creation_date = 2017-09-15 -modification_date = 2017-09-15 -id = 9ef8d677-7b52-4213-a038-99cfc7acc2d8 -version = 1 -reference = ["https://learn.cisecurity.org/20-controls-download"] -detection_searches = ["ESCU - No Windows Updates in a time frame - Rule"] -mappings = {"cis20": ["CIS 18"], "nist": ["PR.MA"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] -support_searches = [] -data_models = ["Updates"] -providing_technologies = none -description = Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches. -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. - -[Netsh Abuse] -category = Abuse -creation_date = 2017-01-05 -modification_date = 2017-01-05 -id = 2b1800dd-92f9-47ec-a981-fdf1351e5f65 -version = 1 -reference = ["https://technet.microsoft.com/library/bb490939.aspx", "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": ["T1059", "T1089"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -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`. - -[Orangeworm Attack Group] -category = Malware -creation_date = 2020-01-22 -modification_date = 2020-01-22 -id = bb9f5ed2-916e-4364-bb6d-97c370efcf52 -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 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1064", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -support_searches = ["ESCU - Previously Seen Running Windows Services", "ESCU - Previously seen command line arguments"] -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. -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.\ -Although the group's motivation is unknown, its goal may be stealing patient information to sell on the black market. Another possible explanation is corporate espionage. \ -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. - -[Phishing Payloads] -category = Adversary Tactics -creation_date = 2019-04-29 -modification_date = 2019-04-29 -id = 57226b40-94f3-4ce5-b101-a75f67759c27 -version = 1 -reference = ["https://www.fireeye.com/blog/threat-research/2019/04/spear-phishing-campaign-targets-ukraine-government.html"] -detection_searches = ["ESCU - Detect Oulook exe writing a zip file - Rule", "ESCU - Suspicious LNK file launching a process - Rule"] -mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1193"], "nist": ["ID.AM", "PR.DS"]} -investigative_searches = ["ESCU - Get Parent Process Info"] -support_searches = [] -data_models = [] -providing_technologies = none -description = Detect signs of malicious payloads that may indicate that your environment has been breached via a phishing attack. -narrative = Despite its simplicity, phishing remains the most pervasive and dangerous cyberthreat. In fact, research shows that as many as [91% of all successful attacks](https://digitalguardian.com/blog/91-percent-cyber-attacks-start-phishing-email-heres-how-protect-against-phishing) are initiated via a phishing email. \ -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. Worse, because its success relies on the gullibility of humans, it's impossible to completely "automate" it out of your environment. However, you can use ES and ESCU to detect and investigate potentially malicious payloads injected into your environment subsequent to a phishing attack. \ -hile any kind of file may contain a malicious payload, some are more likely to be perceived as benign (and thus more often escape notice) by the average victim—especially when the attacker sends an email that seems to be from one of their contacts. An example is Microsoft Office files. Most corporate users are familiar with documents with the following suffixes: .doc/.docx (MS Word), .xls/.xlsx (MS Excel), and .ppt/.pptx (MS PowerPoint), so they may click without a second thought, slashing a hole in their organizations' security. \ -Following is a typical series of events, according to an [article by Trend Micro](https://blog.trendmicro.com/trendlabs-security-intelligence/rising-trend-attackers-using-lnk-files-download-malware/):\ -1. Attacker sends a phishing email. Recipient downloads the attached file, which is typically a .docx or .zip file with an embedded .lnk file\ -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. - -[Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns] -category = Adversary Tactics -creation_date = 2020-01-22 -modification_date = 2020-01-22 -id = 988C59C5-0A1C-45B6-A555-0C62276E327E -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", "T1064", "T1086", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -support_searches = ["ESCU - Baseline of Command Line Length - MLTK", "ESCU - Previously seen command line arguments"] -data_models = ["Endpoint"] -providing_technologies = none -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.\ -The MUDCARP techniques include the use of the compressed-folders module from Microsoft, zipfldr.dll, with RouteTheCall export to run the malicious process or command. After a successful reboot, the malware is made persistent by a manipulating `[HKEY_CURRENT_USER\SOFTWARE\Microsoft\Windows\CurrentVersion\Run]'help'='c:\\windows\\system32\\rundll32.exe c:\\windows\\system32\\zipfldr.dll,RouteTheCall c:\\programdata\\winapp.exe'`. Though this technique is not exclusive to MUDCARP, it has been spotted in the group's arsenal of advanced techniques seen in the wild.\ -This Analytic Story searches for evidence of tactics, techniques, and procedures (TTPs) that allow for the use of a endpoint detection-and-response (EDR) bypass technique to mask the true parent of a malicious process. It can also be set as a registry key for further sandbox evasion and to allow the malware to launch only after reboot.\ -If behavioral searches included in this story yield positive hits, iDefense recommends conducting IOC searches for the following:\ -\ -1. www.chemscalere[.]com\ -1. chemscalere[.]com\ -1. about.chemscalere[.]com\ -1. autoconfig.chemscalere[.]com\ -1. autodiscover.chemscalere[.]com\ -1. catalog.chemscalere[.]com\ -1. cpanel.chemscalere[.]com\ -1. db.chemscalere[.]com\ -1. ftp.chemscalere[.]com\ -1. mail.chemscalere[.]com\ -1. news.chemscalere[.]com\ -1. update.chemscalere[.]com\ -1. webmail.chemscalere[.]com\ -1. www.candlelightparty[.]org\ -1. candlelightparty[.]org\ -1. newapp.freshasianews[.]comIn addition, iDefense also recommends that organizations review their environments for activity related to the following hashes:\ -\ -1. cd195ee448a3657b5c2c2d13e9c7a2e2\ -1. b43ad826fe6928245d3c02b648296b43\ -1. 889a9b52566448231f112a5ce9b5dfaf\ -1. b8ec65dab97cdef3cd256cc4753f0c54\ -1. 04d83cd3813698de28cfbba326d7647c - -[Prohibited Traffic Allowed or Protocol Mismatch] -category = Best Practices -creation_date = 2017-09-11 -modification_date = 2017-09-11 -id = 6d13121c-90f3-446d-8ac3-27efbbc65218 -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 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "PR.AC"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -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. - -[Ransomware] -category = Malware -creation_date = 2020-02-04 -modification_date = 2020-02-04 -id = cf309d0d-d4aa-4fbb-963d-1e79febd3756 -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 - 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 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 - 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"], "mitre_attack": ["T1036", "T1043", "T1047", "T1048", "T1053", "T1070", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Backup Logs For Endpoint"] -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. - -[Router and Infrastructure Security] -category = Best Practices -creation_date = 2017-09-12 -modification_date = 2017-09-12 -id = 91c676cf-0b23-438d-abee-f6335e177e77 -version = 1 -reference = ["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"] -detection_searches = ["ESCU - Detect New Login Attempts to Routers - Rule"] -mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] -support_searches = [] -data_models = ["Authentication"] -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. - -[SQL Injection] -category = Adversary Tactics -creation_date = 2017-09-19 -modification_date = 2017-09-19 -id = 4f6632f5-449c-4686-80df-57625f59bab3 -version = 1 -reference = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] -detection_searches = ["ESCU - SQL Injection with Long URLs - Rule"] -mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable Info"] -support_searches = [] -data_models = ["Web"] -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. - -[SamSam Ransomware] -category = Malware -creation_date = 2018-12-13 -modification_date = 2018-12-13 -id = c4b89506-fbcf-4cb7-bfd6-527e54789604 -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": ["T1059", "T1076", "T1082"], "nist": ["DE.AE", "DE.CM", "ID.AM", "ID.RA", "PR.AC", "PR.DS", "PR.IP", "PR.MA", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Update Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Backup Logs For Endpoint"] -support_searches = ["ESCU - Add Prohibited Processes to Enterprise Security"] -data_models = ["Endpoint", "Network_Traffic", "Web"] -providing_technologies = none -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.\ -SamSam attacks are different beasts. They have become progressively more targeted and skillful than typical ransomware attacks. First, malicious actors break into a victim's network, surveil it, then run the malware manually. The attacks are tailored to cause maximum damage and the threat actors usually demand amounts in the tens of thousands of dollars.\ -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. - -[Spectre And Meltdown Vulnerabilities] -category = Vulnerability -creation_date = 2018-01-08 -modification_date = 2018-01-08 -id = 6d3306f6-bb2b-4219-8609-8efad64032f2 -version = 1 -reference = ["https://meltdownattack.com/"] -detection_searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule"] -mappings = {"cis20": ["CIS 4"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] -support_searches = ["ESCU - Systems Ready for Spectre-Meltdown Windows Patch"] -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. - -[Splunk Enterprise Vulnerability] -category = Vulnerability -creation_date = 2017-09-19 -modification_date = 2017-09-19 -id = 4e692b96-de2d-4bd1-9105-37e2368a8db1 -version = 1 -reference = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] -detection_searches = ["ESCU - Open Redirect in Splunk Web - Rule"] -mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] -support_searches = [] -data_models = [] -providing_technologies = none -description = Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains. -narrative = This Analytic Story is associated with CVE-2016-4859, an open-redirect vulnerability in the following versions of Splunk Enterprise:\ -\ -1. Splunk Enterprise 6.4.x, prior to 6.4.3\ -1. Splunk Enterprise 6.3.x, prior to 6.3.6\ -1. Splunk Enterprise 6.2.x, prior to 6.2.10\ -1. Splunk Enterprise 6.1.x, prior to 6.1.11\ -1. Splunk Enterprise 6.0.x, prior to 6.0.12\ -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. - -[Splunk Enterprise Vulnerability CVE-2018-11409] -category = Vulnerability -creation_date = 2018-06-14 -modification_date = 2018-06-14 -id = 1fc34cbc-34e9-43ba-87ab-6811c9e95400 -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"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From src ip"] -support_searches = [] -data_models = [] -providing_technologies = none -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.\ -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. - -[Suspicious AWS EC2 Activities] -category = Cloud Security -creation_date = 2018-02-09 -modification_date = 2018-02-09 -id = 2e8948a5-5239-406b-b56b-6c50f1268af3 -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"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get EC2 Launch Details", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] -support_searches = ["ESCU - Previously Seen AWS Regions", "ESCU - Previously Seen EC2 Launches By User", "ESCU - Baseline of Excessive AWS Instances Terminated by User - MLTK", "ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK"] -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. - -[Suspicious AWS Login Activities] -category = Cloud Security -creation_date = 2019-05-01 -modification_date = 2019-05-01 -id = 2e8948a5-5239-406b-b56b-6c59f1268af3 -version = 1 -reference = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] -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"], "nist": ["DE.AE", "DE.DP"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By ARN"] -support_searches = ["ESCU - Update previously seen users in CloudTrail", "ESCU - Previously seen users in CloudTrail"] -data_models = [] -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. - -[Suspicious AWS S3 Activities] -category = Cloud Security -creation_date = 2018-07-24 -modification_date = 2018-07-24 -id = 2e8948a5-5239-406b-b56b-6c50w3168af3 -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 - 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"], "nist": ["DE.CM", "DE.DP", "PR.AC", "PR.DS"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get Notable History", "ESCU - Investigate AWS activities via region name", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] -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. - -[Suspicious AWS Traffic] -category = Cloud Security -creation_date = 2018-05-07 -modification_date = 2018-05-07 -id = 2e8948a5-5239-406b-b56b-6c50f2168af3 -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": ["Command and Control"], "nist": ["PR.AC"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network ACL Details from ID", "ESCU - Get User Information from Identity Table"] -support_searches = ["ESCU - Baseline of blocked outbound traffic from AWS"] -data_models = [] -providing_technologies = none -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.\ - 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. - -[Suspicious Command-Line Executions] -category = Adversary Tactics -creation_date = 2020-02-03 -modification_date = 2020-02-03 -id = f4368ddf-d59f-4192-84f6-778ac5a3ffc7 -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", "T1059", "T1064"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -support_searches = ["ESCU - Baseline of Command Line Length - MLTK", "ESCU - Previously seen command line arguments"] -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. - -[Suspicious DNS Traffic] -category = Adversary Tactics -creation_date = 2017-09-18 -modification_date = 2017-09-18 -id = 3c3835c0-255d-4f9e-ab84-e29ec9ec9b56 -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": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -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. - -[Suspicious Emails] -category = Adversary Tactics -creation_date = 2020-01-27 -modification_date = 2020-01-27 -id = 2b1800dd-92f9-47ec-a981-fdf1351e5d55 -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"], "nist": ["DE.AE", "PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get User Information from Identity Table", "ESCU - Get Email Info"] -support_searches = ["ESCU - DNSTwist Domain Names"] -data_models = ["Email", "UEBA"] -providing_technologies = none -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: \ -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. - -[Suspicious MSHTA Activity] -category = Adversary Tactics -creation_date = 2020-02-03 -modification_date = 2020-02-03 -id = 2b1800dd-92f9-47dd-a981-fdf13w1q5d55 -version = 1 -reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] -detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule"] -mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1059", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -support_searches = ["ESCU - Baseline of Command Line Length - MLTK", "ESCU - Previously seen command line arguments"] -data_models = ["Endpoint"] -providing_technologies = none -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 white-listing solutions via the mshta.exe process, which executes Microsoft HTML applications with the .hta suffix. In these cases, attackers use the trusted Windows utility to eproxy execution of malicious files, whether an .hta application, javascript, or VBScript.\ -One example of a notable mshta.exe attack was the Kovter malware (https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5) that was implicated in ransomware and click-fraud attacks. Kovter utilized .hta to execute a series of javascript commands, each progressively more dangerous. According to the Mitre Parternship Network (https://attack.mitre.org/wiki/Technique/T1170), FIN7 has leveraged mshta.exe, as has the MuddyWater group, who used it to execute its POWERSTATS payload (which then used the utility to execute additional payloads).\ -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. - -[Suspicious Okta Activity] -category = Adversary Tactics -creation_date = 2020-04-02 -modification_date = 2020-04-02 -id = 9cbd34af-8f39-4476-a423-bacd126c750b -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 Credentails 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"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by IP Address"] -support_searches = [] -data_models = [] -providing_technologies = none -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. \ -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. - -[Suspicious WMI Use] -category = Adversary Tactics -creation_date = 2018-10-23 -modification_date = 2018-10-23 -id = c8ddc5be-69bc-4202-b3ab-4010b27d7ad5 -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", "T1084"], "nist": ["PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -support_searches = [] -data_models = ["Endpoint"] -providing_technologies = none -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.\ -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. - -[Suspicious Windows Registry Activities] -category = Adversary Tactics -creation_date = 2018-05-31 -modification_date = 2018-05-31 -id = 2b1800dd-92f9-47dd-a981-fdf1351e5d55 -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": ["T1015", "T1042", "T1103", "T1112", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -support_searches = [] -data_models = ["Endpoint"] -providing_technologies = none -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.\ - The searches in this story are designed to help you detect behaviors associated with manipulation of the Windows registry. - -[Unusual AWS EC2 Modifications] -category = Cloud Security -creation_date = 2018-04-09 -modification_date = 2018-04-09 -id = 73de57ef-0dfc-411f-b1e7-fa24428aeae0 -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"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN"] -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. - -[Unusual Processes] -category = Malware -creation_date = 2020-02-04 -modification_date = 2020-02-04 -id = f4368e3f-d59f-4192-84f6-748ac5a3ddb6 -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": ["T1015", "T1036", "T1085"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -support_searches = ["ESCU - Baseline of Command Line Length - MLTK"] -data_models = ["Endpoint"] -providing_technologies = none -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.\ -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. - -[Use of Cleartext Protocols] -category = Best Practices -creation_date = 2017-09-15 -modification_date = 2017-09-15 -id = 826e6431-aeef-41b4-9fc0-6d0985d65a21 -version = 1 -reference = ["https://www.monkey.org/~dugsong/dsniff/"] -detection_searches = ["ESCU - Protocols passing authentication in cleartext - Rule"] -mappings = {"cis20": ["CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] -support_searches = [] -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. - -[Web Fraud Detection] -category = Abuse -creation_date = 2018-10-08 -modification_date = 2018-10-08 -id = 31337aaa-bc22-4752-b599-ef112dq1dq7a -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 Web Session Information via session id", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Notable Info"] -support_searches = [] -data_models = [] -providing_technologies = none -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.\ -hen developing a strategy for preventing fraud in your environment, its important to look across all of your web services for evidence that attackers are abusing enterprise resources to enumerate systems, harvest data for secondary fraudulent activity, or abuse terms of service.This Analytic Story looks for evidence of common Internet attack techniques that could be indicative of web fraud in your environmentincluding account harvesting, anomalous user clickspeed, and password sharing across accounts, to name just a few.\ -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. - -[Windows Defense Evasion Tactics] -category = Adversary Tactics -creation_date = 2018-05-31 -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 - 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"] -mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1089", "T1112"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -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. - -[Windows File Extension and Association Abuse] -category = Malware -creation_date = 2018-01-26 -modification_date = 2018-01-26 -id = 30552a76-ac78-48e4-b3c0-de4e34e9563d -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": ["T1042"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -support_searches = [] -data_models = ["Endpoint"] -providing_technologies = none -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. \ - 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. - -[Windows Log Manipulation] -category = Adversary Tactics -creation_date = 2017-09-12 -modification_date = 2017-09-12 -id = b6db2c60-a281-48b4-95f1-2cd99ed56835 -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"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -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). - -[Windows Persistence Techniques] -category = Adversary Tactics -creation_date = 2018-05-31 -modification_date = 2018-05-31 -id = 30874d4f-20a1-488f-85ec-5d52ef74e3f9 -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 - 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"] -mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1053", "T1089", "T1103", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -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. - -[Windows Privilege Escalation] -category = Adversary Tactics -creation_date = 2020-02-04 -modification_date = 2020-02-04 -id = 644e22d3-598a-429c-a007-16fdb802cae5 -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 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1015", "T1068"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -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. - -[Windows Service Abuse] -category = Malware -creation_date = 2017-11-02 -modification_date = 2017-11-02 -id = 6dbd810e-f66d-414b-8dfc-e46de55cbfe2 -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 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -support_searches = ["ESCU - Previously Seen Running Windows Services"] -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. - -#### END STORIES #### \ No newline at end of file diff --git a/package/default/es_investigations.conf b/package/default/es_investigations.conf deleted file mode 100644 index a1bc55fb1c..0000000000 --- a/package/default/es_investigations.conf +++ /dev/null @@ -1,1501 +0,0 @@ - -[panel_group://workbench_panel_group_aws_cross_account_activity] -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_aws_investigate_user_activities_by_source_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_aws_investigate_user_activities_by_accesskeyid"] - -[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_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_ec2_launch_details", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table"] - -[panel_group://workbench_panel_group_aws_network_acl_activity] -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_risk_modifiers_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_info", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_get_user_information_from_identity_table"] - -[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_region", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_all_aws_activity_from_city", "panel://workbench_panel_get_all_aws_activity_from_country"] - -[panel_group://workbench_panel_group_aws_user_monitoring] -label = AWS User Monitoring -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. -disabled = 0 -panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_aws_user_activities_by_user_field", "panel://workbench_panel_get_notable_info"] - -[panel_group://workbench_panel_group_account_monitoring_and_controls] -label = Account Monitoring and Controls -description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. -disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_logon_rights_modifications_for_user", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_logon_rights_modifications_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table"] - -[panel_group://workbench_panel_group_apache_struts_vulnerability] -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_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_posts_from_src", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_suspicious_strings_in_http_header"] - -[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", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_first_occurrence_and_last_occurrence_of_a_mac_address"] - -[panel_group://workbench_panel_group_brand_monitoring] -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_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_email_info"] - -[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_cloud_compute_instance_activities", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_ec2_launch_details", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_investigate_user_activities_in_single_cloud_region", "panel://workbench_panel_investigate_user_activities_in_all_cloud_regions", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table"] - -[panel_group://workbench_panel_group_coldroot_macos_rat] -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_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_web_activity_from_src_ip", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_network_traffic_from_src_ip", "panel://workbench_panel_get_user_information_from_identity_table"] - -[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_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] - -[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_risk_modifiers_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_info", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] - -[panel_group://workbench_panel_group_common_phishing_frameworks] -label = Common Phishing Frameworks -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. -disabled = 0 -panels = ["panel://workbench_panel_get_certificate_logs_for_a_domain"] - -[panel_group://workbench_panel_group_container_implantation_monitoring_and_investigation] -label = Container Implantation Monitoring and Investigation -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. -disabled = 0 -panels = ["panel://workbench_panel_investigate_aws_ecr_container_listing_activity"] - -[panel_group://workbench_panel_group_credential_dumping] -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_failed_logins_for_multiple_destinations", "panel://workbench_panel_investigate_pass_the_hash_attempts", "panel://workbench_panel_investigate_previous_unseen_user", "panel://workbench_panel_investigate_pass_the_ticket_attempts"] - -[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_risk_modifiers_for_endpoint", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_file_activity", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_registry_activity", "panel://workbench_panel_get_parent_process_info"] - -[panel_group://workbench_panel_group_dns_amplification_attacks] -label = DNS Amplification Attacks -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. -disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info"] - -[panel_group://workbench_panel_group_dns_hijacking] -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"] - -[panel_group://workbench_panel_group_data_protection] -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_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_user_information_from_identity_table"] - -[panel_group://workbench_panel_group_disabling_security_tools] -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_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] - -[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 blacklists. -disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_web_activity_from_src_ip", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_user_information_from_identity_table"] - -[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_risk_modifiers_for_endpoint", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] - -[panel_group://workbench_panel_group_hidden_cobra_malware] -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_risk_modifiers_for_endpoint", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] - -[panel_group://workbench_panel_group_host_redirection] -label = Host Redirection -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. -disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table"] - -[panel_group://workbench_panel_group_jboss_vulnerability] -label = JBoss Vulnerability -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. -disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info"] - -[panel_group://workbench_panel_group_kubernetes_scanning_activity] -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_risk_modifiers_for_endpoint", "panel://workbench_panel_gcp_kubernetes_activity_by_src_ip", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_amazon_eks_kubernetes_activity_by_src_ip"] - -[panel_group://workbench_panel_group_kubernetes_sensitive_object_access_activity] -label = Kubernetes Sensitive Object Access Activity -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. -disabled = 0 -panels = ["panel://workbench_panel_get_notable_info"] - -[panel_group://workbench_panel_group_kubernetes_sensitive_role_activity] -label = Kubernetes Sensitive Role Activity -description = This story addresses detection and response around Sensitive Role usage within a Kubernetes clusters against cluster resources and namespaces. -disabled = 0 -panels = ["panel://workbench_panel_get_notable_info"] - -[panel_group://workbench_panel_group_lateral_movement] -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_risk_modifiers_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] - -[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_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] - -[panel_group://workbench_panel_group_monitor_backup_solution] -label = Monitor Backup Solution -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. -disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_all_backup_logs_for_host", "panel://workbench_panel_get_risk_modifiers_for_user"] - -[panel_group://workbench_panel_group_monitor_for_unauthorized_software] -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_risk_modifiers_for_endpoint", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] - -[panel_group://workbench_panel_group_monitor_for_updates] -label = Monitor for Updates -description = Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches. -disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info"] - -[panel_group://workbench_panel_group_netsh_abuse] -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_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] - -[panel_group://workbench_panel_group_orangeworm_attack_group] -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_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] - -[panel_group://workbench_panel_group_phishing_payloads] -label = Phishing Payloads -description = Detect signs of malicious payloads that may indicate that your environment has been breached via a phishing attack. -disabled = 0 -panels = ["panel://workbench_panel_get_parent_process_info"] - -[panel_group://workbench_panel_group_possible_backdoor_activity_associated_with_mudcarp_espionage_campaigns] -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_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] - -[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_risk_modifiers_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] - -[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_risk_modifiers_for_endpoint", "panel://workbench_panel_get_sysmon_wmi_activity_for_host", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_backup_logs_for_endpoint"] - -[panel_group://workbench_panel_group_router_and_infrastructure_security] -label = Router and Infrastructure Security -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. -disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table"] - -[panel_group://workbench_panel_group_sql_injection] -label = SQL Injection -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. -disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_info"] - -[panel_group://workbench_panel_group_samsam_ransomware] -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_risk_modifiers_for_endpoint", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_backup_logs_for_endpoint"] - -[panel_group://workbench_panel_group_spectre_and_meltdown_vulnerabilities] -label = Spectre And Meltdown Vulnerabilities -description = Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. -disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table"] - -[panel_group://workbench_panel_group_splunk_enterprise_vulnerability] -label = Splunk Enterprise Vulnerability -description = Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains. -disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info"] - -[panel_group://workbench_panel_group_splunk_enterprise_vulnerability_cve_2018_11409] -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_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_network_traffic_from_src_ip", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_investigate_web_activity_from_src_ip"] - -[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_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_ec2_launch_details", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table"] - -[panel_group://workbench_panel_group_suspicious_aws_login_activities] -label = Suspicious AWS Login Activities -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. -disabled = 0 -panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn"] - -[panel_group://workbench_panel_group_suspicious_aws_s3_activities] -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_aws_investigate_user_activities_by_arn", "panel://workbench_panel_aws_s3_bucket_details_via_bucketname", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table"] - -[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_risk_modifiers_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_info", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_get_user_information_from_identity_table"] - -[panel_group://workbench_panel_group_suspicious_command_line_executions] -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_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] - -[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_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] - -[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_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_email_info"] - -[panel_group://workbench_panel_group_suspicious_mshta_activity] -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_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] - -[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_okta_activity_by_app", "panel://workbench_panel_investigate_user_activities_in_okta", "panel://workbench_panel_investigate_okta_activity_by_ip_address"] - -[panel_group://workbench_panel_group_suspicious_wmi_use] -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_risk_modifiers_for_endpoint", "panel://workbench_panel_get_sysmon_wmi_activity_for_host", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] - -[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_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] - -[panel_group://workbench_panel_group_unusual_aws_ec2_modifications] -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_ec2_instance_details_by_instanceid", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_aws_investigate_user_activities_by_arn"] - -[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_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] - -[panel_group://workbench_panel_group_use_of_cleartext_protocols] -label = Use of Cleartext Protocols -description = Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. -disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table"] - -[panel_group://workbench_panel_group_web_fraud_detection] -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_web_session_information_via_session_id", "panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info"] - -[panel_group://workbench_panel_group_windows_defense_evasion_tactics] -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_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] - -[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_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] - -[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_risk_modifiers_for_endpoint", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] - -[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_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] - -[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_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] - -[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_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info"] - - - -[panel://workbench_panel_aws_investigate_user_activities_by_arn] -label = AWS Investigate User Activities By ARN -description = This search lists all the logged CloudTrail activities by a specific user ARN 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 all the user's identity information. -disabled = 0 -tokens = {\ - "user": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "identity",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_aws_investigate_user_activities_by_accesskeyid] -label = AWS Investigate User Activities By AccessKeyId -description = This search retrieves the times, ARN, source IPs, AWS regions, event names, and the result of the event for specific credentials. -disabled = 0 -tokens = {\ - "accessKeyId": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_aws_investigate_user_activities_by_source_user] -label = AWS Investigate User Activities By Source User -description = This search retrieves the times, ARN, source IPs, AWS regions, event names, and the result of the event for specific ARNs. -disabled = 0 -tokens = {\ - "src_user": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_aws_network_acl_details_from_id] -label = AWS Network ACL Details from ID -description = This search queries AWS description logs and returns all the information about a specific network ACL via network ACL ID -disabled = 0 -tokens = {\ - "networkAclId": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_aws_network_interface_details_via_resourceid] -label = AWS Network Interface details via resourceId -description = This search queries AWS configuration logs and returns the information about a specific network interface via network interface ID. The information will include the ARN of the network interface, its relationships with other AWS resources, the public and the private IP associated with the network interface. -disabled = 0 -tokens = {\ - "resourceId": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_aws_s3_bucket_details_via_bucketname] -label = AWS S3 Bucket details via bucketName -description = This search queries AWS configuration logs and returns the information about a specific S3 bucket. The information returned includes the time the S3 bucket was created, the resource ID, the region it belongs to, the value of action performed, AWS account ID, and configuration values of the access-control lists associated with the bucket. -disabled = 0 -tokens = {\ - "bucketName": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_all_backup_logs_for_host] -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 ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_amazon_eks_kubernetes_activity_by_src_ip] -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 -disabled = 0 -tokens = {\ - "src_ip": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_gcp_kubernetes_activity_by_src_ip] -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_user": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_get_all_aws_activity_from_city] -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. -disabled = 0 -tokens = {\ - "City": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_get_all_aws_activity_from_country] -label = Get All AWS Activity From Country -description = This search retrieves all the activity from a specific country and will create a table containing the time, country, 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. -disabled = 0 -tokens = {\ - "Country": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_get_all_aws_activity_from_ip_address] -label = Get All AWS Activity From IP Address -description = This search retrieves all the activity from a specific IP address and will create a table containing the time, ARN, username, the type of user, the IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. -disabled = 0 -tokens = {\ - "src_ip": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_get_all_aws_activity_from_region] -label = Get All AWS Activity From Region -description = This search retrieves all the activity from a specific geographic region and will create a table containing the time, geographic region, 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. -disabled = 0 -tokens = {\ - "Region": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_get_authentication_logs_for_endpoint] -label = Get Authentication Logs For Endpoint -description = This search returns all users that have attempted to access a particular endpoint. -disabled = 0 -tokens = {\ - "dest": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_get_backup_logs_for_endpoint] -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 ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_get_certificate_logs_for_a_domain] -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 ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_get_dns_server_history_for_a_host] -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 ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_get_dns_traffic_ratio] -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 ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - },\ - "dest_ip": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_get_ec2_instance_details_by_instanceid] -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 -disabled = 0 -tokens = {\ - "instanceId": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_get_ec2_launch_details] -label = Get EC2 Launch Details -description = This search returns some of the launch details for a EC2 instance. -disabled = 0 -tokens = {\ - "dest": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_get_email_info] -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 ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_get_emails_from_specific_sender] -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 ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_get_first_occurrence_and_last_occurrence_of_a_mac_address] -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 ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_get_history_of_email_sources] -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 ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_get_logon_rights_modifications_for_endpoint] -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 ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_get_logon_rights_modifications_for_user] -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 ",\ - "valueType": "primitive",\ - "value": "identity",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_get_notable_history] -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 ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_get_notable_info] -label = Get Notable Info -description = This search queries the notable index to retrieve detailed information captured within the notable. Every notable has a unique ID associated with it, which is used to point us directly to the notable event under investigation. -disabled = 0 -tokens = {\ - "event_id": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_get_outbound_emails_to_hidden_cobra_threat_actors] -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 ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - },\ - "recipient": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_get_parent_process_info] -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 = {\ - "process_name": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - },\ - "dest": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_get_process_file_activity] -label = Get Process File Activity -description = This search returns the file activity for a specific process on a specific endpoint -disabled = 0 -tokens = {\ - "process_id": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - },\ - "dest": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_get_process_info] -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 ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - },\ - "dest": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_get_process_information_for_port_activity] -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 ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - },\ - "dest": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_get_process_registry_activity] -label = Get Process Registry Activity -description = This search returns the registry activity for a specific process on a specific endpoint -disabled = 0 -tokens = {\ - "process_id": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - },\ - "dest": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_get_process_responsible_for_the_dns_traffic] -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 ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_get_registry_activities] -label = Get Registry Activities -description = This search queries the Endpoint Datamodel to give you details of the latest registry values for a specific destination computer. -disabled = 0 -tokens = {\ - "dest": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_get_risk_modifiers_for_endpoint] -label = Get Risk Modifiers For Endpoint -description = For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk\_scores, names of the correlation searches that contributed to create a risk score for a specific endpoint(machine\_name) -disabled = 0 -tokens = {\ - "dest": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_get_risk_modifiers_for_user] -label = Get Risk Modifiers For User -description = For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk_scores, names of the correlation searches that contributed to create a risk score for a specific user -disabled = 0 -tokens = {\ - "user": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "identity",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_get_sysmon_wmi_activity_for_host] -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 ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - },\ - "dest": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_get_update_logs_for_endpoint] -label = Get Update Logs For Endpoint -description = This search will tell you give you the update logs for a specific endpoint for the last week. -disabled = 0 -tokens = {\ - "dest": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_get_user_information_from_identity_table] -label = Get User Information from Identity Table -description = Gather more information about the user identified in the Notable Event. -disabled = 0 -tokens = {\ - "user": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "identity",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_get_vulnerability_logs_for_endpoint] -label = Get Vulnerability Logs For Endpoint -description = This search will show you any vulnerabilities noted for a specific endpoint for the last week. -disabled = 0 -tokens = {\ - "dest": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_get_web_session_information_via_session_id] -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 ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_investigate_aws_ecr_container_listing_activity] -label = Investigate AWS ECR container listing activity -description = This search lists all the users performing a list image operation on AWS Elastic Container Registry. Listing source user, image id, source IP, user type, http user agent. This search also gives counts of unique user agents per listing source. -disabled = 0 -tokens = {\ - "Compute.event_name": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_investigate_aws_user_activities_by_user_field] -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. -disabled = 0 -tokens = {\ - "user": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "identity",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_investigate_aws_activities_via_region_name] -label = Investigate AWS activities via region name -description = This search lists all the user activities logged by CloudTrail for a specific region in question and will create a table of the values of parameters requested, the type of the event and the response from the AWS API by each user -disabled = 0 -tokens = {\ - "awsRegion": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_investigate_cloud_compute_instance_activities] -label = Investigate Cloud Compute Instance Activities -description = This search returns a logs of events that operated on the compute instance. -disabled = 0 -tokens = {\ - "dest": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_investigate_failed_logins_for_multiple_destinations] -label = Investigate Failed Logins for Multiple Destinations -description = This search returns failed logins to multiple destinations by user. -disabled = 0 -tokens = {\ - "dest": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_investigate_network_traffic_from_src_ip] -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 ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_investigate_okta_activity_by_ip_address] -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 ",\ - "valueType": "primitive",\ - "value": "identity",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_investigate_okta_activity_by_app] -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 ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_investigate_pass_the_hash_attempts] -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 ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_investigate_pass_the_ticket_attempts] -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 ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_investigate_previous_unseen_user] -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 ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_investigate_successful_remote_desktop_authentications] -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 ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_investigate_suspicious_strings_in_http_header] -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 ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - },\ - "dest_ip": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_investigate_user_activities_in_all_cloud_regions] -label = Investigate User Activities In All Cloud Regions -description = This search lists all the logged cloud infrastructure activities by a specific cloud user -disabled = 0 -tokens = {\ - "region": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - },\ - "src_user": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_investigate_user_activities_in_okta] -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 ",\ - "valueType": "primitive",\ - "value": "identity",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_investigate_user_activities_in_single_cloud_region] -label = Investigate User Activities In Single Cloud Region -description = This search lists all the logged cloud infrastructure activities by a specific cloud user in a specific cloud region -disabled = 0 -tokens = {\ - "region": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - },\ - "src_user": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_investigate_web_activity_from_host] -label = Investigate Web Activity From Host -description = This search allows you to find all the web activity from a specific host. During an investigation, it is important to profile web activity to characterize user or host activity. -disabled = 0 -tokens = {\ - "dest": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_investigate_web_activity_from_src_ip] -label = Investigate Web Activity From src ip -description = This search searches for all web activity from a specific host. During an investigation, it is important to profile web activity to characterize user or host activity. -disabled = 0 -tokens = {\ - "src_ip": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_investigate_web_posts_from_src] -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 ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - -[panel://workbench_panel_process_chain_analysis] -label = Process Chain Analysis -description = Analyze the Process Chain and identify the malicious file. By analyzing the parent process guid and searching for the process guid, the spawning process chain can be identified. -disabled = 0 -tokens = {\ - "process_guid": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ -}\ - - diff --git a/package/default/macros.conf b/package/default/macros.conf deleted file mode 100644 index d2e824a56d..0000000000 --- a/package/default/macros.conf +++ /dev/null @@ -1,1033 +0,0 @@ -############# -# Automatically generated by generator.py in splunk/security-content -# On Date: 2020-06-03T20:28:01 UTC -# Author: Splunk Security Research -# Contact: research@splunk.com -############# - - -[aws_cloudwatchlogs_eks] -definition = sourcetype="aws:cloudwatchlogs:eks" -description = customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. - -[aws_s3_accesslogs] -definition = sourcetype=aws:s3:accesslogs -description = customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. - -[brand_abuse_dns] -definition = lookup update=true brandMonitoring_lookup domain as query OUTPUT domain_abuse | search domain_abuse=true -description = This macro limits the output to only domains that are in the brand monitoring lookup file - -[brand_abuse_email] -definition = lookup update=true brandMonitoring_lookup domain as src_user OUTPUT domain_abuse | search domain_abuse=true -description = This macro limits the output to only domains that are in the brand monitoring lookup file - -[brand_abuse_web] -definition = lookup update=true brandMonitoring_lookup domain as urls OUTPUT domain_abuse | search domain_abuse=true -description = This macro limits the output to only domains that are in the brand monitoring lookup file - -[clients_connecting_to_multiple_dns_servers_output_filter] -definition = search * -description = Use this macro to add additional filters for monitoring clients connecting to multiple dns servers - -[cloudtrail] -definition = sourcetype=aws:cloudtrail -description = customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. - -[cloudwatch_eks] -definition = sourcetype="aws:cloudwatchlogs:eks" -description = customer specific splunk configurations(eg- index, source, sourcetype) for AWS cloudwatch eks logs. Replace the macro definition with configurations for your Splunk Environmnent. - -[cloudwatch_vpc] -definition = sourcetype=aws:cloudwatchlogs:vpcflow -description = customer specific splunk configurations(eg- index, source, sourcetype) for AWS cloudwatch vpc logs. Replace the macro definition with configurations for your Splunk Environmnent. - -[cloudwatchlogs_vpcflow] -definition = sourcetype=aws:cloudwatchlogs:vpcflow -description = customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. - -[create_or_delete_windows_shares_filter] -definition = search * -description = Use this macro to add additional filter for create or delete windows shares - -[dynamic_dns_providers] -definition = lookup update=true dynamic_dns_providers_default dynamic_dns_domains as query OUTPUTNEW isDynDNS_default | lookup update=true dynamic_dns_providers_local dynamic_dns_domains as query OUTPUTNEW isDynDNS_local| eval isDynDNS = coalesce(isDynDNS_default, isDynDNS_local)|fields - isDynDNS_default, isDynDNS_local| search isDynDNS=True -description = This macro limits the output of the query field to dynamic dns domains. It looks up the domains in a file provided by Splunk and one intended to be updated by the end user. - -[dynamic_dns_web_traffic] -definition = lookup update=true dynamic_dns_providers_default dynamic_dns_domains as url OUTPUTNEW isDynDNS_default | lookup update=true dynamic_dns_providers_local dynamic_dns_domains as url OUTPUTNEW isDynDNS_local| eval isDynDNS = coalesce(isDynDNS_default, isDynDNS_local)|fields - isDynDNS_default, isDynDNS_local| search isDynDNS=True -description = This is a description - -[ec2_modification_api_calls] -definition = (eventName=AssociateAddress OR eventName=AssociateIamInstanceProfile OR eventName=AttachClassicLinkVpc OR eventName=AttachNetworkInterface OR eventName=AttachVolume OR eventName=BundleInstance OR eventName=DetachClassicLinkVpc OR eventName=DetachVolume OR eventName=GetConsoleOutput OR eventName=GetConsoleScreenshot OR eventName=ModifyInstanceAttribute OR eventName=ModifyInstancePlacement OR eventName=MonitorInstances OR eventName=RebootInstances OR eventName=ResetInstanceAttribute OR eventName=StartInstances OR eventName=StopInstances OR eventName=TerminateInstances OR eventName=UnmonitorInstances) -description = This is a list of AWS event names that have to do with modifying Amazon EC2 instances - -[evilginx_phishlets_0365] -definition = (query=login* AND query=www*) -description = This limits the query fields to domains that are associated with evilginx masquerading as Office 365 - -[evilginx_phishlets_amazon] -definition = (query=fls-na* AND query = www* AND query=images*) -description = This limits the query fields to domains that are associated with evilginx masquerading as Amazon - -[evilginx_phishlets_aws] -definition = (query=www* AND query=aws* AND query=console.aws* AND query=signin.aws* AND api-northeast-1.console.aws* AND query=fls-na* AND query=images-na*) -description = This limits the query fields to domains that are associated with evilginx masquerading as an AWS console - -[evilginx_phishlets_facebook] -definition = (query=www* AND query = m* AND query=static*) -description = This limits the query fields to domains that are associated with evilginx masquerading as FaceBook - -[evilginx_phishlets_github] -definition = (query=api* AND query = github*) -description = This limits the query fields to domains that are associated with evilginx masquerading as GitHub - -[evilginx_phishlets_google] -definition = (query=accounts* AND query=ssl* AND query=www*) -description = This limits the query fields to domains that are associated with evilginx masquerading as Google - -[evilginx_phishlets_outlook] -definition = (query=outlook* AND query=login* AND query=account*) -description = This limits the query fields to domains that are associated with evilginx masquerading as Outlook - -[filter_rare_process_whitelist] -definition = lookup update=true lookup_rare_process_whitelist_default process as process OUTPUTNEW whitelist | where whitelist="false" | lookup update=true lookup_rare_process_whitelist_local process as process OUTPUT whitelist | where whitelist="false" -description = This macro is intended to whitelist processes that have been definied as rare - -[google_gcp_pubnet_message] -definition = sourcetype="google:gcp:pubsub:message" -description = customer specific splunk configurations(eg- index, source, sourcetype) for Google GCP. Replace the macro definition with configurations for your Splunk Environmnent. - -[google_gcp_pubsub_message] -definition = sourcetype="google:gcp:pubsub:message" -description = customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. - -[is_windows_system_file] -definition = lookup update=true is_windows_system_file filename as process_name OUTPUT systemFile | search systemFile=true -description = This macro limits the output to process names that are in the Windows System directory - -[kubernetes_azure] -definition = sourcetype=mscs:storage:blob:json -description = customer specific splunk configurations(eg- index, source, sourcetype) for Kubernetes data from Azure. Replace the macro definition with configurations for your Splunk Environmnent. - -[kubernetes_azure_detect_most_active_service_accounts_by_pod_namespace_filter] -definition = search * -description = Use this macro to add additional filters - -[kubernetes_azure_detect_rbac_authorization_by_account_filter] -definition = search * -description = Use this macro to add additional filters - -[kubernetes_azure_detect_sensitive_object_access_filter] -definition = search * -description = Use this macro to add additional filters - -[kubernetes_azure_detect_sensitive_role_access_filter] -definition = search * -description = Use this macro to add additional filters - -[kubernetes_azure_detect_service_accounts_forbidden_failure_access_filter] -definition = search * -description = Use this macro to add additional filters - -[kubernetes_azure_detect_suspicious_kubectl_calls_filter] -definition = search * -description = Use this macro to add additional filters - -[kubernetes_azure_pod_scan_fingerprint_detection_filter] -definition = search * -description = Use this macro to add additional filters - -[kubernetes_azure_scan_fingerprint_filter] -definition = search * -description = Use this macro to add additional filters - -[netbackup] -definition = sourcetype="netbackup_logs" -description = customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. - -[network_acl_events] -definition = (eventName = CreateNetworkAcl OR eventName = CreateNetworkAclEntry OR eventName = DeleteNetworkAcl OR eventName = DeleteNetworkAclEntry OR eventName = ReplaceNetworkAclEntry OR eventName = ReplaceNetworkAclAssociation) -description = This is a list of AWS event names that are associated with Network ACLs - -[okta] -definition = eventtype=okta_log -description = customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. - -[previously_seen_cloud_compute_creations_by_user_search_window_begin_offset] -definition = -70m@m -description = Use this macro to determine how far into the past the window should be to determine if the user is new or not - -[previously_seen_cloud_compute_image_search_window_begin_offset] -definition = -70m@m -description = Use this macro to determine how far into the past the window should be to determine if the image is new or not - -[previously_seen_cloud_compute_instance_types_search_window_begin_offset] -definition = -70m@m -description = Use this macro to determine how far into the past the window should be to determine if the instance type is new or not - -[previously_seen_cloud_regions_search_window_begin_offset] -definition = -70m@m -description = Use this macro to determine how far into the past the window should be to determine if the region is new or not - -[prohibited_apps_launching_cmd] -definition = | inputlookup prohibited_apps_launching_cmd | rename prohibited_applications as parent_process_name | eval parent_process_name="*" . parent_process_name | table parent_process_name -description = This macro outputs a list of process that should not be the parent process of cmd.exe - -[prohibited_softwares] -definition = lookup interesting_processes_lookup app as process_name OUTPUT is_prohibited | search is_prohibited=True -description = This macro limits the output to process_names that have been marked as prohibited - -[ransomware_extensions] -definition = lookup update=true ransomware_extensions_lookup Extensions AS file_extension OUTPUT Name | search Name !=False -description = This macro limits the output to files that have extensions associated with ransomware - -[ransomware_notes] -definition = lookup ransomware_notes_lookup ransomware_notes as file_name OUTPUT status as "Known Ransomware Notes" | search "Known Ransomware Notes"=True -description = This macro limits the output to files that have been identified as a ransomware note - -[remove_valid_domains] -definition = eval domain=trim(domain,"*") | search NOT[| inputlookup domains] NOT[ |inputlookup cim_corporate_email_domain_lookup] NOT[inputlookup cim_corporate_web_domain_lookup] | eval domain="*"+domain+"*" -description = This macro removes valid domains from the output - -[s3_accesslogs] -definition = sourcetype=aws:s3:accesslogs -description = customer specific splunk configurations(eg- index, source, sourcetype) for AWS cloudwatch vpc logs. Replace the macro definition with configurations for your Splunk Environmnent. - -[security_content_ctime(1)] -args = field -definition = convert timeformat="%m/%d/%Y %H:%M:%S" ctime($field$) -description = convert epoch time to string - -[security_content_summariesonly] -definition = summariesonly=true allow_old_summaries=true -description = search data model's summaries only - -[security_group_api_calls] -definition = (eventName=AuthorizeSecurityGroupIngress OR eventName=CreateSecurityGroup OR eventName=DeleteSecurityGroup OR eventName=DescribeClusterSecurityGroups OR eventName=DescribeDBSecurityGroups OR eventName=DescribeSecurityGroupReferences OR eventName=DescribeSecurityGroups OR eventName=DescribeStaleSecurityGroups OR eventName=RevokeSecurityGroupIngress OR eventName=UpdateSecurityGroupRuleDescriptionsIngress) -description = This macro is a list of AWS event names associated with security groups - -[stream_http] -definition = sourcetype=stream:http -description = customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. - -[suspicious_email_attachments] -definition = lookup update=true is_suspicious_file_extension_lookup file_name OUTPUT suspicious | search suspicious=true -description = This macro limits the output to email attachments that have suspicious extensions - -[suspicious_writes] -definition = lookup suspicious_writes_lookup file as file_name OUTPUT note as "Reference" | search "Reference" != False -description = This macro limites the output to file names that have been marked as suspicious - -[sysmon] -definition = sourcetype=XmlWinEventLog:Microsoft-Windows-Sysmon/Operational -description = customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. - -[system_network_configuration_discovery_tools] -definition = (process_name= "arp.exe" OR process_name= "at.exe" OR process_name= "attrib.exe" OR process_name= "cscript.exe" OR process_name= "dsquery.exe" OR process_name= "hostname.exe" OR process_name= "ipconfig.exe" OR process_name= "mimikatz.exe" OR process_name= "nbstat.exe" OR process_name= "net.exe" OR process_name= "netsh.exe" OR process_name= "nslookup.exe" OR process_name= "ping.exe" OR process_name= "quser.exe" OR process_name= "qwinsta.exe" OR process_name= "reg.exe" OR process_name= "runas.exe" OR process_name= "sc.exe" OR process_name= "schtasks.exe" OR process_name= "ssh.exe" OR process_name= "systeminfo.exe" OR process_name= "taskkill.exe" OR process_name= "telnet.exe" OR process_name= "tracert.exe" OR process_name="wscript.exe" OR process_name= "xcopy.exe") -description = This macro is a list of process that can be used to discover the network configuration - -[uncommon_processes] -definition = lookup update=true lookup_uncommon_processes_default process_name as process_name outputnew uncommon_default,category_default,analytic_story_default,kill_chain_phase_default,mitre_attack_default | lookup update=true lookup_uncommon_processes_local process_name as process_name outputnew uncommon_local,category_local,analytic_story_local,kill_chain_phase_local,mitre_attack_local | eval uncommon = coalesce(uncommon_default, uncommon_local), analytic_story = coalesce(analytic_story_default, analytic_story_local), category=coalesce(category_default, category_local), kill_chain_phase=coalesce(kill_chain_phase_default, kill_chain_phase_local), mitre_attack=coalesce(mitre_attack_default, mitre_attack_local) | fields - analytic_story_default, analytic_story_local, category_default, category_local, kill_chain_phase_default, kill_chain_phase_local, mitre_attack_default, mitre_attack_local, uncommon_default, uncommon_local | search uncommon=true -description = This macro limits the output to processes that have been marked as uncommon - -[wineventlog_security] -definition = eventtype=wineventlog_security -description = customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. - -[wineventlog_system] -definition = eventtype=wineventlog_system -description = customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. - -[wmi] -definition = sourcetype="wineventlog:microsoft-windows-wmi-activity/operational" -description = customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. - -[aws_cloud_provisioning_from_previously_unseen_city_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[aws_cloud_provisioning_from_previously_unseen_country_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[aws_cloud_provisioning_from_previously_unseen_ip_address_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[aws_cloud_provisioning_from_previously_unseen_region_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[aws_cross_account_activity_from_previously_unseen_account_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. - -[aws_network_access_control_list_deleted_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[abnormally_high_aws_instances_launched_by_user_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[abnormally_high_aws_instances_launched_by_user___mltk_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[abnormally_high_aws_instances_terminated_by_user_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[abnormally_high_aws_instances_terminated_by_user___mltk_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[access_lsass_memory_for_dump_creation_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[amazon_eks_kubernetes_pod_scan_detection_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[amazon_eks_kubernetes_cluster_scan_detection_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[attempt_to_add_certificate_to_untrusted_store_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[attempt_to_stop_security_service_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[attempted_credential_dump_from_registry_via_reg_exe_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. - -[child_processes_of_spoolsv_exe_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[clients_connecting_to_multiple_dns_servers_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[cloud_compute_instance_created_by_previously_unseen_user_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[cloud_compute_instance_created_with_previously_unseen_image_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[cloud_compute_instance_created_with_previously_unseen_instance_type_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[cloud_compute_instance_started_in_previously_unused_region_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[common_ransomware_extensions_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[common_ransomware_notes_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[create_remote_thread_into_lsass_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[create_local_admin_accounts_using_net_exe_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[create_or_delete_windows_shares_using_net_exe_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[creation_of_shadow_copy_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[creation_of_shadow_copy_with_wmic_and_powershell_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[credential_dumping_via_copy_command_from_shadow_copy_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[credential_dumping_via_symlink_to_shadow_copy_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[dns_query_length_outliers___mltk_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[dns_query_length_with_high_standard_deviation_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[dns_query_requests_resolved_by_unauthorized_dns_servers_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[dns_record_changed_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. - -[detect_api_activity_from_users_without_mfa_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_aws_api_activities_from_unapproved_accounts_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_aws_console_login_by_user_from_new_city_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_aws_console_login_by_user_from_new_country_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_aws_console_login_by_user_from_new_region_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_activity_related_to_pass_the_hash_attacks_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_credential_dumping_through_lsass_access_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_dns_requests_to_phishing_sites_leveraging_evilginx2_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_excessive_account_lockouts_from_endpoint_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_excessive_user_account_lockouts_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_large_outbound_icmp_packets_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_long_dns_txt_record_response_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_mimikatz_using_loaded_images_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_mimikatz_via_powershell_and_eventcode_4703_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_new_local_admin_account_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_new_login_attempts_to_routers_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_new_open_s3_buckets_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_oulook_exe_writing_a__zip_file_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_outbound_smb_traffic_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_path_interception_by_creation_of_program_exe_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_prohibited_applications_spawning_cmd_exe_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_psexec_with_accepteula_flag_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_rare_executables_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_s3_access_from_a_new_ip_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_spike_in_aws_api_activity_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_spike_in_network_acl_activity_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_spike_in_s3_bucket_deletion_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_spike_in_security_group_activity_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_spike_in_blocked_outbound_traffic_from_your_aws_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_usb_device_insertion_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_unauthorized_assets_by_mac_address_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_use_of_cmd_exe_to_launch_script_interpreters_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_attackers_scanning_for_vulnerable_jboss_servers_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_hosts_connecting_to_dynamic_domain_providers_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_malicious_requests_to_exploit_jboss_servers_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_mshta_exe_running_scripts_in_command_line_arguments_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_new_api_calls_from_user_roles_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_new_user_aws_console_login_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_processes_used_for_system_network_configuration_discovery_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detect_web_traffic_to_dynamic_domain_providers_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detection_of_dns_tunnels_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[detection_of_tools_built_by_nirsoft_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. - -[dump_lsass_via_comsvcs_dll_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[ec2_instance_modified_with_previously_unseen_user_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[ec2_instance_started_in_previously_unseen_region_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[ec2_instance_started_with_previously_unseen_ami_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[ec2_instance_started_with_previously_unseen_instance_type_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[ec2_instance_started_with_previously_unseen_user_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[email_attachments_with_lots_of_spaces_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[email_files_written_outside_of_the_outlook_directory_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[email_servers_sending_high_volume_traffic_to_hosts_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[excessive_dns_failures_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[execution_of_file_with_spaces_before_extension_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[execution_of_file_with_multiple_extensions_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[extended_period_without_successful_netbackup_backups_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[file_with_samsam_extension_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[first_time_seen_running_windows_service_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[first_time_seen_command_line_argument_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[gcp_gcr_container_uploaded_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[gcp_kubernetes_cluster_scan_detection_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[hiding_files_and_directories_with_attrib_exe_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[hosts_receiving_high_volume_of_network_traffic_from_email_server_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[identify_new_user_accounts_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[kubernetes_azure_detect_rbac_authorization_by_account_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[kubernetes_azure_detect_most_active_service_accounts_by_pod_namespace_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[kubernetes_azure_detect_sensitive_object_access_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[kubernetes_azure_detect_sensitive_role_access_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[kubernetes_azure_detect_service_accounts_forbidden_failure_access_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[kubernetes_azure_detect_suspicious_kubectl_calls_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[kubernetes_azure_pod_scan_fingerprint_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[kubernetes_azure_scan_fingerprint_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[large_volume_of_dns_any_queries_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[macos___re_opened_applications_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[malicious_powershell_process___connect_to_internet_with_hidden_window_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[malicious_powershell_process___encoded_command_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[malicious_powershell_process___execution_policy_bypass_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[malicious_powershell_process___multiple_suspicious_command_line_arguments_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[malicious_powershell_process_with_obfuscation_techniques_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. - -[monitor_email_for_brand_abuse_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[monitor_registry_keys_for_print_monitors_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[monitor_web_traffic_for_brand_abuse_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[multiple_okta_users_with_invalid_credentails_from_the_same_ip_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[new_container_uploaded_to_aws_ecr_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[no_windows_updates_in_a_time_frame_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[okta_account_lockout_events_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[okta_failed_sso_attempts_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[okta_user_logins_from_multiple_cities_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[open_redirect_in_splunk_web_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[osquery_pack___coldroot_detection_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[overwriting_accessibility_binaries_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[process_execution_via_wmi_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[processes_tapping_keyboard_events_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[processes_created_by_netsh_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[processes_launching_netsh_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[prohibited_network_traffic_allowed_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[prohibited_software_on_endpoint_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[protocol_or_port_mismatch_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[protocols_passing_authentication_in_cleartext_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[reg_exe_manipulating_windows_services_registry_keys_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[reg_exe_used_to_hide_files_directories_via_registry_keys_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[registry_keys_used_for_persistence_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[registry_keys_used_for_privilege_escalation_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[registry_keys_for_creating_shim_databases_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[remote_desktop_network_bruteforce_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[remote_desktop_network_traffic_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[remote_desktop_process_running_on_system_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[remote_process_instantiation_via_wmi_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[remote_registry_key_modifications_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[remote_wmi_command_attempt_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[rundll_loading_dll_by_ordinal_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[smb_traffic_spike_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[smb_traffic_spike___mltk_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[sql_injection_with_long_urls_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[samsam_test_file_write_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[sc_exe_manipulating_windows_services_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[scheduled_task_name_used_by_dragonfly_threat_actors_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[scheduled_tasks_used_in_badrabbit_ransomware_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[schtasks_scheduling_job_on_remote_system_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[schtasks_used_for_forcing_a_reboot_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[script_execution_via_wmi_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[shim_database_file_creation_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[shim_database_installation_with_suspicious_parameters_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[short_lived_windows_accounts_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[single_letter_process_on_endpoint_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[spectre_and_meltdown_vulnerable_systems_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[spike_in_file_writes_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[splunk_enterprise_information_disclosure_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[suspicious_changes_to_file_associations_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[suspicious_email___uba_anomaly_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[suspicious_email_attachment_extensions_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[suspicious_file_write_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[suspicious_java_classes_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[suspicious_lnk_file_launching_a_process_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[suspicious_reg_exe_process_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[suspicious_wevtutil_usage_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[suspicious_writes_to_system_volume_information_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[suspicious_writes_to_windows_recycle_bin_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[system_processes_run_from_unexpected_locations_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[tor_traffic_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[usn_journal_deletion_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[uncommon_processes_on_endpoint_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[unload_sysmon_filter_driver_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[unsigned_image_loaded_by_lsass_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[unsuccessful_netbackup_backups_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[unusually_long_command_line_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[unusually_long_command_line___mltk_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[unusually_long_content_type_length_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[wmi_permanent_event_subscription_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[wmi_permanent_event_subscription___sysmon_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[wmi_temporary_event_subscription_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[web_fraud___account_harvesting_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[web_fraud___anomalous_user_clickspeed_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[web_fraud___password_sharing_across_accounts_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[web_servers_executing_suspicious_processes_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[windows_event_log_cleared_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[windows_hosts_file_modification_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - diff --git a/package/default/savedsearches.conf b/package/default/savedsearches.conf deleted file mode 100644 index 13a435839d..0000000000 --- a/package/default/savedsearches.conf +++ /dev/null @@ -1,10143 +0,0 @@ -############# -# Automatically generated by generator.py in splunk/security-content -# On Date: 2020-06-03T20:28:01 UTC -# Author: Splunk Security Research -# Contact: research@splunk.com -############# - -### ESCU DETECTIONS ### - -[ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule] -action.escu = 0 -action.escu.enabled = 1 -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." -action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -action.escu.data_models = [] -action.escu.eli5 = 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." -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. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. -action.escu.known_false_positives = This is a strictly behavioral search, so we define "false positive" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching within, plus what is stored in the cache feature. But while there are really no "false positives" in a traditional sense, there is definitely lots of noise.\ - This search will fire any time a new city is seen in the **GeoIP** database for any kind of provisioning activity. If you typically do all provisioning from tools inside of your city, there should be few false positives. If you are located in countries where the free version of **MaxMind GeoIP** that ships by default with Splunk has weak resolution (particularly small countries in less economically powerful regions), this may be much less valuable to you. -action.escu.creation_date = 2018-03-16 -action.escu.modification_date = 2018-03-16 -action.escu.confidence = high -action.escu.full_search_name = ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule -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." -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search City=* [search `cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search City=* | stats earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country | inputlookup append=t previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by sourceIPAddress, City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by City | eval newCity=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newCity=1 | table City] | spath output=user userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, City, eventName, errorCode | `aws_cloud_provisioning_from_previously_unseen_city_filter` - -[ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule] -action.escu = 0 -action.escu.enabled = 1 -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." -action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -action.escu.data_models = [] -action.escu.eli5 = 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." -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. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. -action.escu.known_false_positives = This is a strictly behavioral search, so we define "false positive" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching over plus what is stored in the cache feature. But while there are really no "false positives" in a traditional sense, there is definitely lots of noise.\ - This search will fire any time a new country is seen in the **GeoIP** database for any kind of provisioning activity. If you typically do all provisioning from tools inside of your country, there should be few false positives. If you are located in countries where the free version of **MaxMind GeoIP** that ships by default with Splunk has weak resolution (particularly small countries in less economically powerful regions), this may be much less valuable to you. -action.escu.creation_date = 2018-03-16 -action.escu.modification_date = 2018-03-16 -action.escu.confidence = high -action.escu.full_search_name = ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule -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." -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search Country=* [search `cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search Country=* | stats earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country | inputlookup append=t previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by sourceIPAddress, City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by Country | eval newCountry=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newCountry=1 | table Country] | spath output=user userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, Country, eventName, errorCode | `aws_cloud_provisioning_from_previously_unseen_country_filter` - -[ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule] -action.escu = 0 -action.escu.enabled = 1 -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." -action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -action.escu.data_models = [] -action.escu.eli5 = 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." -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. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. -action.escu.known_false_positives = This is a strictly behavioral search, so we define "false positive" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching within, plus what is stored in the cache feature. But while there are really no "false positives" in a traditional sense, there is definitely lots of noise.\ - This search will fire any time a new IP address is seen in the **GeoIP** database for any kind of provisioning activity. If you typically do all provisioning from tools inside of your country, there should be few false positives. If you are located in countries where the free version of **MaxMind GeoIP** that ships by default with Splunk has weak resolution (particularly small countries in less economically powerful regions), this may be much less valuable to you. -action.escu.creation_date = 2018-03-16 -action.escu.modification_date = 2018-03-16 -action.escu.confidence = high -action.escu.full_search_name = ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule -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." -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `cloudtrail` (eventName=Run* OR eventName=Create*) [search `cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search Country=* | stats earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country | inputlookup append=t previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by sourceIPAddress, City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by sourceIPAddress | eval newIP=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newIP=1 | table sourceIPAddress] | spath output=user userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, eventName, errorCode | `aws_cloud_provisioning_from_previously_unseen_ip_address_filter` - -[ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule] -action.escu = 0 -action.escu.enabled = 1 -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." -action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -action.escu.data_models = [] -action.escu.eli5 = 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." -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. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. -action.escu.known_false_positives = This is a strictly behavioral search, so we define "false positive" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching within, plus what is stored in the cache feature. But while there are really no "false positives" in a traditional sense, there is definitely lots of noise.\ - This search will fire any time a new region is seen in the **GeoIP** database for any kind of provisioning activity. If you typically do all provisioning from tools inside of your region, there should be few false positives. If you are located in regions where the free version of **MaxMind GeoIP** that ships by default with Splunk has weak resolution (particularly small countries in less economically powerful regions), this may be much less valuable to you. -action.escu.creation_date = 2018-03-16 -action.escu.modification_date = 2018-03-16 -action.escu.confidence = high -action.escu.full_search_name = ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule -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." -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search Region=* [search `cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search Region=* | stats earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country | inputlookup append=t previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by sourceIPAddress, City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by Region | eval newRegion=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newRegion=1 | table Region] | spath output=user userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, Region, eventName, errorCode | `aws_cloud_provisioning_from_previously_unseen_region_filter` - -[ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for AssumeRole events where an IAM role in a different account is requested for the first time. -action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.AC", "PR.DS", "DE.AE"]} -action.escu.data_models = [] -action.escu.eli5 = This search looks for AssumeRole events where an IAM role in a different account is requested for the first time. -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. Run the `Previously Seen AWS Cross Account Activity` support search only once to create the baseline of previously seen cross account activity. Thanks to Pablo Vega at Recurly for suggesting improvements to the search. -action.escu.known_false_positives = Using multiple AWS accounts and roles is perfectly valid behavior. It's suspicious when an account requests privileges of an account it hasn't before. You should validate with the account owner that this is a legitimate request. -action.escu.creation_date = 2018-11-02 -action.escu.modification_date = 2018-11-02 -action.escu.confidence = high -action.escu.full_search_name = ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["AWS Cross Account Activity"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule -schedule_window = auto -action.notable = 1 -action.notable.param.nes_fields = ['user'] -action.notable.param.rule_description = This search looks for AssumeRole events where an IAM role in a different account is requested for the first time. -action.notable.param.rule_title = AWS Cross Account Activity From Previously Unseen Account -action.notable.param.security_domain = network -action.notable.param.severity = high -alert.digest_mode = 1 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `cloudtrail` eventName=AssumeRole | spath output=requestingAccountId path=userIdentity.accountId | spath output=requestedAccountId path=resources{}.accountId | search requestingAccountId=* | where requestingAccountId != requestedAccountId | inputlookup append=t previously_seen_aws_cross_account_activity | multireport [| stats min(eval(coalesce(firstTime, strptime(_time,"%Y-%m-%d %H:%M:%S")))) as firstTime max(eval(coalesce(strptime(_time,"%Y-%m-%d %H:%M:%S"), lastTime))) as lastTime by requestingAccountId, requestedAccountId | outputlookup previously_seen_aws_cross_account_activity | where fact=fiction] [| eventstats min(eval(coalesce(firstTime, strptime(_time,"%Y-%m-%d %H:%M:%S")))) as firstTime, max(eval(coalesce(strptime(_time,"%Y-%m-%d %H:%M:%S"), lastTime))) as lastTime by requestingAccountId, requestedAccountId | where firstTime >= relative_time(now(), "-70m@m") AND isnotnull(_time) | spath output=accessKeyId path=responseElements.credentials.accessKeyId | spath output=requestingARN path=resources{}.ARN | stats values(awsRegion) as awsRegion values(firstTime) as firstTime values(lastTime) as lastTime values(sharedEventID) as sharedEventID, values(requestingARN) as src_user, values(responseElements.assumedRoleUser.arn) as dest_user by _time, requestingAccountId, requestedAccountId, accessKeyId] | table _time, firstTime, lastTime, src_user, requestingAccountId, dest_user, requestedAccountId, awsRegion, accessKeyId, sharedEventID | `aws_cross_account_activity_from_previously_unseen_account_filter` - -[ESCU - AWS Network Access Control List Created with All Open Ports - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = The search looks for CloudTrail events to detect if any network ACLs were created with all the ports open to a specified CIDR. -action.escu.mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} -action.escu.data_models = [] -action.escu.eli5 = The search looks for CloudTrail events to detect if any network ACLs were created with all the ports open to a specified CIDR. -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, and configure your CloudTrail inputs. -action.escu.known_false_positives = It's possible that an admin has created this ACL with all ports open for some legitimate purpose however, this should be scoped and not allowed in production environment. -action.escu.creation_date = 2017-01-10 -action.escu.modification_date = 2017-01-10 -action.escu.confidence = high -action.escu.full_search_name = ESCU - AWS Network Access Control List Created with All Open Ports - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["AWS Network ACL Activity"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - AWS Network Access Control List Created with All Open Ports - Rule -schedule_window = auto -action.notable = 1 -action.notable.param.nes_fields = ['src'] -action.notable.param.rule_description = The search looks for CloudTrail events to detect if any network ACLs were created with all the ports open to a specified CIDR. -action.notable.param.rule_title = AWS Network Access Control List Created with All Open Ports -action.notable.param.security_domain = network -action.notable.param.severity = high -alert.digest_mode = 1 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `cloudtrail` eventName=CreateNetworkAclEntry | mvexpand requestParameters | mvexpand responseElements | search requestParameters.portRange.from=1024 requestParameters.portRange.to=65535 requestParameters.ruleAction=allow | rename userIdentity.arn as arn | rename requestParameters.networkAclId as networkAclId | table _time aws_account_id src userName arn networkAclId requestParameters.* responseElements.* | `aws_network_access_control_list_created_with_all_open_ports_filter` - -[ESCU - AWS Network Access Control List Deleted - Rule] -action.escu = 0 -action.escu.enabled = 1 -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 AWS 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 CloudTrail logs to detect users deleting network ACLs. -action.escu.mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} -action.escu.data_models = [] -action.escu.eli5 = 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 AWS 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 CloudTrail logs to detect users deleting network ACLs. -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. -action.escu.known_false_positives = It's possible that a user has legitimately deleted a network ACL. -action.escu.creation_date = 2017-01-10 -action.escu.modification_date = 2017-01-10 -action.escu.confidence = high -action.escu.full_search_name = ESCU - AWS Network Access Control List Deleted - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["AWS Network ACL Activity"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - AWS Network Access Control List Deleted - Rule -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 AWS 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 CloudTrail logs to detect users deleting network ACLs. -action.notable.param.rule_title = AWS Network Access Control List Deleted -action.notable.param.security_domain = network -action.notable.param.severity = high -alert.digest_mode = 1 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `cloudtrail` eventName=DeleteNetworkAcl|rename userIdentity.arn as arn | stats count min(_time) as firstTime max(_time) as lastTime values(errorMessage) values(errorCode) values(userAgent) values(userIdentity.*) by src userName arn eventName | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `aws_network_access_control_list_deleted_filter` - -[ESCU - Abnormally High AWS Instances Launched by User - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for CloudTrail events where a user successfully launches an abnormally high number of instances. -action.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} -action.escu.data_models = [] -action.escu.eli5 = This search looks for CloudTrail events where a user successfully launches an abnormally high number of 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. The threshold value should be tuned to your environment. -action.escu.known_false_positives = Many service accounts configured within an AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify if this search alerted on a human user. -action.escu.creation_date = 2018-02-26 -action.escu.modification_date = 2018-02-26 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Abnormally High AWS Instances Launched by User - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["AWS Cryptomining", "Suspicious AWS EC2 Activities"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Abnormally High AWS Instances Launched by User - Rule -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. -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `cloudtrail` eventName=RunInstances errorCode=success | bucket span=10m _time | stats count AS instances_launched by _time userName | eventstats avg(instances_launched) as total_launched_avg, stdev(instances_launched) as total_launched_stdev | eval threshold_value = 4 | eval isOutlier=if(instances_launched > total_launched_avg+(total_launched_stdev * threshold_value), 1, 0) | search isOutlier=1 AND _time >= relative_time(now(), "-10m@m") | eval num_standard_deviations_away = round(abs(instances_launched - total_launched_avg) / total_launched_stdev, 2) | table _time, userName, instances_launched, num_standard_deviations_away, total_launched_avg, total_launched_stdev | `abnormally_high_aws_instances_launched_by_user_filter` - -[ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for CloudTrail events where a user successfully launches an abnormally high number of instances. -action.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} -action.escu.data_models = [] -action.escu.eli5 = This search looks for CloudTrail events where a user successfully launches an abnormally high number of 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. The threshold value should be tuned to your environment. -action.escu.known_false_positives = Many service accounts configured within an AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify if this search alerted on a human user. -action.escu.creation_date = 2019-11-14 -action.escu.modification_date = 2019-11-14 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Cloud Cryptomining", "Suspicious AWS EC2 Activities"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule -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. -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `cloudtrail` eventName=RunInstances errorCode=success `abnormally_high_aws_instances_launched_by_user___mltk_filter` | bucket span=10m _time | stats count as instances_launched by _time src_user | apply ec2_excessive_runinstances_v1 | rename "IsOutlier(instances_launched)" as isOutlier | where isOutlier=1 - -[ESCU - Abnormally High AWS Instances Terminated by User - Rule] -action.escu = 0 -action.escu.enabled = 1 -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 -action.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} -action.escu.data_models = [] -action.escu.eli5 = This search looks for CloudTrail events where an abnormally high number of instances were successfully terminated by a user in a 10-minute 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. -action.escu.known_false_positives = Many service accounts configured with your AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify whether this search alerted on a human user. -action.escu.creation_date = 2018-02-26 -action.escu.modification_date = 2018-02-26 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Abnormally High AWS Instances Terminated by User - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious AWS EC2 Activities"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Abnormally High AWS Instances Terminated by User - Rule -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 -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `cloudtrail` eventName=TerminateInstances errorCode=success | bucket span=10m _time | stats count AS instances_terminated by _time userName | eventstats avg(instances_terminated) as total_terminations_avg, stdev(instances_terminated) as total_terminations_stdev | eval threshold_value = 4 | eval isOutlier=if(instances_terminated > total_terminations_avg+(total_terminations_stdev * threshold_value), 1, 0) | search isOutlier=1 AND _time >= relative_time(now(), "-10m@m")| eval num_standard_deviations_away = round(abs(instances_terminated - total_terminations_avg) / total_terminations_stdev, 2) |table _time, userName, instances_terminated, num_standard_deviations_away, total_terminations_avg, total_terminations_stdev | `abnormally_high_aws_instances_terminated_by_user_filter` - -[ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for CloudTrail events where a user successfully terminates an abnormally high number of instances. -action.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} -action.escu.data_models = [] -action.escu.eli5 = This search looks for CloudTrail events where a user successfully terminates an abnormally high number of 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. The threshold value should be tuned to your environment. -action.escu.known_false_positives = Many service accounts configured within an AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify if this search alerted on a human user. -action.escu.creation_date = 2019-11-14 -action.escu.modification_date = 2019-11-14 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious AWS EC2 Activities"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule -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. -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `cloudtrail` eventName=TerminateInstances errorCode=success `abnormally_high_aws_instances_terminated_by_user___mltk_filter` | bucket span=10m _time | stats count as instances_terminated by _time src_user | apply ec2_excessive_terminateinstances_v1 | rename "IsOutlier(instances_terminated)" as isOutlier | where isOutlier=1 - -[ESCU - Access LSASS Memory for Dump Creation - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = Detect memory dumping of the LSASS process. -action.escu.mappings = {"cis20": ["CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} -action.escu.data_models = [] -action.escu.eli5 = Detect memory dumping of the LSASS process. -action.escu.how_to_implement = This search requires Sysmon Logs and a Sysmon configuration, which includes EventCode 10 for lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon 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. -action.escu.known_false_positives = Administrators can create memory dumps for debugging purposes, but memory dumps of the LSASS process would be unusual. -action.escu.creation_date = 2019-12-06 -action.escu.modification_date = 2019-12-06 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Access LSASS Memory for Dump Creation - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Credential Dumping"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Access LSASS Memory for Dump Creation - Rule -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 -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -alert.digest_mode = 1 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `sysmon` EventCode=10 TargetImage=*lsass.exe CallTrace=*dbgcore.dll* OR CallTrace=*dbghelp.dll* | stats count min(_time) as firstTime max(_time) as lastTime by Computer, TargetImage, TargetProcessId, SourceImage, SourceProcessId | rename Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `access_lsass_memory_for_dump_creation_filter` - -[ESCU - Amazon EKS Kubernetes Pod scan detection - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search provides detection information on unauthenticated requests against Kubernetes' Pods API -action.escu.mappings = {"kill_chain_phases": ["Reconnaissance"]} -action.escu.data_models = [] -action.escu.eli5 = This search provides detection information on unauthenticated requests against Kubernetes' Pods API -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on forAWS (version 4.4.0 or later), then configure your AWS CloudWatch EKS Logs.Please also customize the `kubernetes_pods_aws_scan_fingerprint_detection` macro to filter out the false positives. -action.escu.known_false_positives = Not all unauthenticated requests are malicious, but frequency, UA and source IPs and direct request to API provide context. -action.escu.creation_date = 2020-04-15 -action.escu.modification_date = 2020-04-15 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Amazon EKS Kubernetes Pod scan detection - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Kubernetes Scanning Activity"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Amazon EKS Kubernetes Pod scan detection - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `aws_cloudwatchlogs_eks` "user.username"="system:anonymous" verb=list objectRef.resource=pods requestURI="/api/v1/pods" | rename source as cluster_name sourceIPs{} as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(responseStatus.reason) values(responseStatus.code) values(userAgent) values(verb) values(requestURI) by src_ip cluster_name user.username user.groups{} | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `amazon_eks_kubernetes_pod_scan_detection_filter` - -[ESCU - Amazon EKS Kubernetes cluster scan detection - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster in AWS -action.escu.mappings = {"kill_chain_phases": ["Reconnaissance"]} -action.escu.data_models = [] -action.escu.eli5 = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster in AWS -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 CloudWatch EKS Logs inputs. -action.escu.known_false_positives = Not all unauthenticated requests are malicious, but frequency, UA and source IPs will provide context. -action.escu.creation_date = 2020-04-15 -action.escu.modification_date = 2020-04-15 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Amazon EKS Kubernetes cluster scan detection - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Kubernetes Scanning Activity"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Amazon EKS Kubernetes cluster scan detection - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `aws_cloudwatchlogs_eks` "user.username"="system:anonymous" userAgent!="AWS Security Scanner" | rename sourceIPs{} as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(responseStatus.reason) values(source) as cluster_name values(responseStatus.code) values(userAgent) as http_user_agent values(verb) values(requestURI) by src_ip user.username user.groups{} | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` |`amazon_eks_kubernetes_cluster_scan_detection_filter` - -[ESCU - Attempt To Add Certificate To Untrusted Store - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = Attempt to add a certificate to the untrusted certificate store -action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1089"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = Attempt to add a certificate to the untrusted certificate store -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -action.escu.known_false_positives = There may be legitimate reasons for administrators to add a certificate to the untrusted certificate store. In such cases, this will typically be done on a large number of systems. -action.escu.creation_date = 2018-11-15 -action.escu.modification_date = 2018-11-15 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Attempt To Add Certificate To Untrusted Store - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Disabling Security Tools"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Attempt To Add Certificate To Untrusted Store - Rule -schedule_window = auto -action.notable = 1 -action.notable.param.nes_fields = ['user'] -action.notable.param.rule_description = Attempt to add a certificate to the untrusted certificate 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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 values(Processes.process) as process max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=certutil.exe (Processes.process=*-addstore* AND Processes.process=*disallowed* ) by Processes.parent_process Processes.process_name Processes.user | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | `attempt_to_add_certificate_to_untrusted_store_filter` - -[ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = Monitor for changes of the ExecutionPolicy in the registry to the values "unrestricted" or "bypass," which allows the execution of malicious scripts. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = Monitor for changes of the ExecutionPolicy in the registry to the values "unrestricted" or "bypass," which allows the execution of malicious scripts. -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 Registry node. You must also be ingesting logs with the fields registry_path, registry_key_name, and registry_value_name from your endpoints. -action.escu.known_false_positives = Administrators may attempt to change the default execution policy on a system for a variety of reasons. However, setting the policy to "unrestricted" or "bypass" as this search is designed to identify, would be unusual. Hits should be reviewed and investigated as appropriate. -action.escu.creation_date = 2019-12-02 -action.escu.modification_date = 2019-12-02 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Malicious PowerShell", "Credential Dumping"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule -schedule_window = auto -action.notable = 1 -action.notable.param.nes_fields = ['dest'] -action.notable.param.rule_description = Monitor for changes of the ExecutionPolicy in the registry to the values "unrestricted" or "bypass," which allows the execution of malicious scripts. -action.notable.param.rule_title = Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -alert.digest_mode = 1 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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\\Powershell\\1\\ShellIds\\Microsoft.PowerShell* Registry.registry_key_name=ExecutionPolicy (Registry.registry_value_name=Unrestricted OR Registry.registry_value_name=Bypass) 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)` | `attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass_filter` - -[ESCU - Attempt To Stop Security Service - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for attempts to stop security-related services on the endpoint. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1089"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for attempts to stop security-related services on the endpoint. -action.escu.how_to_implement = You must be ingesting data that records the file-system 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. The search is shipped with a lookup file, `security_services.csv`, that can be edited to update the list of services to monitor. This lookup file can be edited directly where it lives in `$SPLUNK_HOME/etc/apps/DA-ESS-ContentUpdate/lookups`, or via the Splunk console. You should add the names of services an attacker might use on the command line and surround with asterisks (*****), so that they work properly when searching the command line. The file should be updated with the names of any services you would like to monitor for attempts to stop the service., -action.escu.known_false_positives = None identified. Attempts to disable security-related services should be identified and understood. -action.escu.creation_date = 2017-09-15 -action.escu.modification_date = 2017-09-15 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Attempt To Stop Security Service - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Disabling Security Tools"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Attempt To Stop Security Service - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = | tstats `security_content_summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processes.process_name = net.exe OR Processes.process_name = sc.exe) Processes.process="* stop *" by Processes.process_name Processes.parent_process_name Processes.dest Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` |lookup security_services_lookup service as process OUTPUTNEW category, description | search category=security | `attempt_to_stop_security_service_filter` - -[ESCU - Attempted Credential Dump From Registry via Reg exe - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = Monitor for execution of reg.exe with parameters specifying an export of keys that contain hashed credentials that attackers may try to crack offline. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = Monitor for execution of reg.exe with parameters specifying an export of keys that contain hashed credentials that attackers may try to crack offline. -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. The command-line arguments are mapped to the "process" field in the Endpoint data model. -action.escu.known_false_positives = None identified. -action.escu.creation_date = 2019-12-02 -action.escu.modification_date = 2019-12-02 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Attempted Credential Dump From Registry via Reg exe - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Credential Dumping"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Attempted Credential Dump From Registry via Reg exe - Rule -schedule_window = auto -action.notable = 1 -action.notable.param.nes_fields = ['user', 'dest'] -action.notable.param.rule_description = Monitor for execution of reg.exe with parameters specifying an export of keys that contain hashed credentials that attackers may try to crack offline. -action.notable.param.rule_title = Attempted Credential Dump From Registry via Reg exe -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -alert.digest_mode = 1 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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=reg.exe OR Processes.process_name=cmd.exe) Processes.process=*save* (Processes.process=*HKEY_LOCAL_MACHINE\\Security* OR Processes.process=*HKEY_LOCAL_MACHINE\\SAM* OR Processes.process=*HKEY_LOCAL_MACHINE\\System* OR Processes.process=*HKLM\\Security* OR Processes.process=*HKLM\\System* OR Processes.process=*HKLM\\SAM*) by Processes.user Processes.process_name Processes.process Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `attempted_credential_dump_from_registry_via_reg_exe_filter` - -[ESCU - Batch File Write to System32 - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = The search looks for a batch file (.bat) written to the Windows system directory tree. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Delivery"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = The search looks for a batch file (.bat) written to the Windows system directory tree. -action.escu.how_to_implement = You must be ingesting data that records the file-system 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 = It is possible for this search to generate a notable event for a batch file write to a path that includes the string "system32", but is not the actual Windows system directory. As such, you should confirm the path of the batch file identified by the search. In addition, a false positive may be generated by an administrator copying a legitimate batch file in this directory tree. You should confirm that the activity is legitimate and modify the search to add exclusions, as necessary. -action.escu.creation_date = 2018-12-14 -action.escu.modification_date = 2018-12-14 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Batch File Write to System32 - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["SamSam Ransomware"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Batch File Write to System32 - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 values(Filesystem.dest) as dest values(Filesystem.file_name) as file_name values(Filesystem.user) as user from datamodel=Endpoint.Filesystem by Filesystem.file_path | `drop_dm_object_name(Filesystem)` | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)`| rex field=file_name "(?\.[^\.]+)$" | search file_path=*system32* AND file_extension=.bat | `batch_file_write_to_system32_filter` - -[ESCU - Child Processes of Spoolsv exe - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 5", "CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1068"], "nist": ["PR.AC", "PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = 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.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. The command-line arguments are mapped to the "process" field in the Endpoint data model. Update the `children_of_spoolsv_filter` macro to filter out legitimate child processes spawned by spoolsv.exe. -action.escu.known_false_positives = Some legitimate printer-related processes may show up as children of spoolsv.exe. You should confirm that any activity as legitimate and may be added as exclusions in the search. -action.escu.creation_date = 2020-03-16 -action.escu.modification_date = 2020-03-16 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Child Processes of Spoolsv exe - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Windows Privilege Escalation"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Child Processes of Spoolsv exe - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 values(Processes.process_name) as process_name values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.parent_process_name=spoolsv.exe AND Processes.process_name!=regsvr32.exe by Processes.dest Processes.parent_process Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `child_processes_of_spoolsv_exe_filter` - -[ESCU - Clients Connecting to Multiple DNS Servers - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 9", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048"], "nist": ["PR.PT", "DE.AE", "PR.DS"]} -action.escu.data_models = ["Network_Resolution"] -action.escu.eli5 = 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.escu.how_to_implement = This search requires that DNS data is being ingested and populating the `Network_Resolution` data model. This data can come from DNS logs or from solutions that parse network traffic for this data, such as Splunk Stream or Bro.\ -This search produces fields (`dest_count`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** Distinct DNS Connections, **Field:** dest_count\ -Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -action.escu.known_false_positives = It's possible that an enterprise has more than five DNS servers that are configured in a round-robin rotation. Please customize the search, as appropriate. -action.escu.creation_date = 2020-01-16 -action.escu.modification_date = 2020-01-16 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Clients Connecting to Multiple DNS Servers - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Command and Control", "Host Redirection", "Suspicious DNS Traffic", "DNS Hijacking"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Clients Connecting to Multiple DNS Servers - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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, values(DNS.dest) AS dest dc(DNS.dest) as dest_count from datamodel=Network_Resolution where DNS.message_type=QUERY by DNS.src | `drop_dm_object_name("Network_Resolution")` |where dest_count > 5 | `clients_connecting_to_multiple_dns_servers_filter` - -[ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for cloud compute instances created by users who have not created them before. -action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -action.escu.data_models = ["Cloud_Infrastructure"] -action.escu.eli5 = This search looks for cloud compute instances created by users who have not created them before. -action.escu.how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the "Previously Seen Cloud Compute Creations By User" support search to create of baseline of previously seen users. -action.escu.known_false_positives = It's possible that a user will start to create compute instances for the first time, for any number of reasons. Verify with the user launching instances that this is the intended behavior. -action.escu.creation_date = 2018-03-12 -action.escu.modification_date = 2018-03-12 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Cloud Cryptomining"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule -schedule_window = auto -action.notable = 1 -action.notable.param.nes_fields = ['user', 'dest'] -action.notable.param.rule_description = This search looks for cloud compute instances created by users who have not created them before. -action.notable.param.rule_title = Cloud Compute Instance Created By Previously Unseen User -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -alert.digest_mode = 1 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = | tstats `security_content_summariesonly` earliest(_time) as firstTime, latest(_time) as lastTime values(Compute.dest) as dest from datamodel=Cloud_Infrastructure.Compute where Compute.action=run by Compute.src_user | `drop_dm_object_name("Compute")` | inputlookup append=t previously_seen_cloud_compute_creations_by_user | stats min(firstTime) as firstTime max(lastTime) as lastTime, values(dest) as dest by src_user | multireport [| table src_user, firstTime, lastTime | outputlookup previously_seen_cloud_compute_creations_by_user | where fact=fiction][| eval new_user=if(firstTime >= relative_time(now(), `previously_seen_cloud_compute_creations_by_user_search_window_begin_offset`), 1, 0) | where new_user=1 | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`] | table src_user, dest, firstTime, lastTime | `cloud_compute_instance_created_by_previously_unseen_user_filter` - -[ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for cloud compute instances being created with previously unseen image IDs. -action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -action.escu.data_models = ["Cloud_Infrastructure"] -action.escu.eli5 = This search looks for cloud compute instances being created with previously unseen image IDs. -action.escu.how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the "Previously Seen Cloud Compute Images" support search to create a baseline of previously seen images. -action.escu.known_false_positives = After a new image is created, the first systems created with that image will cause this alert to fire. Verify that the image being used was created by a legitimate user. -action.escu.creation_date = 2018-10-12 -action.escu.modification_date = 2018-10-12 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Cloud Cryptomining"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule -schedule_window = auto -action.notable = 1 -action.notable.param.nes_fields = ['user', 'dest'] -action.notable.param.rule_description = This search looks for cloud compute instances being created with previously unseen image IDs. -action.notable.param.rule_title = Cloud Compute Instance Created With Previously Unseen Image -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -alert.digest_mode = 1 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime values(Compute.dest) as dest from datamodel=Cloud_Infrastructure.Compute where Compute.action=run `cloud_compute_instance_created_with_previously_unseen_image_filter` by Compute.image_id, Compute.src_user | `drop_dm_object_name("Compute")` | inputlookup append=t previously_seen_cloud_compute_images | stats min(firstTime) as firstTime max(lastTime) as lastTime, values(dest) as dest by image_id, src_user | multireport [| table image_id, firstTime, lastTime | outputlookup previously_seen_cloud_compute_images | where fact=fiction][| eval new_image=if(firstTime >= relative_time(now(), `previously_seen_cloud_compute_image_search_window_begin_offset`), 1, 0) | where new_image=1 | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`] | table image_id, dest, src_user, firstTime, lastTime - -[ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = Find EC2 instances being created with previously unseen instance types. -action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -action.escu.data_models = ["Cloud_Infrastructure"] -action.escu.eli5 = Find EC2 instances being created with previously unseen instance types. -action.escu.how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the " Previously Seen Cloud Compute Instance Types" support search to create a baseline of previously seen regions. -action.escu.known_false_positives = It is possible that an admin will create a new system using a new instance type that has never been used before. Verify with the creator that they intended to create the system with the new instance type. -action.escu.creation_date = 2018-03-12 -action.escu.modification_date = 2018-03-12 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Cloud Cryptomining"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule -schedule_window = auto -action.notable = 1 -action.notable.param.nes_fields = ['user', 'dest'] -action.notable.param.rule_description = Find EC2 instances being created with previously unseen instance types. -action.notable.param.rule_title = Cloud Compute Instance Created With Previously Unseen Instance Type -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -alert.digest_mode = 1 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime values(Compute.dest) as dest from datamodel=Cloud_Infrastructure.Compute where Compute.event_name=RunInstances `cloud_compute_instance_created_with_previously_unseen_instance_type_filter` by Compute.instance_type, Compute.src_user | `drop_dm_object_name("Compute")` | inputlookup append=t previously_seen_cloud_compute_instance_types | stats min(firstTime) as firstTime max(lastTime) as lastTime, values(dest) as dest by instance_type, src_user | multireport [| table instance_type, firstTime, lastTime | outputlookup previously_seen_cloud_compute_instance_types | where fact=fiction][| eval new_type=if(firstTime >= relative_time(now(), `previously_seen_cloud_compute_instance_types_search_window_begin_offset`), 1, 0) | where new_type=1 | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`] | table instance_type, dest, src_user, firstTime, lastTime - -[ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks at cloud-infrastructure events where an instance is created in any region within the last hour and then compares it to a lookup file of previously seen regions where instances have been created. -action.escu.mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} -action.escu.data_models = ["Cloud_Infrastructure"] -action.escu.eli5 = This search looks at cloud-infrastructure events where an instance is created in any region within the last hour and then compares it to a lookup file of previously seen regions where instances have been created. -action.escu.how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the \"Previously Seen Cloud Compute Instance Types\" support search to create a baseline of previously seen regions. -action.escu.known_false_positives = It's possible that a user has unknowingly started an instance in a new region. Please verify that this activity is legitimate. -action.escu.creation_date = 2019-10-02 -action.escu.modification_date = 2019-10-02 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Cloud Cryptomining"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule -schedule_window = auto -action.notable = 1 -action.notable.param.nes_fields = ['user', 'dest'] -action.notable.param.rule_description = This search looks at cloud-infrastructure events where an instance is created in any region within the last hour and then compares it to a lookup file of previously seen regions where instances have been created. -action.notable.param.rule_title = Cloud Compute Instance Started In Previously Unused Region -action.notable.param.security_domain = network -action.notable.param.severity = high -alert.digest_mode = 1 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime values(Compute.dest) as dest from datamodel=Cloud_Infrastructure.Compute where Compute.event_name=RunInstances `cloud_compute_instance_started_in_previously_unused_region_filter` by Compute.region, Compute.src_user | `drop_dm_object_name("Compute")` | inputlookup append=t previously_seen_cloud_regions | stats min(firstTime) as firstTime max(lastTime) as lastTime, values(dest) as dest by region, src_user | multireport [| table region, firstTime, lastTime | outputlookup previously_seen_cloud_regions | where fact=fiction][| eval new_region=if(firstTime >= relative_time(now(), `previously_seen_cloud_regions_search_window_begin_offset`), 1, 0) | where new_region=1 | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`] | table region, dest, src_user, firstTime, lastTime - -[ESCU - Common Ransomware Extensions - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = The search looks for file modifications with extensions commonly used by Ransomware -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = The search looks for file modifications with extensions commonly used by Ransomware -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.\ -This search produces fields (`query`,`query_length`,`count`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** Name, **Field:** Name\ -1. \ -1. **Label:** File Extension, **Field:** file_extension\ -Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -action.escu.known_false_positives = It is possible for a legitimate file with these extensions to be created. If this is a true ransomware attack, there will be a large number of files created with these extensions. -action.escu.creation_date = 2020-03-16 -action.escu.modification_date = 2020-03-16 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Common Ransomware Extensions - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["SamSam Ransomware", "Ransomware"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Common Ransomware Extensions - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_path) as file_path from datamodel=Endpoint.Filesystem by Filesystem.file_name | `drop_dm_object_name(Filesystem)` | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)`| rex field=file_name "(?\.[^\.]+)$" | `ransomware_extensions` | `common_ransomware_extensions_filter` - -[ESCU - Common Ransomware Notes - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = 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.escu.how_to_implement = You must be ingesting data that records file-system activity from your hosts to populate the Endpoint Filesystem data-model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file-system reads and writes. -action.escu.known_false_positives = It's possible that a legitimate file could be created with the same name used by ransomware note files. -action.escu.creation_date = 2020-03-16 -action.escu.modification_date = 2020-03-16 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Common Ransomware Notes - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["SamSam Ransomware", "Ransomware"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Common Ransomware Notes - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_path) as file_path from datamodel=Endpoint.Filesystem by Filesystem.file_name | `drop_dm_object_name(Filesystem)` | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)`|`ransomware_notes`| `common_ransomware_notes_filter` - -[ESCU - Create Remote Thread into LSASS - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = Detect remote thread creation into LSASS consistent with credential dumping. -action.escu.mappings = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} -action.escu.data_models = [] -action.escu.eli5 = Detect remote thread creation into LSASS consistent with credential dumping. -action.escu.how_to_implement = This search needs Sysmon Logs with a Sysmon configuration, which includes EventCode 8 with lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon 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. -action.escu.known_false_positives = Other tools can access LSASS for legitimate reasons and generate an event. In these cases, tweaking the search may help eliminate noise. -action.escu.creation_date = 2019-12-06 -action.escu.modification_date = 2019-12-06 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Create Remote Thread into LSASS - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Credential Dumping"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Create Remote Thread into LSASS - Rule -schedule_window = auto -action.notable = 1 -action.notable.param.nes_fields = ['dest'] -action.notable.param.rule_description = Detect remote thread creation into LSASS consistent with credential dumping. -action.notable.param.rule_title = Create Remote Thread into LSASS -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -alert.digest_mode = 1 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `sysmon` EventID=8 TargetImage=*lsass.exe | stats count min(_time) as firstTime max(_time) as lastTime by Computer, EventCode, TargetImage, TargetProcessId | rename Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` |`create_remote_thread_into_lsass_filter` - -[ESCU - Create local admin accounts using net exe - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for the creation of local administrator accounts using net.exe. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for the creation of local administrator accounts using net.exe. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -action.escu.known_false_positives = Administrators often leverage net.exe to create admin accounts. -action.escu.creation_date = 2020-03-16 -action.escu.modification_date = 2020-03-16 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Create local admin accounts using net exe - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["DHS Report TA18-074A"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Create local admin accounts using net exe - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 values(Processes.user) as user values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processs.process_name=net.exe OR Processes.process_name=net1.exe) by Processes.process Processes.process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | search (process=*localgroup* OR process=*/add* OR process=*user*) |`create_local_admin_accounts_using_net_exe_filter` - -[ESCU - Create or delete windows shares using net exe - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for the creation or deletion of hidden shares using net.exe. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for the creation or deletion of hidden shares using net.exe. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -action.escu.known_false_positives = Administrators often leverage net.exe to create or delete network shares. You should verify that the activity was intentional and is legitimate. -action.escu.creation_date = 2020-01-20 -action.escu.modification_date = 2020-01-20 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Create or delete windows shares using net exe - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Hidden Cobra Malware"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Create or delete windows shares using net exe - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 values(Processes.user) as user values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processs.process_name=net.exe OR Processes.process_name=net1.exe) by Processes.process Processes.process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | search (process=*share* AND process=*delete*) | `create_or_delete_windows_shares_using_net_exe_filter` - -[ESCU - Creation of Shadow Copy - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = Monitor for signs that Ntdsutil, Vssadmin, or Wmic has been used to create a shadow copy. -action.escu.mappings = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = Monitor for signs that Ntdsutil, Vssadmin, or Wmic has been used to create a shadow copy. -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. The command-line arguments are mapped to the "process" field in the Endpoint data model. -action.escu.known_false_positives = Legtimate administrator usage of Ntdsutil, Vssadmin, or Wmic will create false positives. -action.escu.creation_date = 2019-12-10 -action.escu.modification_date = 2019-12-10 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Creation of Shadow Copy - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Credential Dumping"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Creation of Shadow Copy - Rule -schedule_window = auto -action.notable = 1 -action.notable.param.nes_fields = ['user', 'dest'] -action.notable.param.rule_description = Monitor for signs that Ntdsutil, Vssadmin, or Wmic has been used to create a shadow copy. -action.notable.param.rule_title = Creation of Shadow Copy -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -alert.digest_mode = 1 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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=ntdsutil.exe Processes.process=*ntds* Processes.process=*create*) OR (Processes.process_name=vssadmin.exe Processes.process=*create* Processes.process=*shadow*) OR (Processes.process_name=wmic.exe Processes.process=*shadowcopy* Processes.process=*create*) by Processes.dest Processes.user Processes.process_name Processes.process Processes.parent_process Processes.process_id Processes.parent_process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `creation_of_shadow_copy_filter` - -[ESCU - Creation of Shadow Copy with wmic and powershell - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search detects the use of wmic and Powershell to create a shadow copy. -action.escu.mappings = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} -action.escu.data_models = [] -action.escu.eli5 = This search detects the use of wmic and Powershell to create a shadow copy. -action.escu.how_to_implement = You must enable Powershell scriptblock logging in order to detect this attack.This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon 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. -action.escu.known_false_positives = Legtimate administrator usage of wmic to create a shadow copy. -action.escu.creation_date = 2019-12-10 -action.escu.modification_date = 2019-12-10 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Creation of Shadow Copy with wmic and powershell - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Credential Dumping"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Creation of Shadow Copy with wmic and powershell - Rule -schedule_window = auto -action.notable = 1 -action.notable.param.nes_fields = ['dest'] -action.notable.param.rule_description = This search detects the use of wmic and Powershell to create a shadow copy. -action.notable.param.rule_title = Creation of Shadow Copy with wmic and powershell -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -alert.digest_mode = 1 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `sysmon` Message=*win32_shadowcopy* Message=*Create* | stats count min(_time) as firstTime max(_time) as lastTime by dvc User EventCode Message | rename User as user, dvc as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `creation_of_shadow_copy_with_wmic_and_powershell_filter` - -[ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search detects credential dumping using copy command from a shadow copy. -action.escu.mappings = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search detects credential dumping using copy command from a shadow copy. -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. The command-line arguments are mapped to the "process" field in the Endpoint data model. -action.escu.known_false_positives = unknown -action.escu.creation_date = 2019-12-10 -action.escu.modification_date = 2019-12-10 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Credential Dumping"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule -schedule_window = auto -action.notable = 1 -action.notable.param.nes_fields = ['user', 'dest'] -action.notable.param.rule_description = This search detects credential dumping using copy command from a shadow copy. -action.notable.param.rule_title = Credential Dumping via Copy Command from Shadow Copy -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -alert.digest_mode = 1 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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=cmd.exe (Processes.process=*\\system32\\config\\sam* OR Processes.process=*\\system32\\config\\security* OR Processes.process=*\\system32\\config\\system* OR Processes.process=*\\windows\\ntds\\ntds.dit*) by Processes.dest Processes.user Processes.process_name Processes.process Processes.parent_process Processes.process_id Processes.parent_process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `credential_dumping_via_copy_command_from_shadow_copy_filter` - -[ESCU - Credential Dumping via Symlink to Shadow Copy - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search detects the creation of a symlink to a shadow copy. -action.escu.mappings = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search detects the creation of a symlink to a shadow copy. -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. The command-line arguments are mapped to the "process" field in the Endpoint data model. -action.escu.known_false_positives = unknown -action.escu.creation_date = 2019-12-10 -action.escu.modification_date = 2019-12-10 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Credential Dumping via Symlink to Shadow Copy - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Credential Dumping"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Credential Dumping via Symlink to Shadow Copy - Rule -schedule_window = auto -action.notable = 1 -action.notable.param.nes_fields = ['user', 'dest'] -action.notable.param.rule_description = This search detects the creation of a symlink to a shadow copy. -action.notable.param.rule_title = Credential Dumping via Symlink to Shadow Copy -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -alert.digest_mode = 1 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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=cmd.exe Processes.process=*mklink* Processes.process=*HarddiskVolumeShadowCopy* by Processes.dest Processes.user Processes.process_name Processes.process Processes.parent_process Processes.process_id Processes.parent_process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `credential_dumping_via_symlink_to_shadow_copy_filter` - -[ESCU - DNS Query Length Outliers - MLTK - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search allows you to identify DNS requests that are unusually large for the record type being requested in your environment. -action.escu.mappings = {"cis20": ["CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1043"], "nist": ["PR.PT", "DE.AE", "DE.CM"]} -action.escu.data_models = ["Network_Resolution"] -action.escu.eli5 = This search allows you to identify DNS requests that are unusually large for the record type being requested in your environment. -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, the Machine Learning Toolkit (MLTK) version 4.2 or greater must be installed on your search heads, along with any required dependencies. Finally, the support search "Baseline of DNS Query Length - MLTK" must be executed before this detection search, because it builds a machine-learning (ML) model over the historical data used by this search. It is important that this search is run in the same app context as the associated support search, so that the model created by the support search is available for use. You should periodically re-run the support search to rebuild the model with the latest data available in your environment.\ -This search produces fields (`query`,`query_length`,`count`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** DNS Query, **Field:** query\ -1. \ -1. **Label:** DNS Query Length, **Field:** query_length\ -1. \ -1. **Label:** Number of events, **Field:** count\ -Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -action.escu.known_false_positives = If you are seeing more results than desired, you may consider reducing the value for threshold in the search. You should also periodically re-run the support search to re-build the ML model on the latest data. -action.escu.creation_date = 2020-01-22 -action.escu.modification_date = 2020-01-22 -action.escu.confidence = high -action.escu.full_search_name = ESCU - DNS Query Length Outliers - MLTK - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Command and Control", "Hidden Cobra Malware", "Suspicious DNS Traffic"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - DNS Query Length Outliers - MLTK - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 start_time max(_time) as end_time values(DNS.src) as src values(DNS.dest) as dest from datamodel=Network_Resolution by DNS.query DNS.record_type | search DNS.record_type=* | `drop_dm_object_name(DNS)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | eval query_length = len(query) | apply dns_query_pdfmodel threshold=0.01 | rename "IsOutlier(query_length)" as isOutlier | search isOutlier > 0 | sort -query_length | table start_time end_time query record_type count src dest query_length | `dns_query_length_outliers___mltk_filter` - -[ESCU - DNS Query Length With High Standard Deviation - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1043"], "nist": ["PR.PT", "DE.AE", "DE.CM"]} -action.escu.data_models = ["Network_Resolution"] -action.escu.eli5 = 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.escu.how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. -action.escu.known_false_positives = It's possible there can be long domain names that are legitimate. -action.escu.creation_date = 2020-01-22 -action.escu.modification_date = 2020-01-22 -action.escu.confidence = high -action.escu.full_search_name = ESCU - DNS Query Length With High Standard Deviation - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Command and Control", "Hidden Cobra Malware", "Suspicious DNS Traffic"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - DNS Query Length With High Standard Deviation - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 from datamodel=Network_Resolution by DNS.query DNS.record_type | `drop_dm_object_name("DNS")` | eval query_length = len(query) | table query query_length record_type count | eventstats stdev(query_length) AS stdev avg(query_length) AS avg p50(query_length) AS p50| where query_length>(avg+stdev*2) | eval z_score=(query_length-avg)/stdev | `dns_query_length_with_high_standard_deviation_filter` - -[ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 1", "CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"]} -action.escu.data_models = ["Network_Resolution"] -action.escu.eli5 = 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.escu.how_to_implement = To successfully implement this search you will need to ensure that DNS data is populating the Network_Resolution data model. It also requires that your DNS servers are identified correctly in the Assets and Identity table of Enterprise Security. -action.escu.known_false_positives = Legitimate DNS activity can be detected in this search. Investigate, verify and update the list of authorized DNS servers as appropriate. -action.escu.creation_date = 2020-01-17 -action.escu.modification_date = 2020-01-17 -action.escu.confidence = high -action.escu.full_search_name = ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Command and Control", "Host Redirection", "Suspicious DNS Traffic", "DNS Hijacking"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 from datamodel=Network_Resolution where DNS.dest_category != dns_server AND DNS.src_category != dns_server by DNS.src DNS.dest | `drop_dm_object_name("DNS")` | `dns_query_requests_resolved_by_unauthorized_dns_servers_filter` - -[ESCU - DNS record changed - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 1", "CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"]} -action.escu.data_models = ["Network_Resolution"] -action.escu.eli5 = 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.escu.how_to_implement = To successfully implement this search you will need to ensure that DNS data is populating the `Network_Resolution` data model. It also requires that the `discover_dns_record` lookup table be populated by the included support search "Discover DNS record". \ - **Splunk>Phantom Playbook Integration**\ -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/`).\ - -action.escu.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. -action.escu.creation_date = 2020-01-16 -action.escu.modification_date = 2020-01-16 -action.escu.confidence = high -action.escu.full_search_name = ESCU - DNS record changed - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["DNS Hijacking"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - DNS record changed - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = | inputlookup discovered_dns_records.csv | 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 - Deleting Shadow Copies - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 8", "CIS 10"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = 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.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. The command-line arguments are mapped to the "process" field in the Endpoint data model. -action.escu.known_false_positives = vssadmin.exe and wmic.exe are standard applications shipped with modern versions of windows. They may be used by administrators to legitimately delete old backup copies, although this is typically rare. -action.escu.creation_date = 2020-04-17 -action.escu.modification_date = 2020-04-17 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Deleting Shadow Copies - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["SamSam Ransomware", "Windows Log Manipulation", "Ransomware"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Deleting Shadow Copies - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 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=vssadmin.exe OR Processes.process_name=wmic.exe) by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | search process=*delete* AND process=*shadow* | `deleting_shadow_copies_filter` - -[ESCU - Detect API activity from users without MFA - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 16"], "nist": ["DE.DP", "PR.AC"]} -action.escu.data_models = [] -action.escu.eli5 = 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.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. Leverage the support search `Create a list of approved AWS service accounts`: run it once every 30 days to create a list of service accounts and validate them.\ -This search produces fields (`eventName`,`userIdentity.type`,`userIdentity.arn`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** AWS Event Name, **Field:** eventName\ -1. \ -1. **Label:** AWS User ARN, **Field:** userIdentity.arn\ -1. \ -1. **Label:** AWS User Type, **Field:** userIdentity.type\ -Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -action.escu.known_false_positives = Many service accounts configured within an AWS infrastructure do not have multi factor authentication enabled. Please ignore the service accounts, if triggered and instead add them to the aws_service_accounts.csv file to fine tune the detection. It is also possible that the search detects users in your environment using Single Sign-On systems, since the MFA is not handled by AWS. -action.escu.creation_date = 2018-05-17 -action.escu.modification_date = 2018-05-17 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect API activity from users without MFA - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["AWS User Monitoring"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect API activity from users without MFA - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `cloudtrail` userIdentity.sessionContext.attributes.mfaAuthenticated=false | search NOT [| inputlookup aws_service_accounts | fields identity | rename identity as user]| stats count min(_time) as firstTime max(_time) as lastTime values(eventName) as eventName by userIdentity.arn userIdentity.type user | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `detect_api_activity_from_users_without_mfa_filter` - -[ESCU - Detect AWS API Activities From Unapproved Accounts - Rule] -action.escu = 0 -action.escu.enabled = 1 -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. -action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC", "ID.AM"]} -action.escu.data_models = [] -action.escu.eli5 = 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. -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. You must also populate the `identity_lookup_expanded` lookup shipped with the Asset and Identity framework to be able to look up users in your identity table in Enterprise Security (ES). Leverage the support search called "Create a list of approved AWS service accounts": run it once every 30 days to create and validate a list of service accounts.\ -This search produces fields (`eventName`,`firstTime`,`lastTime`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** AWS Event Name, **Field:** eventName\ -1. \ -1. **Label:** First Time, **Field:** firstTime\ -1. \ -1. **Label:** Last Time, **Field:** lastTime\ -Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -action.escu.known_false_positives = It's likely that you'll find activity detected by users/service accounts that are not listed in the `identity_lookup_expanded` or ` aws_service_accounts.csv` file. If the user is a legitimate service account, update the `aws_service_accounts.csv` table with that entry. -action.escu.creation_date = 2018-03-13 -action.escu.modification_date = 2018-03-13 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect AWS API Activities From Unapproved Accounts - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["AWS User Monitoring"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect AWS API Activities From Unapproved Accounts - Rule -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. -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `cloudtrail` errorCode=success | rename userName as identity | search NOT [| inputlookup identity_lookup_expanded | fields identity] | search NOT [| inputlookup aws_service_accounts | fields identity] | rename identity as user | stats count min(_time) as firstTime max(_time) as lastTime values(eventName) as eventName by user | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `detect_aws_api_activities_from_unapproved_accounts_filter` - -[ESCU - Detect AWS Console Login by User from New City - Rule] -action.escu = 0 -action.escu.enabled = 1 -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 -action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} -action.escu.data_models = [] -action.escu.eli5 = 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 -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. Run the "Previously seen users in CloudTrail" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run "Update previously seen users in CloudTrail" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines. -action.escu.known_false_positives = When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate. -action.escu.creation_date = 2018-04-30 -action.escu.modification_date = 2018-04-30 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect AWS Console Login by User from New City - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious AWS Login Activities"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect AWS Console Login by User from New City - Rule -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 -action.notable.param.rule_title = Detect AWS Console Login by User from New City -action.notable.param.security_domain = network -action.notable.param.severity = high -alert.digest_mode = 1 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = | inputlookup previously_seen_users_console_logins.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by user City | join user type=outer [| inputlookup previously_seen_users_console_logins.csv | stats min(firstTime) AS earliestseen by user | fields earliestseen user] | eval userStatus=if(firstTime >= relative_time(now(), "@d"), "New City","Previously Seen City") | eval UserData=if(earliestseen >= relative_time(now(), "@d") OR isnull(earliestseen), "New User","Old User") | where userStatus="New City" AND UserData="Old User" | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`| `security_content_ctime(earliestseen)` | table user City userStatus firstTime lastTime earliestseen | `detect_aws_console_login_by_user_from_new_city_filter` - -[ESCU - Detect AWS Console Login by User from New Country - Rule] -action.escu = 0 -action.escu.enabled = 1 -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 -action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} -action.escu.data_models = [] -action.escu.eli5 = 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 -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. Run the "Previously seen users in CloudTrail" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run "Update previously seen users in CloudTrail" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines. -action.escu.known_false_positives = When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate. -action.escu.creation_date = 2018-04-30 -action.escu.modification_date = 2018-04-30 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect AWS Console Login by User from New Country - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious AWS Login Activities"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect AWS Console Login by User from New Country - Rule -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 -action.notable.param.rule_title = Detect AWS Console Login by User from New Country -action.notable.param.security_domain = network -action.notable.param.severity = high -alert.digest_mode = 1 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = | inputlookup previously_seen_users_console_logins.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by user Country | join user type=outer [| inputlookup previously_seen_users_console_logins.csv | stats min(firstTime) AS earliestseen by user | fields earliestseen user] | eval userStatus=if(firstTime >= relative_time(now(), "@d"), "New Country","Previously Seen Country") | eval UserData=if(earliestseen >= relative_time(now(), "@d") OR isnull(earliestseen), "New User","Old User") | where userStatus="New Country" AND UserData="Old User" | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`|`security_content_ctime(earliestseen)` | table user Country userStatus firstTime lastTime earliestseen | `detect_aws_console_login_by_user_from_new_country_filter` - -[ESCU - Detect AWS Console Login by User from New Region - Rule] -action.escu = 0 -action.escu.enabled = 1 -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 -action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} -action.escu.data_models = [] -action.escu.eli5 = 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 -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. Run the "Previously seen users in CloudTrail" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run "Update previously seen users in CloudTrail" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines. -action.escu.known_false_positives = When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate. -action.escu.creation_date = 2018-04-30 -action.escu.modification_date = 2018-04-30 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect AWS Console Login by User from New Region - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious AWS Login Activities"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect AWS Console Login by User from New Region - Rule -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 -action.notable.param.rule_title = Detect AWS Console Login by User from New Region -action.notable.param.security_domain = network -action.notable.param.severity = high -alert.digest_mode = 1 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = | inputlookup previously_seen_users_console_logins.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by user Region | join user type=outer [| inputlookup previously_seen_users_console_logins.csv | stats min(firstTime) AS earliestseen by user | fields earliestseen user] | eval userStatus=if(firstTime >= relative_time(now(), "@d"), "New Region","Previously Seen Region") | eval UserData=if(earliestseen >= relative_time(now(), "@d") OR isnull(earliestseen), "New User","Old User") | where userStatus="New Region" AND UserData="Old User" | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `security_content_ctime(earliestseen)` | table user Region userStatus firstTime lastTime earliestseen | `detect_aws_console_login_by_user_from_new_region_filter` - -[ESCU - Detect Activity Related to Pass the Hash Attacks - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1075"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} -action.escu.data_models = [] -action.escu.eli5 = 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.escu.how_to_implement = To successfully implement this search, you must ingest your Windows Security Event logs and leverage the latest TA for Windows. -action.escu.known_false_positives = Legitimate logon activity by authorized NTLM systems may be detected by this search. Please investigate as appropriate. -action.escu.creation_date = 2020-01-09 -action.escu.modification_date = 2020-01-09 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect Activity Related to Pass the Hash Attacks - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Lateral Movement"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect Activity Related to Pass the Hash Attacks - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `wineventlog_security` EventCode=4624 (Logon_Type=3 LogonProcessName=NtLmSsp WorkstationName=WORKSTATION NOT AccountName="ANONYMOUS LOGON") OR (EventCode=4624 Logon_Type=9 LogonProcessName=seclogo) | stats count min(_time) as firstTime max(_time) as lastTime by EventCode, Logon_Type, WorkstationName, user, dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `detect_activity_related_to_pass_the_hash_attacks_filter` - -[ESCU - Detect Credential Dumping through LSASS access - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for reading lsass memory consistent with credential dumping. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["PR.IP", "PR.AC", "DE.CM"]} -action.escu.data_models = [] -action.escu.eli5 = This search looks for reading lsass memory consistent with credential dumping. -action.escu.how_to_implement = This search needs Sysmon Logs and a sysmon configuration, which includes EventCode 10 with lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon 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. -action.escu.known_false_positives = The activity may be legitimate. Other tools can access lsass for legitimate reasons, and it's possible this event could be generated in those cases. In these cases, false positives should be fairly obvious and you may need to tweak the search to eliminate noise. -action.escu.creation_date = 2019-12-03 -action.escu.modification_date = 2019-12-03 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect Credential Dumping through LSASS access - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Credential Dumping"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect Credential Dumping through LSASS access - Rule -schedule_window = auto -action.notable = 1 -action.notable.param.nes_fields = ['dest'] -action.notable.param.rule_description = This search looks for reading lsass memory consistent with credential dumping. -action.notable.param.rule_title = Detect Credential Dumping through LSASS access -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -alert.digest_mode = 1 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `sysmon` EventCode=10 TargetImage=*lsass.exe (GrantedAccess=0x1010 OR GrantedAccess=0x1410) | stats count min(_time) as firstTime max(_time) as lastTime by Computer, SourceImage, SourceProcessId, TargetImage, TargetProcessId, EventCode, GrantedAccess | rename Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `detect_credential_dumping_through_lsass_access_filter` - -[ESCU - Detect DNS requests to Phishing Sites leveraging EvilGinx2 - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for DNS requests for phishing domains that are leveraging EvilGinx tools to mimic websites. -action.escu.mappings = {"cis20": ["CIS 8", "CIS 7"], "kill_chain_phases": ["Delivery", "Command and Control"], "mitre_attack": ["T1192"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"]} -action.escu.data_models = ["Network_Resolution"] -action.escu.eli5 = This search looks for DNS requests for phishing domains that are leveraging EvilGinx tools to mimic websites. -action.escu.how_to_implement = You need to ingest data from your DNS logs in the Network_Resolution datamodel. Specifically you must ingest the domain that is being queried and the IP of the host originating the request. Ideally, you should also be ingesting the answer to the query and the query type. This approach allows you to also create your own localized passive DNS capability which can aid you in future investigations. You will have to add legitimate domain names to the `legit_domains.csv` file shipped with the app. \ - **Splunk>Phantom Playbook Integration**\ -If Splunk>Phantom is also configured in your environment, a Playbook called `Lets Encrypt Domain Investigate` can be configured to run when any results are found by this detection search. 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/lets-encrypt-domain-investigate/`).\ - -action.escu.known_false_positives = If a known good domain is not listed in the legit_domains.csv file, then the search could give you false postives. Please update that lookup file to filter out DNS requests to legitimate domains. -action.escu.creation_date = 2019-04-29 -action.escu.modification_date = 2019-04-29 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect DNS requests to Phishing Sites leveraging EvilGinx2 - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Common Phishing Frameworks"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect DNS requests to Phishing Sites leveraging EvilGinx2 - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 values(DNS.answer) as answer from datamodel=Network_Resolution.DNS by DNS.dest DNS.src DNS.query host | `drop_dm_object_name(DNS)`| rex field=query ".*?(?[^./:]+\.(\S{2,3}|\S{2,3}.\S{2,3}))$" | stats count values(query) as query by domain dest src answer| search `evilginx_phishlets_amazon` OR `evilginx_phishlets_facebook` OR `evilginx_phishlets_github` OR `evilginx_phishlets_0365` OR `evilginx_phishlets_outlook` OR `evilginx_phishlets_aws` OR `evilginx_phishlets_google` | search NOT [ inputlookup legit_domains.csv | fields domain]| join domain type=outer [| tstats count `security_content_summariesonly` values(Web.url) as url from datamodel=Web.Web by Web.dest Web.site | rename "Web.*" as * | rex field=site ".*?(?[^./:]+\.(\S{2,3}|\S{2,3}.\S{2,3}))$" | table dest domain url] | table count src dest query answer domain url | `detect_dns_requests_to_phishing_sites_leveraging_evilginx2_filter` - -[ESCU - Detect Excessive Account Lockouts From Endpoint - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search identifies endpoints that have caused a relatively high number of account lockouts in a short period. -action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["PR.IP"]} -action.escu.data_models = ["Change"] -action.escu.eli5 = This search identifies endpoints that have caused a relatively high number of account lockouts in a short period. -action.escu.how_to_implement = You must ingest your Windows security event logs in the `Change` datamodel under the nodename is `Account_Management`, for this search to execute successfully. Please consider updating the cron schedule and the count of lockouts you want to monitor, according to your environment. \ - **Splunk>Phantom Playbook Integration**\ -If Splunk>Phantom is also configured in your environment, a Playbook called "Excessive Account Lockouts Enrichment and Response" can be configured to run when any results are found by this detection search. The Playbook executes the Contextual and Investigative searches in this Story, conducts additional information gathering on Windows endpoints, and takes a response action to shut down the affected endpoint. 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/4.1/playbook/excessive-account-lockouts-enrichment-and-response/`).\ - -action.escu.known_false_positives = It's possible that a widely used system, such as a kiosk, could cause a large number of account lockouts. -action.escu.creation_date = 2019-04-18 -action.escu.modification_date = 2019-04-18 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect Excessive Account Lockouts From Endpoint - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Account Monitoring and Controls"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect Excessive Account Lockouts From Endpoint - Rule -schedule_window = auto -action.notable = 1 -action.notable.param.nes_fields = ['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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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=Change.All_Changes where nodename=All_Changes.Account_Management All_Changes.result="lockout" by All_Changes.dest All_Changes.result |`drop_dm_object_name("All_Changes")` |`drop_dm_object_name("Account_Management")`| `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | search count > 5 | `detect_excessive_account_lockouts_from_endpoint_filter` - -[ESCU - Detect Excessive User Account Lockouts - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search detects user accounts that have been locked out a relatively high number of times in a short period. -action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["PR.IP"]} -action.escu.data_models = ["Change"] -action.escu.eli5 = This search detects user accounts that have been locked out a relatively high number of times in a short period. -action.escu.how_to_implement = ou must ingest your Windows security event logs in the `Change` datamodel under the nodename is `Account_Management`, for this search to execute successfully. Please consider updating the cron schedule and the count of lockouts you want to monitor, according to your environment. -action.escu.known_false_positives = It is possible that a legitimate user is experiencing an issue causing multiple account login failures leading to lockouts. -action.escu.creation_date = 2019-03-01 -action.escu.modification_date = 2019-03-01 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect Excessive User Account Lockouts - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Account Monitoring and Controls"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect Excessive User Account Lockouts - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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=Change.All_Changes where nodename=All_Changes.Account_Management All_Changes.result="lockout" by All_Changes.user All_Changes.result |`drop_dm_object_name("All_Changes")` |`drop_dm_object_name("Account_Management")`| `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | search count > 5 | `detect_excessive_user_account_lockouts_filter` - -[ESCU - Detect Large Outbound ICMP Packets - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1095"], "nist": ["DE.AE"]} -action.escu.data_models = ["Network_Traffic"] -action.escu.eli5 = 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.escu.how_to_implement = In order to run this search effectively, we highly recommend that you leverage the Assets and Identity framework. It is important that you have a good understanding of how your network segments are designed and that you are able to distinguish internal from external address space. Add a category named `internal` to the CIDRs that host the company's assets in the `assets_by_cidr.csv` lookup file, which is located in `$SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/`. More information on updating this lookup can be found here: https://docs.splunk.com/Documentation/ES/5.0.0/Admin/Addassetandidentitydata. This search also requires you to be ingesting your network traffic and populating the Network_Traffic data model -action.escu.known_false_positives = ICMP packets are used in a variety of ways to help troubleshoot networking issues and ensure the proper flow of traffic. As such, it is possible that a large ICMP packet could be perfectly legitimate. If large ICMP packets are associated with command and control traffic, there will typically be a large number of these packets observed over time. If the search is providing a large number of false positives, you can modify the search to adjust the byte threshold or whitelist specific IP addresses, as necessary. -action.escu.creation_date = 2018-06-01 -action.escu.modification_date = 2018-06-01 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect Large Outbound ICMP Packets - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Command and Control"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect Large Outbound ICMP Packets - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 earliest(_time) as firstTime latest(_time) as lastTime values(All_Traffic.action) values(All_Traffic.bytes) from datamodel=Network_Traffic where All_Traffic.action !=blocked All_Traffic.dest_category !=internal (All_Traffic.protocol=icmp OR All_Traffic.transport=icmp) All_Traffic.bytes > 1000 by All_Traffic.src_ip All_Traffic.dest_ip | `drop_dm_object_name("All_Traffic")` | search ( dest_ip!=10.0.0.0/8 AND dest_ip!=172.16.0.0/12 AND dest_ip!=192.168.0.0/16) | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | `detect_large_outbound_icmp_packets_filter` - -[ESCU - Detect Long DNS TXT Record Response - Rule] -action.escu = 0 -action.escu.enabled = 1 -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. -action.escu.mappings = {"cis20": ["CIS 8", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1043"], "nist": ["PR.DS", "PR.PT", "DE.AE", "DE.CM"]} -action.escu.data_models = ["Network_Resolution"] -action.escu.eli5 = 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. -action.escu.how_to_implement = To successfully implement this search you need to ingest data from your DNS logs, or monitor DNS traffic using Stream, Bro or something similar. Specifically, this query requires that the DNS data model is populated with information regarding the DNS record type that is being returned as well as the data in the answer section of the protocol. -action.escu.known_false_positives = It's possible that legitimate TXT record responses can be long enough to trigger this search. You can modify the packet threshold for this search to help mitigate false positives. -action.escu.creation_date = 2017-09-18 -action.escu.modification_date = 2017-09-18 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect Long DNS TXT Record Response - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Command and Control", "Suspicious DNS Traffic"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect Long DNS TXT Record Response - Rule -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. -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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=Network_Resolution where DNS.message_type=response AND DNS.record_type=TXT by DNS.src DNS.dest DNS.answer DNS.record_type | `drop_dm_object_name("DNS")` | eval anslen=len(answer) | search anslen>100 | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | rename src as "Source IP", dest as "Destination IP", answer as "DNS Answer" anslen as "Answer Length" record_type as "DNS Record Type" firstTime as "First Time" lastTime as "Last Time" count as Count | table "Source IP" "Destination IP" "DNS Answer" "DNS Record Type" "Answer Length" Count "First Time" "Last Time" | `detect_long_dns_txt_record_response_filter` - -[ESCU - Detect Mimikatz Using Loaded Images - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for reading loaded Images unique to credential dumping with Mimikatz. -action.escu.mappings = {"cis20": ["CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.AE", "DE.CM"]} -action.escu.data_models = [] -action.escu.eli5 = This search looks for reading loaded Images unique to credential dumping with Mimikatz. -action.escu.how_to_implement = This search needs Sysmon Logs and a sysmon configuration, which includes EventCode 7 with powershell.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon 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. -action.escu.known_false_positives = Other tools can import the same DLLs. These tools should be part of a whtelist. -action.escu.creation_date = 2019-12-03 -action.escu.modification_date = 2019-12-03 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect Mimikatz Using Loaded Images - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Credential Dumping"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect Mimikatz Using Loaded Images - Rule -schedule_window = auto -action.notable = 1 -action.notable.param.nes_fields = ['dest'] -action.notable.param.rule_description = This search looks for reading loaded Images unique to credential dumping with Mimikatz. -action.notable.param.rule_title = Detect Mimikatz Using Loaded Images -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -alert.digest_mode = 1 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `sysmon` EventCode=7 | stats values(ImageLoaded) as ImageLoaded values(ProcessId) as ProcessId by Computer, Image | search ImageLoaded=*WinSCard.dll ImageLoaded=*cryptdll.dll ImageLoaded=*hid.dll ImageLoaded=*samlib.dll ImageLoaded=*vaultcli.dll | rename Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `detect_mimikatz_using_loaded_images_filter` - -[ESCU - Detect Mimikatz Via PowerShell And EventCode 4703 - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for PowerShell requesting privileges consistent with credential dumping. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["PR.IP", "PR.AC", "DE.CM"]} -action.escu.data_models = [] -action.escu.eli5 = This search looks for PowerShell requesting privileges consistent with credential dumping. -action.escu.how_to_implement = You must be ingesting Windows Security logs. You must also enable the account change auditing here: http://docs.splunk.com/Documentation/Splunk/7.0.2/Data/MonitorWindowseventlogdata. Additionally, this search requires you to enable your Group Management Audit Logs in your Local Windows Security Policy and to be ingesting those logs. More information on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/. Finally, please make sure that the local administrator group name is "Administrators" to be able to look for the right group membership changes. -action.escu.known_false_positives = The activity may be legitimate. PowerShell is often used by administrators to perform various tasks, and it's possible this event could be generated in those cases. In these cases, false positives should be fairly obvious and you may need to tweak the search to eliminate noise. -action.escu.creation_date = 2019-02-27 -action.escu.modification_date = 2019-02-27 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect Mimikatz Via PowerShell And EventCode 4703 - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = [] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect Mimikatz Via PowerShell And EventCode 4703 - Rule -schedule_window = auto -action.notable = 1 -action.notable.param.rule_description = This search looks for PowerShell requesting privileges consistent with credential dumping. -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `wineventlog_security` signature_id=4703 Process_Name=*powershell.exe | rex field=Message "Enabled Privileges:\s+(?\w+)\s+Disabled Privileges:" | where privs="SeDebugPrivilege" | stats count min(_time) as firstTime max(_time) as lastTime by dest, Process_Name, privs, Process_ID, Message | rename privs as "Enabled Privilege" | rename Process_Name as process | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `detect_mimikatz_via_powershell_and_eventcode_4703_filter` - -[ESCU - Detect New Local Admin account - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for newly created accounts that have been elevated to local administrators. -action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1078"], "nist": ["PR.AC", "DE.CM"]} -action.escu.data_models = [] -action.escu.eli5 = This search looks for newly created accounts that have been elevated to local administrators. -action.escu.how_to_implement = You must be ingesting Windows Security logs. You must also enable the account change auditing here:http://docs.splunk.com/Documentation/Splunk/7.0.2/Data/MonitorWindowseventlogdata. Additionally, this search requires you to enable your Group Management Audit Logs in your Local Windows Security Policy and to be ingesting those logs. More information on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/. Finally, please make sure that the local administrator group name is "Administrators" to be able to look for the right group membership changes.\ -This search produces fields (`Security_ID`,`Group_Name`,`Message`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** Security ID, **Field:** Security_ID\ -1. \ -1. **Label:** Group Name, **Field:** Group_Name\ -1. \ -1. **Label:** Message, **Field:** Message\ -Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -action.escu.known_false_positives = The activity may be legitimate. For this reason, it's best to verify the account with an administrator and ask whether there was a valid service request for the account creation. If your local administrator group name is not "Administrators", this search may generate an excessive number of false positives -action.escu.creation_date = 2019-02-28 -action.escu.modification_date = 2019-02-28 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect New Local Admin account - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["DHS Report TA18-074A"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect New Local Admin account - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `wineventlog_security` signature_id=4720 OR (signature_id=4732 Group_Name= Administrators) | transaction Security_ID connected=false maxspan=180m | search signature_id=4720 signature_id=4732 | table _time user dest signature_id Security_ID Group_Name src_user Message | `detect_new_local_admin_account_filter` - -[ESCU - Detect New Login Attempts to Routers - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "PR.AC", "PR.IP"]} -action.escu.data_models = ["Authentication"] -action.escu.eli5 = 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.escu.how_to_implement = To successfully implement this search, you must ensure the network router devices are categorized as "router" in the Assets and identity table. You must also populate the Authentication data model with logs related to users authenticating to routing infrastructure. -action.escu.known_false_positives = Legitimate router connections may appear as new connections -action.escu.creation_date = 2017-09-12 -action.escu.modification_date = 2017-09-12 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect New Login Attempts to Routers - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Router and Infrastructure Security"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect New Login Attempts to Routers - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 earliest(_time) as earliest latest(_time) as latest from datamodel=Authentication where Authentication.dest_category=router by Authentication.dest Authentication.user| eval isOutlier=if(earliest >= relative_time(now(), "-30d@d"), 1, 0) | where isOutlier=1| `security_content_ctime(earliest)`| `security_content_ctime(latest)` | `drop_dm_object_name("Authentication")` | `detect_new_login_attempts_to_routers_filter` - -[ESCU - Detect New Open S3 buckets - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for CloudTrail events where a user has created an open/public S3 bucket. -action.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS", "PR.AC", "DE.CM"]} -action.escu.data_models = [] -action.escu.eli5 = This search looks for CloudTrail events where a user has created an open/public S3 bucket. -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), and then configure your CloudTrail inputs. The threshold value should be tuned to your environment. -action.escu.known_false_positives = While this search has no known false positives, it is possible that an AWS admin has legitimately created a public bucket for a specific purpose. That said, AWS strongly advises against granting full control to the "All Users" group. -action.escu.creation_date = 2018-07-25 -action.escu.modification_date = 2018-07-25 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect New Open S3 buckets - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious AWS S3 Activities"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect New Open S3 buckets - Rule -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 has created an open/public S3 bucket. -action.notable.param.rule_title = Detect New Open S3 buckets -action.notable.param.security_domain = network -action.notable.param.severity = high -alert.digest_mode = 1 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `cloudtrail` AllUsers eventName=PutBucketAcl | spath output=userIdentityArn path=userIdentity.arn | spath output=bucketName path=requestParameters.bucketName | spath output=aclControlList path=requestParameters.AccessControlPolicy.AccessControlList | spath input=aclControlList output=grantee path=Grant{} | mvexpand grantee | spath input=grantee | search Grantee.URI=*AllUsers | rename userIdentityArn as user| table _time, src,awsRegion Permission, Grantee.URI, bucketName, user | `detect_new_open_s3_buckets_filter` - -[ESCU - Detect Oulook exe writing a zip file - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for execution of process `outlook.exe` where the process is writing a `.zip` file to the disk. -action.escu.mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1193"], "nist": ["ID.AM", "PR.DS"]} -action.escu.data_models = [] -action.escu.eli5 = This search looks for execution of process `outlook.exe` where the process is writing a `.zip` file to the disk. -action.escu.how_to_implement = You must be ingesting data that records filesystem and process activity from your hosts to populate the Endpoint data model. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. -action.escu.known_false_positives = It is not uncommon for outlook to write legitimate zip files to the disk. -action.escu.creation_date = 2020-03-16 -action.escu.modification_date = 2020-03-16 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect Oulook exe writing a zip file - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Phishing Payloads"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect Oulook exe writing a zip file - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = | tstats `security_content_summariesonly` min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes where Processes.process_name=outlook.exe OR Processes.process_name=explorer.exe by _time span=5m Processes.parent_process_id Processes.process_id Processes.dest Processes.process_name Processes.parent_process_name Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | rename process_id as malicious_id| rename parent_process_id as outlook_id| join malicious_id type=inner[| tstats `security_content_summariesonly` count values(Filesystem.file_path) as file_path values(Filesystem.file_name) as file_name FROM datamodel=Endpoint.Filesystem where (Filesystem.file_path=*zip* OR Filesystem.file_name=*.lnk ) AND (Filesystem.file_path=C:\\Users* OR Filesystem.file_path=*Local\\Temp*) by _time span=5m Filesystem.process_id Filesystem.file_hash Filesystem.dest | `drop_dm_object_name(Filesystem)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | rename process_id as malicious_id| fields malicious_id outlook_id dest file_path file_name file_hash count file_id] | table firstTime lastTime user malicious_id outlook_id process_name parent_process_name file_name file_path | where file_name != "" | `detect_oulook_exe_writing_a__zip_file_filter` - -[ESCU - Detect Outbound SMB Traffic - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -action.escu.data_models = ["Network_Traffic"] -action.escu.eli5 = 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.escu.how_to_implement = In order to run this search effectively, we highly recommend that you leverage the Assets and Identity framework. It is important that you have good understanding of how your network segments are designed, and be able to distinguish internal from external address space. Add a category named `internal` to the CIDRs that host the company's assets in `assets_by_cidr.csv` lookup file, which is located in `$SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/`. More information on updating this lookup can be found here: https://docs.splunk.com/Documentation/ES/5.0.0/Admin/Addassetandidentitydata. This search also requires you to be ingesting your network traffic and populating the Network_Traffic data model -action.escu.known_false_positives = It is likely that the outbound Server Message Block (SMB) traffic is legitimate, if the company's internal networks are not well-defined in the Assets and Identity Framework. Categorize the internal CIDR blocks as `internal` in the lookup file to avoid creating notable events for traffic destined to those CIDR blocks. Any other network connection that is going out to the Internet should be investigated and blocked. Best practices suggest preventing external communications of all SMB versions and related protocols at the network boundary. -action.escu.creation_date = 2020-01-22 -action.escu.modification_date = 2020-01-22 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect Outbound SMB Traffic - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Hidden Cobra Malware", "DHS Report TA18-074A"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect Outbound SMB Traffic - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 earliest(_time) as earliest latest(_time) as latest values(All_Traffic.action) from datamodel=Network_Traffic where All_Traffic.action !=blocked All_Traffic.dest_category !=internal (All_Traffic.dest_port=139 OR All_Traffic.dest_port=445 OR All_Traffic.app=smb) by All_Traffic.src_ip All_Traffic.dest_ip | `drop_dm_object_name("All_Traffic")` | search ( dest_ip!=10.0.0.0/8 AND dest_ip!=172.16.0.0/12 AND dest_ip!=192.168.0.0/16) | `security_content_ctime(earliest)`| `security_content_ctime(latest)` | `detect_outbound_smb_traffic_filter` - -[ESCU - Detect Path Interception By Creation Of program exe - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = The search is looking for the creation of program.exe in the C: drive. The creation of this file in that location may be driven by a motive to perform path interception. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = The search is looking for the creation of program.exe in the C: drive. The creation of this file in that location may be driven by a motive to perform path interception. -action.escu.how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file system reads and writes. -action.escu.known_false_positives = It is unlikely that a normal user may create and place this file in the C: drive. Confirm with the user. -action.escu.creation_date = 2018-11-15 -action.escu.modification_date = 2018-11-15 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect Path Interception By Creation Of program exe - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Windows Persistence Techniques"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect Path Interception By Creation Of program exe - Rule -schedule_window = auto -action.notable = 1 -action.notable.param.nes_fields = ['user', 'dest'] -action.notable.param.rule_description = The search is looking for the creation of program.exe in the C: drive. The creation of this file in that location may be driven by a motive to perform path interception. -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_hash) as file_hash values(Filesystem.file_path) as file_path from datamodel=Endpoint.Filesystem where Filesystem.file_path="C:\\program.exe" by Filesystem.file_name | `drop_dm_object_name(Filesystem)` | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `detect_path_interception_by_creation_of_program_exe_filter` - -[ESCU - Detect Prohibited Applications Spawning cmd exe - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = 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.escu.how_to_implement = You must be ingesting data that records process activity from your hosts and populates the Endpoint data model with the resultant dataset. This search includes a lookup file, `prohibited_apps_launching_cmd.csv`, that contains a list of processes that should not be spawning cmd.exe. You can modify this lookup to better suit your environment. -action.escu.known_false_positives = There are circumstances where an application may legitimately execute and interact with the Windows command-line interface. Investigate and modify the lookup file, as appropriate. -action.escu.creation_date = 2020-02-03 -action.escu.modification_date = 2020-02-03 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect Prohibited Applications Spawning cmd exe - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Command-Line Executions", "Suspicious MSHTA Activity"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect Prohibited Applications Spawning cmd exe - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=cmd.exe by Processes.parent_process_name Processes.process_name Processes.dest Processes.user| `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` |search [`prohibited_apps_launching_cmd`] | `detect_prohibited_applications_spawning_cmd_exe_filter` - -[ESCU - Detect PsExec With accepteula Flag - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = 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.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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -action.escu.known_false_positives = Administrators can leverage PsExec for accessing remote systems and might pass `accepteula` as an argument if they are running this tool for the first time. However, it is not likely that you'd see multiple occurrences of this event on a machine -action.escu.creation_date = 2019-02-26 -action.escu.modification_date = 2019-02-26 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect PsExec With accepteula Flag - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["SamSam Ransomware", "DHS Report TA18-074A"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect PsExec With accepteula Flag - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = | tstats `security_content_summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = PsExec.exe Processes.process = "*accepteula*" by Processes.process_name Processes.dest Processes.parent_process_name | `drop_dm_object_name(Processes)`| `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `detect_psexec_with_accepteula_flag_filter` - -[ESCU - Detect Rare Executables - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.PT", "PR.DS", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search will return a table of rare processes, the names of the systems running them, and the users who initiated each process. -action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts and populating the endpoint data model with the resultant dataset. The macro `filter_rare_process_whitelist` searches two lookup files to whitelist your processes. These consist of `rare_process_whitelist_default.csv` and `rare_process_whitelist_local.csv`. To add your own processes to the whitelist, add them to `rare_process_whitelist_local.csv`. If you wish to remove an entry from the default lookup file, you will have to modify the macro itself to set the whitelist value for that process to false. You can modify the limit parameter and search scheduling to better suit your environment. -action.escu.known_false_positives = Some legitimate processes may be only rarely executed in your environment. As these are identified, update `rare_process_whitelist_local.csv` to filter them out of your search results. -action.escu.creation_date = 2020-03-16 -action.escu.modification_date = 2020-03-16 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect Rare Executables - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Emotet Malware DHS Report TA18-201A ", "Unusual Processes"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect Rare Executables - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 values(Processes.dest) as dest values(Processes.user) as user min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes by Processes.process_name | rename Processes.process_name as process | rex field=user "(?.*)\\\\(?.*)" | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| search [| tstats count from datamodel=Endpoint.Processes by Processes.process_name | rare Processes.process_name limit=30 | rename Processes.process_name as process| `filter_rare_process_whitelist`| table process ] | `detect_rare_executables_filter` - -[ESCU - Detect S3 access from a new IP - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS", "PR.AC", "DE.CM"]} -action.escu.data_models = [] -action.escu.eli5 = 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.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. This search works best when you run the "Previously Seen S3 Bucket Access by Remote IP" support search once to create a history of previously seen remote IPs and bucket names. -action.escu.known_false_positives = S3 buckets can be accessed from any IP, as long as it can make a successful connection. This will be a false postive, since the search is looking for a new IP within the past hour -action.escu.creation_date = 2018-06-28 -action.escu.modification_date = 2018-06-28 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect S3 access from a new IP - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious AWS S3 Activities"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect S3 access from a new IP - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `aws_s3_accesslogs` http_status=200 [search `aws_s3_accesslogs` http_status=200 | stats earliest(_time) as firstTime latest(_time) as lastTime by bucket_name remote_ip | inputlookup append=t previously_seen_S3_access_from_remote_ip.csv | stats min(firstTime) as firstTime, max(lastTime) as lastTime by bucket_name remote_ip | outputlookup previously_seen_S3_access_from_remote_ip.csv | eval newIP=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newIP=1 | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | table bucket_name remote_ip]| iplocation remote_ip |rename remote_ip as src_ip | table _time bucket_name src_ip City Country operation request_uri | `detect_s3_access_from_a_new_ip_filter` - -[ESCU - Detect Spike in AWS API Activity - Rule] -action.escu = 0 -action.escu.enabled = 1 -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. -action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC"]} -action.escu.data_models = [] -action.escu.eli5 = 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. -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. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike.\ -This search produces fields (`eventName`,`numberOfApiCalls`,`uniqueApisCalled`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** AWS Event Name, **Field:** eventName\ -1. \ -1. **Label:** Number of API Calls, **Field:** numberOfApiCalls\ -1. \ -1. **Label:** Unique API Calls, **Field:** uniqueApisCalled\ -Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -action.escu.known_false_positives = -action.escu.creation_date = 2018-04-09 -action.escu.modification_date = 2018-04-09 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect Spike in AWS API Activity - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["AWS User Monitoring"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect Spike in AWS API Activity - Rule -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. -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `cloudtrail` eventType=AwsApiCall [search `cloudtrail` eventType=AwsApiCall | spath output=arn path=userIdentity.arn | stats count as apiCalls by arn | inputlookup api_call_by_user_baseline append=t | fields - latestCount | stats values(*) as * by arn | rename apiCalls as latestCount | eval newAvgApiCalls=avgApiCalls + (latestCount-avgApiCalls)/720 | eval newStdevApiCalls=sqrt(((pow(stdevApiCalls, 2)*719 + (latestCount-newAvgApiCalls)*(latestCount-avgApiCalls))/720)) | eval avgApiCalls=coalesce(newAvgApiCalls, avgApiCalls), stdevApiCalls=coalesce(newStdevApiCalls, stdevApiCalls), numDataPoints=if(isnull(latestCount), numDataPoints, numDataPoints+1) | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup api_call_by_user_baseline | eval dataPointThreshold = 15, deviationThreshold = 3 | eval isSpike=if((latestCount > avgApiCalls+deviationThreshold*stdevApiCalls) AND numDataPoints > dataPointThreshold, 1, 0) | where isSpike=1 | rename arn as userIdentity.arn | table userIdentity.arn] | spath output=user userIdentity.arn | stats values(eventName) as eventName, count as numberOfApiCalls, dc(eventName) as uniqueApisCalled by user | `detect_spike_in_aws_api_activity_filter` - -[ESCU - Detect Spike in Network ACL Activity - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search will detect users creating spikes in API activity related to network access-control lists (ACLs)in your AWS environment. -action.escu.mappings = {"cis20": ["CIS 12", "CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC"]} -action.escu.data_models = [] -action.escu.eli5 = This search will detect users creating spikes in API activity related to network access-control lists (ACLs)in your AWS environment. -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. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike. This search works best when you run the "Baseline of Network ACL Activity by ARN" support search once to create a lookup file of previously seen Network ACL Activity. To add or remove API event names related to network ACLs, edit the macro `network_acl_events`. -action.escu.known_false_positives = The false-positive rate may vary based on the values of`dataPointThreshold` and `deviationThreshold`. Please modify this according the your environment. -action.escu.creation_date = 2018-05-21 -action.escu.modification_date = 2018-05-21 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect Spike in Network ACL Activity - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["AWS Network ACL Activity"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect Spike in Network ACL Activity - Rule -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. -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `cloudtrail` `network_acl_events` [search `cloudtrail` `network_acl_events` | spath output=arn path=userIdentity.arn | stats count as apiCalls by arn | inputlookup network_acl_activity_baseline append=t | fields - latestCount | stats values(*) as * by arn | rename apiCalls as latestCount | eval newAvgApiCalls=avgApiCalls + (latestCount-avgApiCalls)/720 | eval newStdevApiCalls=sqrt(((pow(stdevApiCalls, 2)*719 + (latestCount-newAvgApiCalls)*(latestCount-avgApiCalls))/720)) | eval avgApiCalls=coalesce(newAvgApiCalls, avgApiCalls), stdevApiCalls=coalesce(newStdevApiCalls, stdevApiCalls), numDataPoints=if(isnull(latestCount), numDataPoints, numDataPoints+1) | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup network_acl_activity_baseline | eval dataPointThreshold = 15, deviationThreshold = 3 | eval isSpike=if((latestCount > avgApiCalls+deviationThreshold*stdevApiCalls) AND numDataPoints > dataPointThreshold, 1, 0) | where isSpike=1 | rename arn as userIdentity.arn | table userIdentity.arn] | spath output=user userIdentity.arn | stats values(eventName) as eventNames, count as numberOfApiCalls, dc(eventName) as uniqueApisCalled by user | `detect_spike_in_network_acl_activity_filter` - -[ESCU - Detect Spike in S3 Bucket deletion - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC"]} -action.escu.data_models = [] -action.escu.eli5 = 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.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. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike. This search works best when you run the "Baseline of S3 Bucket deletion activity by ARN" support search once to create a baseline of previously seen S3 bucket-deletion activity. -action.escu.known_false_positives = Based on the values of`dataPointThreshold` and `deviationThreshold`, the false positive rate may vary. Please modify this according the your environment. -action.escu.creation_date = 2018-11-27 -action.escu.modification_date = 2018-11-27 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect Spike in S3 Bucket deletion - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious AWS S3 Activities"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect Spike in S3 Bucket deletion - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `cloudtrail` eventName=DeleteBucket [search `cloudtrail` eventName=DeleteBucket | spath output=arn path=userIdentity.arn | stats count as apiCalls by arn | inputlookup s3_deletion_baseline append=t | fields - latestCount | stats values(*) as * by arn | rename apiCalls as latestCount | eval newAvgApiCalls=avgApiCalls + (latestCount-avgApiCalls)/720 | eval newStdevApiCalls=sqrt(((pow(stdevApiCalls, 2)*719 + (latestCount-newAvgApiCalls)*(latestCount-avgApiCalls))/720)) | eval avgApiCalls=coalesce(newAvgApiCalls, avgApiCalls), stdevApiCalls=coalesce(newStdevApiCalls, stdevApiCalls), numDataPoints=if(isnull(latestCount), numDataPoints, numDataPoints+1) | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup s3_deletion_baseline | eval dataPointThreshold = 15, deviationThreshold = 3 | eval isSpike=if((latestCount > avgApiCalls+deviationThreshold*stdevApiCalls) AND numDataPoints > dataPointThreshold, 1, 0) | where isSpike=1 | rename arn as userIdentity.arn | table userIdentity.arn] | spath output=user userIdentity.arn | spath output=bucketName path=requestParameters.bucketName | stats values(bucketName) as bucketName, count as numberOfApiCalls, dc(eventName) as uniqueApisCalled by user | `detect_spike_in_s3_bucket_deletion_filter` - -[ESCU - Detect Spike in Security Group Activity - Rule] -action.escu = 0 -action.escu.enabled = 1 -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. -action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC"]} -action.escu.data_models = [] -action.escu.eli5 = 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. -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. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike.This search works best when you run the "Baseline of Security Group Activity by ARN" support search once to create a history of previously seen Security Group Activity. To add or remove API event names for security groups, edit the macro `security_group_api_calls`. -action.escu.known_false_positives = Based on the values of`dataPointThreshold` and `deviationThreshold`, the false positive rate may vary. Please modify this according the your environment. -action.escu.creation_date = 2018-04-18 -action.escu.modification_date = 2018-04-18 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect Spike in Security Group Activity - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["AWS User Monitoring"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect Spike in Security Group Activity - Rule -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. -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `cloudtrail` `security_group_api_calls` [search `cloudtrail` `security_group_api_calls` | spath output=arn path=userIdentity.arn | stats count as apiCalls by arn | inputlookup security_group_activity_baseline append=t | fields - latestCount | stats values(*) as * by arn | rename apiCalls as latestCount | eval newAvgApiCalls=avgApiCalls + (latestCount-avgApiCalls)/720 | eval newStdevApiCalls=sqrt(((pow(stdevApiCalls, 2)*719 + (latestCount-newAvgApiCalls)*(latestCount-avgApiCalls))/720)) | eval avgApiCalls=coalesce(newAvgApiCalls, avgApiCalls), stdevApiCalls=coalesce(newStdevApiCalls, stdevApiCalls), numDataPoints=if(isnull(latestCount), numDataPoints, numDataPoints+1) | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup security_group_activity_baseline | eval dataPointThreshold = 15, deviationThreshold = 3 | eval isSpike=if((latestCount > avgApiCalls+deviationThreshold*stdevApiCalls) AND numDataPoints > dataPointThreshold, 1, 0) | where isSpike=1 | rename arn as userIdentity.arn | table userIdentity.arn] | spath output=user userIdentity.arn | stats values(eventName) as eventNames, count as numberOfApiCalls, dc(eventName) as uniqueApisCalled by user | `detect_spike_in_security_group_activity_filter` - -[ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "nist": ["DE.AE", "DE.CM", "PR.AC"]} -action.escu.data_models = [] -action.escu.eli5 = 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.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. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the number of data points required to meet the definition of "spike." The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike. This search works best when you run the "Baseline of Blocked Outbound Connection" support search once to create a history of previously seen blocked outbound connections. -action.escu.known_false_positives = The false-positive rate may vary based on the values of`dataPointThreshold` and `deviationThreshold`. Additionally, false positives may result when AWS administrators roll out policies enforcing network blocks, causing sudden increases in the number of blocked outbound connections. -action.escu.creation_date = 2018-05-07 -action.escu.modification_date = 2018-05-07 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Command and Control", "AWS Network ACL Activity", "Suspicious AWS Traffic"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -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) [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) | stats count as numberOfBlockedConnections by src_ip | inputlookup baseline_blocked_outbound_connections append=t | fields - latestCount | stats values(*) as * by src_ip | rename numberOfBlockedConnections as latestCount | eval newAvgBlockedConnections=avgBlockedConnections + (latestCount-avgBlockedConnections)/720 | eval newStdevBlockedConnections=sqrt(((pow(stdevBlockedConnections, 2)*719 + (latestCount-newAvgBlockedConnections)*(latestCount-avgBlockedConnections))/720)) | eval avgBlockedConnections=coalesce(newAvgBlockedConnections, avgBlockedConnections), stdevBlockedConnections=coalesce(newStdevBlockedConnections, stdevBlockedConnections), numDataPoints=if(isnull(latestCount), numDataPoints, numDataPoints+1) | table src_ip, latestCount, numDataPoints, avgBlockedConnections, stdevBlockedConnections | outputlookup baseline_blocked_outbound_connections | eval dataPointThreshold = 5, deviationThreshold = 3 | eval isSpike=if((latestCount > avgBlockedConnections+deviationThreshold*stdevBlockedConnections) AND numDataPoints > dataPointThreshold, 1, 0) | where isSpike=1 | table src_ip] | stats values(dest_ip) as "Blocked Destination IPs", values(interface_id) as "resourceId" count as numberOfBlockedConnections, dc(dest_ip) as uniqueDestConnections by src_ip | `detect_spike_in_blocked_outbound_traffic_from_your_aws_filter` - -[ESCU - Detect USB device insertion - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "nist": ["PR.PT", "PR.DS"]} -action.escu.data_models = ["Change_Analysis"] -action.escu.eli5 = 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.escu.how_to_implement = To successfully implement this search, you must ingest Windows Security Event logs and track event code 4663 and 4656. Ensure that the field from the event logs is being mapped to the result_id field in the Change_Analysis data model. To minimize the alert volume, this search leverages the Assets and Identity framework to filter out events from those assets not marked high priority in the Enterprise Security Assets and Identity Framework. -action.escu.known_false_positives = Legitimate USB activity will also be detected. Please verify and investigate as appropriate. -action.escu.creation_date = 2017-11-27 -action.escu.modification_date = 2017-11-27 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect USB device insertion - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Data Protection"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect USB device insertion - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 earliest(_time) AS earliest latest(_time) AS latest from datamodel=Change_Analysis where (nodename = All_Changes) All_Changes.result="Removable Storage device" (All_Changes.result_id=4663 OR All_Changes.result_id=4656) (All_Changes.src_priority=high) by All_Changes.dest | `drop_dm_object_name("All_Changes")`| `security_content_ctime(earliest)`| `security_content_ctime(latest)` | `detect_usb_device_insertion_filter` - -[ESCU - Detect Unauthorized Assets by MAC address - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 1"], "kill_chain_phases": ["Reconnaissance", "Delivery", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"]} -action.escu.data_models = ["Network_Sessions"] -action.escu.eli5 = 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.escu.how_to_implement = This search uses the Network_Sessions data model shipped with Enterprise Security. It leverages the Assets and Identity framework to populate the assets_by_str.csv file located in SA-IdentityManagement, which will contain a list of known authorized organizational assets including their MAC addresses. Ensure that all inventoried systems have their MAC address populated. -action.escu.known_false_positives = This search might be prone to high false positives. Please consider this when conducting analysis or investigations. Authorized devices may be detected as unauthorized. If this is the case, verify the MAC address of the system responsible for the false positive and add it to the Assets and Identity framework with the proper information. -action.escu.creation_date = 2017-09-13 -action.escu.modification_date = 2017-09-13 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect Unauthorized Assets by MAC address - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Asset Tracking"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect Unauthorized Assets by MAC address - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 from datamodel=Network_Sessions where nodename=All_Sessions.DHCP All_Sessions.signature=DHCPREQUEST by All_Sessions.src_ip All_Sessions.src_mac | dedup All_Sessions.src_mac| `drop_dm_object_name("Network_Sessions")`|`drop_dm_object_name("All_Sessions")` | search NOT [| inputlookup asset_lookup_by_str |rename mac as src_mac | fields + src_mac] | `detect_unauthorized_assets_by_mac_address_filter` - -[ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = 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.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. -action.escu.known_false_positives = Some legitimate applications may exhibit this behavior. -action.escu.creation_date = 2020-03-02 -action.escu.modification_date = 2020-03-02 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Command-Line Executions", "Emotet Malware DHS Report TA18-201A "] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 values(Processes.process) min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.parent_process_name="cmd.exe" (Processes.process_name=cscript.exe OR Processes.process_name =wscript.exe) by Processes.parent_process Processes.process_name Processes.user Processes.dest | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | `detect_use_of_cmd_exe_to_launch_script_interpreters_filter` - -[ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"kill_chain_phases": ["Reconnaissance"], "mitre_attack": ["T1082"]} -action.escu.data_models = ["Web"] -action.escu.eli5 = 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.escu.how_to_implement = You must be ingesting data from the web server or network traffic that contains web specific information, and populating the Web data model. -action.escu.known_false_positives = It's possible for legitimate HTTP requests to be made to URLs containing the suspicious paths. -action.escu.creation_date = 2017-09-23 -action.escu.modification_date = 2017-09-23 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["SamSam Ransomware", "JBoss Vulnerability"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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=Web where (Web.http_method="GET" OR Web.http_method="HEAD") AND (Web.url="*/web-console/ServerInfo.jsp*" OR Web.url="*web-console*" OR Web.url="*jmx-console*" OR Web.url = "*invoker*") by Web.http_method, Web.url, Web.src, Web.dest | `drop_dm_object_name("Web")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `detect_attackers_scanning_for_vulnerable_jboss_servers_filter` - -[ESCU - Detect hosts connecting to dynamic domain providers - Rule] -action.escu = 0 -action.escu.enabled = 1 -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, blacklists 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.escu.mappings = {"cis20": ["CIS 8", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "nist": ["PR.DS", "PR.PT", "DE.AE", "DE.CM"]} -action.escu.data_models = ["Network_Resolution"] -action.escu.eli5 = 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, blacklists 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.escu.how_to_implement = First, you'll need to ingest data from your DNS operations. This can be done by ingesting logs from your server or data, collected passively by Splunk Stream or a similar solution. Specifically, data that contains the domain that is being queried and the IP of the host originating the request must be populating the `Network_Resolution` data model. This search also leverages a lookup file, `dynamic_dns_providers_default.csv`, which contains a non-exhaustive list of Dynamic DNS providers. Please consider updating the local lookup periodically by adding new domains to the list of `dynamic_dns_providers_local.csv`.\ -This search produces fields (query, answer, isDynDNS) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable event. To see the additional metadata, add the following fields, if not already present, to Incident Review. Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** DNS Query, **Field:** query\ -1. \ -1. **Label:** DNS Answer, **Field:** answer\ -1. \ -1. **Label:** IsDynamicDNS, **Field:** isDynDNS\ -Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -action.escu.known_false_positives = Some users and applications may leverage Dynamic DNS to reach out to some domains on the Internet since dynamic DNS by itself is not malicious, however this activity must be verified. -action.escu.creation_date = 2020-01-16 -action.escu.modification_date = 2020-01-16 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect hosts connecting to dynamic domain providers - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Prohibited Traffic Allowed or Protocol Mismatch", "Suspicious DNS Traffic", "DNS Hijacking", "Dynamic DNS", "Command and Control", "Data Protection"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect hosts connecting to dynamic domain providers - Rule -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, blacklists 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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 values(DNS.answer) as answer min(_time) as firstTime from datamodel=Network_Resolution by DNS.src, DNS.query | `drop_dm_object_name("DNS")` | `security_content_ctime(firstTime)` | `dynamic_dns_providers` | `detect_hosts_connecting_to_dynamic_domain_providers_filter` - -[ESCU - Detect malicious requests to exploit JBoss servers - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 12", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "PR.PT", "PR.IP", "DE.AE", "PR.MA", "DE.CM"]} -action.escu.data_models = ["Web"] -action.escu.eli5 = 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.escu.how_to_implement = You must ingest data from the web server or capture network data that contains web specific information with solutions such as Bro or Splunk Stream, and populating the Web data model -action.escu.known_false_positives = No known false positives for this detection. -action.escu.creation_date = 2017-09-23 -action.escu.modification_date = 2017-09-23 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect malicious requests to exploit JBoss servers - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["SamSam Ransomware", "JBoss Vulnerability"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect malicious requests to exploit JBoss servers - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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=Web where (Web.http_method="GET" OR Web.http_method="HEAD") by Web.http_method, Web.url,Web.url_length Web.src, Web.dest | search Web.url="*jmx-console/HtmlAdaptor?action=invokeOpByName&name=jboss.admin*import*" AND Web.url_length > 200 | `drop_dm_object_name("Web")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | table src, dest_ip, http_method, url, firstTime, lastTime | `detect_malicious_requests_to_exploit_jboss_servers_filter` - -[ESCU - Detect mshta exe running scripts in command-line arguments - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for the execution of "mshta.exe" with command-line arguments that launch a script. 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.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for the execution of "mshta.exe" with command-line arguments that launch a script. 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.escu.how_to_implement = To successfully implement this search, you need to be ingesting logs with the process name, parent process, and command-line executions from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. -action.escu.known_false_positives = Although unlikely, some legitimate applications may exhibit this behavior, triggering a false positive. -action.escu.creation_date = 2018-12-03 -action.escu.modification_date = 2018-12-03 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect mshta exe running scripts in command-line arguments - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious MSHTA Activity"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect mshta exe running scripts in command-line arguments - Rule -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 "mshta.exe" with command-line arguments that launch a script. 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 exe running scripts in command-line arguments -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -alert.digest_mode = 1 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 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=mshta.exe by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| search (process=*vbscript* OR process=*javascript*) | `detect_mshta_exe_running_scripts_in_command_line_arguments_filter` - -[ESCU - Detect new API calls from user roles - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -action.escu.data_models = [] -action.escu.eli5 = 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.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. This search works best when you run the "Previously seen API call per user roles in CloudTrail" support search once to create a history of previously seen user roles. -action.escu.known_false_positives = It is possible that there are legitimate user roles making new or infrequently used API calls in your infrastructure, causing the search to trigger. -action.escu.creation_date = 2018-04-16 -action.escu.modification_date = 2018-04-16 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect new API calls from user roles - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["AWS User Monitoring"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect new API calls from user roles - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `cloudtrail` eventType=AwsApiCall errorCode=success userIdentity.type=AssumedRole [search `cloudtrail` eventType=AwsApiCall errorCode=success userIdentity.type=AssumedRole | stats earliest(_time) as earliest latest(_time) as latest by userName eventName | inputlookup append=t previously_seen_api_calls_from_user_roles | stats min(earliest) as earliest, max(latest) as latest by userName eventName | outputlookup previously_seen_api_calls_from_user_roles| eval newApiCallfromUserRole=if(earliest>=relative_time(now(), "-70m@m"), 1, 0) | where newApiCallfromUserRole=1 | `security_content_ctime(earliest)` | `security_content_ctime(latest)` | table eventName userName] |rename userName as user| stats values(eventName) earliest(_time) as earliest latest(_time) as latest by user | `security_content_ctime(earliest)` | `security_content_ctime(latest)` | `detect_new_api_calls_from_user_roles_filter` - -[ESCU - Detect new user AWS Console Login - Rule] -action.escu = 0 -action.escu.enabled = 1 -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 -action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} -action.escu.data_models = [] -action.escu.eli5 = 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 -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. Run the "Previously seen users in CloudTrail" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run "Update previously seen users in CloudTrail" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines. -action.escu.known_false_positives = When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate. -action.escu.creation_date = 2018-04-30 -action.escu.modification_date = 2018-04-30 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect new user AWS Console Login - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious AWS Login Activities"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect new user AWS Console Login - Rule -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 -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `cloudtrail` eventName=ConsoleLogin | rename userIdentity.arn as user | stats earliest(_time) as firstTime latest(_time) as lastTime by user | inputlookup append=t previously_seen_users_console_logins.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by user | eval userStatus=if(firstTime >= relative_time(now(), "-70m@m"), "First Time Logging into AWS Console","Previously Seen User") | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`| where userStatus ="First Time Logging into AWS Console" | `detect_new_user_aws_console_login_filter` - -[ESCU - Detect processes used for System Network Configuration Discovery - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for fast execution of processes used for system network configuration discovery on the endpoint. -action.escu.mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for fast execution of processes used for system network configuration discovery on the endpoint. -action.escu.how_to_implement = You must be ingesting data that records registry activity from your hosts to populate the Endpoint data model in the processes node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. The data used for this search is usually generated via logs that report reads and writes to the registry or that are populated via Windows event logs, after enabling process tracking in your Windows audit settings. -action.escu.known_false_positives = It is uncommon for normal users to execute a series of commands used for network discovery. System administrators often use scripts to execute these commands. These can generate false positives. -action.escu.creation_date = 2018-11-20 -action.escu.modification_date = 2018-11-20 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect processes used for System Network Configuration Discovery - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Unusual Processes"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect processes used for System Network Configuration Discovery - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes by Processes.dest Processes.process_name Processes.user _time | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name(Processes)` | search `system_network_configuration_discovery_tools` | transaction dest connected=false maxpause=5m |where eventcount>=5 | table firstTime lastTime dest user process_name process parent_process eventcount | `detect_processes_used_for_system_network_configuration_discovery_filter` - -[ESCU - Detect web traffic to dynamic domain providers - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for web connections to dynamic DNS providers. -action.escu.mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1102", "T1041"], "nist": ["PR.IP", "DE.DP"]} -action.escu.data_models = ["Web"] -action.escu.eli5 = This search looks for web connections to dynamic DNS providers. -action.escu.how_to_implement = This search requires you to be ingesting web-traffic logs. You can obtain these logs from indexing data from a web proxy or by using a network-traffic-analysis tool, such as Bro or Splunk Stream. The web data model must contain the URL being requested, the IP address of the host initiating the request, and the destination IP. This search also leverages a lookup file, `dynamic_dns_providers_default.csv`, which contains a non-exhaustive list of dynamic DNS providers. Consider periodically updating this local lookup file with new domains.\ -This search produces fields (`isDynDNS`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** IsDynamicDNS, **Field:** isDynDNS\ -Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -action.escu.known_false_positives = It is possible that list of dynamic DNS providers is outdated and/or that the URL being requested is legitimate. -action.escu.creation_date = 2018-09-06 -action.escu.modification_date = 2018-09-06 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect web traffic to dynamic domain providers - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Dynamic DNS"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detect web traffic to dynamic domain providers - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 values(Web.url) as url min(_time) as firstTime from datamodel=Web where Web.status=200 by Web.src Web.dest Web.status | `drop_dm_object_name("Web")` | `security_content_ctime(firstTime)` | `dynamic_dns_web_traffic` | `detect_web_traffic_to_dynamic_domain_providers_filter` - -[ESCU - Detection of DNS Tunnels - Rule] -action.escu = 0 -action.escu.enabled = 1 -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. -action.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1043"], "nist": ["PR.PT", "PR.DS"]} -action.escu.data_models = ["Network_Resolution"] -action.escu.eli5 = 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. -action.escu.how_to_implement = To successfully implement this search, we must ensure that DNS data is being ingested and mapped to the appropriate fields in the Network_Resolution data model. Fields like src_category are automatically provided by the Assets and Identity Framework shipped with Splunk Enterprise Security. You will need to ensure you are using the Assets and Identity Framework and populating the src_category field. You will also need to enable the `cim_corporate_web_domain_search()` macro which will essentially filter out the DNS queries made to the corporate web domains to reduce alert fatigue. -action.escu.known_false_positives = It's possible that normal DNS traffic will exhibit this behavior. If an alert is generated, please investigate and validate as appropriate. The threshold can also be modified to better suit your environment. -action.escu.creation_date = 2017-09-18 -action.escu.modification_date = 2017-09-18 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detection of DNS Tunnels - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Command and Control", "Data Protection", "Suspicious DNS Traffic"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detection of DNS Tunnels - Rule -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. -action.notable.param.rule_title = Detection of DNS Tunnels -action.notable.param.security_domain = network -action.notable.param.severity = high -alert.digest_mode = 1 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = | tstats `security_content_summariesonly` dc("DNS.query") as count from datamodel=Network_Resolution where nodename=DNS "DNS.message_type"="QUERY" NOT (`cim_corporate_web_domain_search("DNS.query")`) NOT "DNS.query"="*.in-addr.arpa" NOT ("DNS.src_category"="svc_infra_dns" OR "DNS.src_category"="svc_infra_webproxy" OR "DNS.src_category"="svc_infra_email*" ) by "DNS.src","DNS.query" | rename "DNS.src" as src "DNS.query" as message | eval length=len(message) | stats sum(length) as length by src | append [ tstats `security_content_summariesonly` dc("DNS.answer") as count from datamodel=Network_Resolution where nodename=DNS "DNS.message_type"="QUERY" NOT (`cim_corporate_web_domain_search("DNS.query")`) NOT "DNS.query"="*.in-addr.arpa" NOT ("DNS.src_category"="svc_infra_dns" OR "DNS.src_category"="svc_infra_webproxy" OR "DNS.src_category"="svc_infra_email*" ) by "DNS.src","DNS.answer" | rename "DNS.src" as src "DNS.answer" as message | eval message=if(message=="unknown","", message) | eval length=len(message) | stats sum(length) as length by src ] | stats sum(length) as length by src | where length > 10000 | `detection_of_dns_tunnels_filter` - -[ESCU - Detection of tools built by NirSoft - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 3"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1072", "T1087"], "nist": ["PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = 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.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. The command-line arguments are mapped to the "process" field in the Endpoint data model. -action.escu.known_false_positives = While legitimate, these NirSoft tools are prone to abuse. You should verfiy that the tool was used for a legitimate purpose. -action.escu.creation_date = 2018-12-03 -action.escu.modification_date = 2018-12-03 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Detection of tools built by NirSoft - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Emotet Malware DHS Report TA18-201A "] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Detection of tools built by NirSoft - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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) 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 - Disabling Remote User Account Control - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = The search looks for modifications to registry keys that control the enforcement of Windows User Account Control (UAC). -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1112"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [] -action.escu.eli5 = The search looks for modifications to registry keys that control the enforcement of Windows User Account Control (UAC). -action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report registry modifications. -action.escu.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. -action.escu.creation_date = 2020-03-02 -action.escu.modification_date = 2020-03-02 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Disabling Remote User Account Control - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Defense Evasion Tactics"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Disabling Remote User Account Control - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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="*Windows\\CurrentVersion\\Policies\\System\\LocalAccountTokenFilterPolicy" by Registry.dest, Registry.registry_key_name Registry.user Registry.registry_path Registry.action | `drop_dm_object_name(Registry)` | `disabling_remote_user_account_control_filter` - -[ESCU - Dump LSASS via comsvcs DLL - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = Detect the usage of comsvcs.dll for dumping the lsass process. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = Detect the usage of comsvcs.dll for dumping the lsass process. -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. The command-line arguments are mapped to the "process" field in the Endpoint data model. -action.escu.known_false_positives = None identified. -action.escu.creation_date = 2020-02-21 -action.escu.modification_date = 2020-02-21 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Dump LSASS via comsvcs DLL - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Credential Dumping"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Dump LSASS via comsvcs DLL - Rule -schedule_window = auto -action.notable = 1 -action.notable.param.nes_fields = ['user', 'dest'] -action.notable.param.rule_description = Detect the usage of comsvcs.dll for dumping the lsass process. -action.notable.param.rule_title = Dump LSASS via comsvcs DLL -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -alert.digest_mode = 1 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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=rundll32.exe Processes.process=*comsvcs.dll* Processes.process=*MiniDump* by Processes.user Processes.process_name Processes.process Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `dump_lsass_via_comsvcs_dll_filter` - -[ESCU - EC2 Instance Modified With Previously Unseen User - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for EC2 instances being modified by users who have not previously modified them. -action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -action.escu.data_models = [] -action.escu.eli5 = This search looks for EC2 instances being modified by users who have not previously modified them. -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. This search works best when you run the "Previously Seen EC2 Launches By User" support search once to create a history of previously seen ARNs. To add or remove APIs that modify an EC2 instance, edit the macro `ec2_modification_api_calls`. -action.escu.known_false_positives = It's possible that a new user will start to modify EC2 instances when they haven't before for any number of reasons. Verify with the user that is modifying instances that this is the intended behavior. -action.escu.creation_date = 2018-04-09 -action.escu.modification_date = 2018-04-09 -action.escu.confidence = high -action.escu.full_search_name = ESCU - EC2 Instance Modified With Previously Unseen User - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Unusual AWS EC2 Modifications"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - EC2 Instance Modified With Previously Unseen User - Rule -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. -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `cloudtrail` `ec2_modification_api_calls` [search `cloudtrail` `ec2_modification_api_calls` errorCode=success | stats earliest(_time) as firstTime latest(_time) as lastTime by userIdentity.arn | rename userIdentity.arn as arn | inputlookup append=t previously_seen_ec2_modifications_by_user | stats min(firstTime) as firstTime, max(lastTime) as lastTime by arn | outputlookup previously_seen_ec2_modifications_by_user | eval newUser=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newUser=1 | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | rename arn as userIdentity.arn | table userIdentity.arn] | spath output=dest responseElements.instancesSet.items{}.instanceId | spath output=user userIdentity.arn | table _time, user, dest | `ec2_instance_modified_with_previously_unseen_user_filter` - -[ESCU - EC2 Instance Started In Previously Unseen Region - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} -action.escu.data_models = [] -action.escu.eli5 = 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.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. Run the "Previously seen AWS Regions" support search only once to create of baseline of previously seen regions. -action.escu.known_false_positives = It's possible that a user has unknowingly started an instance in a new region. Please verify that this activity is legitimate. -action.escu.creation_date = 2018-02-23 -action.escu.modification_date = 2018-02-23 -action.escu.confidence = high -action.escu.full_search_name = ESCU - EC2 Instance Started In Previously Unseen Region - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["AWS Cryptomining", "Suspicious AWS EC2 Activities"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - EC2 Instance Started In Previously Unseen Region - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `cloudtrail` earliest=-1h StartInstances | stats earliest(_time) as earliest latest(_time) as latest by awsRegion | inputlookup append=t previously_seen_aws_regions.csv | stats min(earliest) as earliest max(latest) as latest by awsRegion | outputlookup previously_seen_aws_regions.csv | eval regionStatus=if(earliest >= relative_time(now(),"-1d@d"), "Instance Started in a New Region","Previously Seen Region") | `security_content_ctime(earliest)` | `security_content_ctime(latest)` | where regionStatus="Instance Started in a New Region" | `ec2_instance_started_in_previously_unseen_region_filter` - -[ESCU - EC2 Instance Started With Previously Unseen AMI - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for EC2 instances being created with previously unseen AMIs. -action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -action.escu.data_models = [] -action.escu.eli5 = This search looks for EC2 instances being created with previously unseen AMIs. -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. This search works best when you run the "Previously Seen EC2 AMIs" support search once to create a history of previously seen AMIs. -action.escu.known_false_positives = After a new AMI is created, the first systems created with that AMI will cause this alert to fire. Verify that the AMI being used was created by a legitimate user. -action.escu.creation_date = 2018-03-12 -action.escu.modification_date = 2018-03-12 -action.escu.confidence = high -action.escu.full_search_name = ESCU - EC2 Instance Started With Previously Unseen AMI - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["AWS Cryptomining"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - EC2 Instance Started With Previously Unseen AMI - Rule -schedule_window = auto -action.notable = 1 -action.notable.param.rule_description = This search looks for EC2 instances being created with previously unseen AMIs. -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `cloudtrail` eventName=RunInstances [search `cloudtrail` eventName=RunInstances errorCode=success | stats earliest(_time) as firstTime latest(_time) as lastTime by requestParameters.instancesSet.items{}.imageId | rename requestParameters.instancesSet.items{}.imageId as amiID | inputlookup append=t previously_seen_ec2_amis.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by amiID | outputlookup previously_seen_ec2_amis.csv | eval newAMI=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | where newAMI=1 | rename amiID as requestParameters.instancesSet.items{}.imageId | table requestParameters.instancesSet.items{}.imageId] | rename requestParameters.instanceType as instanceType, responseElements.instancesSet.items{}.instanceId as dest, userIdentity.arn as arn, requestParameters.instancesSet.items{}.imageId as amiID | table firstTime, lastTime, arn, amiID, dest, instanceType | `ec2_instance_started_with_previously_unseen_ami_filter` - -[ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for EC2 instances being created with previously unseen instance types. -action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -action.escu.data_models = [] -action.escu.eli5 = This search looks for EC2 instances being created with previously unseen 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. This search works best when you run the "Previously Seen EC2 Instance Types" support search once to create a history of previously seen instance types. -action.escu.known_false_positives = It is possible that an admin will create a new system using a new instance type never used before. Verify with the creator that they intended to create the system with the new instance type. -action.escu.creation_date = 2020-02-07 -action.escu.modification_date = 2020-02-07 -action.escu.confidence = high -action.escu.full_search_name = ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["AWS Cryptomining"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule -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. -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `cloudtrail` eventName=RunInstances [search `cloudtrail` eventName=RunInstances errorCode=success | fillnull value="m1.small" requestParameters.instanceType | stats earliest(_time) as earliest latest(_time) as latest by requestParameters.instanceType | rename requestParameters.instanceType as instanceType | inputlookup append=t previously_seen_ec2_instance_types.csv | stats min(earliest) as earliest max(latest) as latest by instanceType | outputlookup previously_seen_ec2_instance_types.csv | eval newType=if(earliest >= relative_time(now(), "-70m@m"), 1, 0) | `security_content_ctime(earliest)` | `security_content_ctime(latest)` | where newType=1 | rename instanceType as requestParameters.instanceType | table requestParameters.instanceType] | spath output=user userIdentity.arn | rename requestParameters.instanceType as instanceType, responseElements.instancesSet.items{}.instanceId as dest | table _time, user, dest, instanceType | `ec2_instance_started_with_previously_unseen_instance_type_filter` - -[ESCU - EC2 Instance Started With Previously Unseen User - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for EC2 instances being created by users who have not created them before. -action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -action.escu.data_models = [] -action.escu.eli5 = This search looks for EC2 instances being created by users who have not created them before. -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. This search works best when you run the "Previously Seen EC2 Launches By User" support search once to create a history of previously seen ARNs. -action.escu.known_false_positives = It's possible that a user will start to create EC2 instances when they haven't before for any number of reasons. Verify with the user that is launching instances that this is the intended behavior. -action.escu.creation_date = 2018-03-12 -action.escu.modification_date = 2018-03-12 -action.escu.confidence = high -action.escu.full_search_name = ESCU - EC2 Instance Started With Previously Unseen User - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["AWS Cryptomining", "Suspicious AWS EC2 Activities"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - EC2 Instance Started With Previously Unseen User - Rule -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. -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `cloudtrail` eventName=RunInstances [search `cloudtrail` eventName=RunInstances errorCode=success | stats earliest(_time) as firstTime latest(_time) as lastTime by userIdentity.arn | rename userIdentity.arn as arn | inputlookup append=t previously_seen_ec2_launches_by_user.csv | stats min(firstTime) as firstTime, max(lastTime) as lastTime by arn | outputlookup previously_seen_ec2_launches_by_user.csv | eval newUser=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newUser=1 | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | rename arn as userIdentity.arn | table userIdentity.arn] | rename requestParameters.instanceType as instanceType, responseElements.instancesSet.items{}.instanceId as dest, userIdentity.arn as user | table _time, user, dest, instanceType | `ec2_instance_started_with_previously_unseen_user_filter` - -[ESCU - Email Attachments With Lots Of Spaces - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"]} -action.escu.data_models = ["Email"] -action.escu.eli5 = 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.escu.how_to_implement = You need to ingest data from emails. Specifically, the sender's address and the file names of any attachments must be mapped to the Email data model. The threshold ratio is set to 10%, but this value can be configured to suit each environment. \ - **Splunk Phantom Playbook Integration**\ -If Splunk Phantom is also configured in your environment, a playbook called "Suspicious Email Attachment Investigate and Delete" can be configured to run when any results are found by this detection search. To use this integration, install the Phantom App for Splunk `https://splunkbase.splunk.com/app/3411/` and add the correct hostname to the "Phantom Instance" field in the Adaptive Response Actions when configuring this detection search. The notable event will be sent to Phantom and the playbook will gather further information about the file attachment and its network behaviors. If Phantom finds malicious behavior and an analyst approves of the results, the email will be deleted from the user's inbox. -action.escu.known_false_positives = None at this time -action.escu.creation_date = 2017-09-19 -action.escu.modification_date = 2017-09-19 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Email Attachments With Lots Of Spaces - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Emails", "Emotet Malware DHS Report TA18-201A "] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Email Attachments With Lots Of Spaces - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 values(All_Email.recipient) as recipient_address min(_time) as firstTime max(_time) as lastTime from datamodel=Email where All_Email.file_name="*" by All_Email.src_user, All_Email.file_name All_Email.message_id | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name("All_Email")` | eval space_ratio = (mvcount(split(file_name," "))-1)/len(file_name) | search space_ratio >= 0.1 | rex field=recipient_address "(?.*)@" | `email_attachments_with_lots_of_spaces_filter` - -[ESCU - Email files written outside of the Outlook directory - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = The search looks at the change-analysis data model and detects email files created outside the normal Outlook directory. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1114"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = The search looks at the change-analysis data model and detects email files created outside the normal Outlook directory. -action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records the file-system activity from your hosts to populate the Endpoint.Filesystem data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or by other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file-system reads and writes. -action.escu.known_false_positives = Administrators and users sometimes prefer backing up their email data by moving the email files into a different folder. These attempts will be detected by the search. -action.escu.creation_date = 2020-03-23 -action.escu.modification_date = 2020-03-23 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Email files written outside of the Outlook directory - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Collection and Staging"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Email files written outside of the Outlook directory - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 values(Filesystem.file_path) as file_path min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Filesystem where (Filesystem.file_name=*.pst OR Filesystem.file_name=*.ost) Filesystem.file_path != "C:\\Users\\*\\My Documents\\Outlook Files\\*" Filesystem.file_path!="C:\\Users\\*\\AppData\\Local\\Microsoft\\Outlook*" by Filesystem.action Filesystem.process_id Filesystem.file_name Filesystem.dest | `drop_dm_object_name("Filesystem")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`| `email_files_written_outside_of_the_outlook_directory_filter` - -[ESCU - Email servers sending high volume traffic to hosts - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1114", "T1043"], "nist": ["PR.PT", "DE.CM", "DE.AE"]} -action.escu.data_models = ["Network_Traffic"] -action.escu.eli5 = 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.escu.how_to_implement = This search requires you to be ingesting your network traffic and populating the Network_Traffic data model. Your email servers must be categorized as "email_server" for the search to work, as well. You may need to adjust the deviation_threshold and minimum_data_samples values based on the network traffic in your environment. The "deviation_threshold" field is a multiplying factor to control how much variation you're willing to tolerate. The "minimum_data_samples" field is the minimum number of connections of data samples required for the statistic to be valid. -action.escu.known_false_positives = The false-positive rate will vary based on how you set the deviation_threshold and data_samples values. Our recommendation is to adjust these values based on your network traffic to and from your email servers. -action.escu.creation_date = 2017-12-20 -action.escu.modification_date = 2017-12-20 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Email servers sending high volume traffic to hosts - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Collection and Staging"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Email servers sending high volume traffic to hosts - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = | tstats `security_content_summariesonly` sum(All_Traffic.bytes_out) as bytes_out from datamodel=Network_Traffic where All_Traffic.src_category=email_server by All_Traffic.dest_ip _time span=1d | `drop_dm_object_name("All_Traffic")` | eventstats avg(bytes_out) as avg_bytes_out stdev(bytes_out) as stdev_bytes_out | eventstats count as num_data_samples avg(eval(if(_time < relative_time(now(), "@d"), bytes_out, null))) as per_source_avg_bytes_out stdev(eval(if(_time < relative_time(now(), "@d"), bytes_out, null))) as per_source_stdev_bytes_out by dest_ip | eval minimum_data_samples = 4, deviation_threshold = 3 | where num_data_samples >= minimum_data_samples AND bytes_out > (avg_bytes_out + (deviation_threshold * stdev_bytes_out)) AND bytes_out > (per_source_avg_bytes_out + (deviation_threshold * per_source_stdev_bytes_out)) AND _time >= relative_time(now(), "@d") | eval num_standard_deviations_away_from_server_average = round(abs(bytes_out - avg_bytes_out) / stdev_bytes_out, 2), num_standard_deviations_away_from_client_average = round(abs(bytes_out - per_source_avg_bytes_out) / per_source_stdev_bytes_out, 2) | table dest_ip, _time, bytes_out, avg_bytes_out, per_source_avg_bytes_out, num_standard_deviations_away_from_server_average, num_standard_deviations_away_from_client_average | `email_servers_sending_high_volume_traffic_to_hosts_filter` - -[ESCU - Excessive DNS Failures - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 8", "CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048", "T1043"], "nist": ["PR.PT", "DE.AE", "DE.CM"]} -action.escu.data_models = ["Network_Resolution"] -action.escu.eli5 = 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.escu.how_to_implement = To successfully implement this search you must ensure that DNS data is populating the Network_Resolution data model. -action.escu.known_false_positives = It is possible legitimate traffic can trigger this rule. Please investigate as appropriate. The threshold for generating an event can also be customized to better suit your environment. -action.escu.creation_date = 2017-09-18 -action.escu.modification_date = 2017-09-18 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Excessive DNS Failures - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Command and Control", "Suspicious DNS Traffic"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Excessive DNS Failures - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 values("DNS.query") as queries from datamodel=Network_Resolution where nodename=DNS "DNS.reply_code"!="No Error" "DNS.reply_code"!="NoError" DNS.reply_code!="unknown" NOT "DNS.query"="*.arpa" "DNS.query"="*.*" by "DNS.src","DNS.query"| `drop_dm_object_name("DNS")`| lookup cim_corporate_web_domain_lookup domain as query OUTPUT domain| where isnull(domain)| lookup update=true alexa_lookup_by_str domain as query OUTPUT rank| where isnull(rank)| stats sum(count) as count mode(queries) as queries by src| `get_asset(src)`| where count>50 | `excessive_dns_failures_filter` - -[ESCU - Execution of File With Spaces Before Extension - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.PT", "PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = 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.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. -action.escu.known_false_positives = None identified. -action.escu.creation_date = 2018-01-26 -action.escu.modification_date = 2018-01-26 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Execution of File With Spaces Before Extension - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Windows File Extension and Association Abuse"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Execution of File With Spaces Before Extension - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 values(Processes.process_path) as process_path min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process = "* .*" by Processes.dest Processes.user Processes.process Processes.process_name | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `drop_dm_object_name(Processes)` | `execution_of_file_with_spaces_before_extension_filter` - -[ESCU - Execution of File with Multiple Extensions - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.PT", "PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = 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.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. -action.escu.known_false_positives = None identified. -action.escu.creation_date = 2018-11-02 -action.escu.modification_date = 2018-11-02 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Execution of File with Multiple Extensions - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Windows File Extension and Association Abuse"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Execution of File with Multiple Extensions - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 = *.doc.exe OR Processes.process = *.htm.exe OR Processes.process = *.html.exe OR Processes.process = *.txt.exe OR Processes.process = *.pdf.exe OR Processes.process = *.doc.exe by Processes.dest Processes.user Processes.process Processes.parent_process | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name(Processes)` | `execution_of_file_with_multiple_extensions_filter` - -[ESCU - Extended Period Without Successful Netbackup Backups - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search returns a list of hosts that have not successfully completed a backup in over a week. -action.escu.mappings = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} -action.escu.data_models = [] -action.escu.eli5 = This search returns a list of hosts that have not successfully completed a backup in over a week. -action.escu.how_to_implement = To successfully implement this search you need to first obtain data from your backup solution, either from the backup logs on your hosts, or from a central server responsible for performing the backups. If you do not use Netbackup, you can modify this search for your backup solution. Depending on how often you backup your systems, you may want to modify how far in the past to look for a successful backup, other than the default of seven days. -action.escu.known_false_positives = None identified -action.escu.creation_date = 2017-09-12 -action.escu.modification_date = 2017-09-12 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Extended Period Without Successful Netbackup Backups - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Monitor Backup Solution"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Extended Period Without Successful Netbackup Backups - Rule -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. -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `netbackup` MESSAGE="Disk/Partition backup completed successfully." | stats latest(_time) as latestTime by COMPUTERNAME | `security_content_ctime(latestTime)` | rename COMPUTERNAME as dest | eval isOutlier=if(latestTime <= relative_time(now(), "-7d@d"), 1, 0) | search isOutlier=1 | table latestTime, dest | `extended_period_without_successful_netbackup_backups_filter` - -[ESCU - File with Samsam Extension - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = The search looks for file writes with extensions consistent with a SamSam ransomware attack. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Installation"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = The search looks for file writes with extensions consistent with a SamSam ransomware attack. -action.escu.how_to_implement = You must be ingesting data that records file-system 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 = Because these extensions are not typically used in normal operations, you should investigate all results. -action.escu.creation_date = 2018-12-14 -action.escu.modification_date = 2018-12-14 -action.escu.confidence = high -action.escu.full_search_name = ESCU - File with Samsam Extension - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["SamSam Ransomware"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - File with Samsam Extension - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_path) as file_path from datamodel=Endpoint.Filesystem by Filesystem.file_name | `drop_dm_object_name(Filesystem)` | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)`| rex field=file_name "(?\.[^\.]+)$" | search file_extension=.stubbin OR file_extension=.berkshire OR file_extension=.satoshi OR file_extension=.sophos OR file_extension=.keyxml | `file_with_samsam_extension_filter` - -[ESCU - First Time Seen Running Windows Service - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for the first time a Windows service is seen running in your environment. -action.escu.mappings = {"cis20": ["CIS 2", "CIS 9"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1050"], "nist": ["ID.AM", "PR.DS", "PR.AC", "DE.AE"]} -action.escu.data_models = [] -action.escu.eli5 = This search looks for the first time a Windows service is seen running in your environment. -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 in order for this search to execute successfully. The support search, `Previously Seen Running Windows Services`, should be run before this search to create the baseline of known Windows services. Please ensure that the Splunk Add-on for Microsoft Windows is version 5.0.0 or above. -action.escu.known_false_positives = A previously unseen service is not necessarily malicious. Verify that the service is legitimate and that was installed by a legitimate process. -action.escu.creation_date = 2020-01-13 -action.escu.modification_date = 2020-01-13 -action.escu.confidence = high -action.escu.full_search_name = ESCU - First Time Seen Running Windows Service - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Windows Service Abuse", "Orangeworm Attack Group"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - First Time Seen Running Windows Service - Rule -schedule_window = auto -action.notable = 1 -action.notable.param.nes_fields = ['dest'] -action.notable.param.rule_description = This search looks for the first time a Windows service is seen running in your environment. -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `wineventlog_system` signature_id=7036 | rename param1 as service_name | rename param2 as action | search action="running" [ search `wineventlog_system` signature_id=7036 | rename param1 as service_name | rename param2 as action | search action="running" | stats earliest(_time) as firstTime, latest(_time) as lastTime by service_name | inputlookup append=t previously_seen_running_windows_services | stats min(firstTime) as firstTime max(lastTime) as lastTime by service_name | outputlookup previously_seen_running_windows_services| eval serviceStatus=if(firstTime >= relative_time(now(),"-60m@m"), "First time seen Windows service","Previously seen Windows service") | where serviceStatus="First time seen Windows service"| `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | table service_name]| table _time dest service_name | `first_time_seen_running_windows_service_filter` - -[ESCU - First time seen command line argument - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for command-line arguments that use a `/c` parameter to execute a command that has not previously been seen. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1064", "T1059"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for command-line arguments that use a `/c` parameter to execute a command that has not previously been seen. -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. Please make sure you run the support search "Previously seen command line arguments,"—which creates a lookup file called `previously_seen_cmd_line_arguments.csv`—a historical baseline of all command-line arguments. You must also validate this list. For the search to do accurate calculation, ensure the search scheduling is the same value as the `relative_time` evaluation function. -action.escu.known_false_positives = Legitimate programs can also use command-line arguments to execute. Please verify the command-line arguments to check what command/program is being executed. We recommend customizing the `first_time_seen_cmd_line_filter` macro to exclude legitimate parent_process_name -action.escu.creation_date = 2020-03-02 -action.escu.modification_date = 2020-03-02 -action.escu.confidence = high -action.escu.full_search_name = ESCU - First time seen command line argument - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Command-Line Executions", "Hidden Cobra Malware", "DHS Report TA18-074A", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Orangeworm Attack Group"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - First time seen command line argument - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -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 Processes.process = "* /c *" by Processes.process Processes.process_name Processes.parent_process_name Processes.dest| `drop_dm_object_name(Processes)`| `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | search [| tstats `security_content_summariesonly` earliest(_time) as firstTime latest(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = cmd.exe Processes.process = "* /c *" by Processes.process | `drop_dm_object_name(Processes)` | inputlookup append=t previously_seen_cmd_line_arguments | stats min(firstTime) as firstTime, max(lastTime) as lastTime by process | outputlookup previously_seen_cmd_line_arguments | eval newCmdLineArgument=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newCmdLineArgument=1 | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | table process] | `first_time_seen_command_line_argument_filter` - -[ESCU - GCP GCR container uploaded - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {} -action.escu.data_models = [] -action.escu.eli5 = This search show information on uploaded containers including source user, account, action, bucket name event name, http user agent, message and destination path. -action.escu.how_to_implement = You must install the GCP App for Splunk (version 2.0.0 or later), then configure stackdriver and set a subpub subscription to be imported to Splunk. You must also install Cloud Infrastructure data model. Please also customize the `container_implant_gcp_detection_filter` macro to filter out the false positives. -action.escu.known_false_positives = Uploading container is a normal behavior from developers or users with access to container registry. GCP GCR registers container upload as a Storage event, this search must be considered under the context of CONTAINER upload creation which automatically generates a bucket entry for destination path. -action.escu.creation_date = 2020-02-20 -action.escu.modification_date = 2020-02-20 -action.escu.confidence = high -action.escu.full_search_name = ESCU - GCP GCR container uploaded - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Container Implantation Monitoring and Investigation"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - GCP GCR container uploaded - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = |tstats count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Cloud_Infrastructure.Storage where Storage.event_name=storage.objects.create by Storage.src_user Storage.account Storage.action Storage.bucket_name Storage.event_name Storage.http_user_agent Storage.msg Storage.object_path | `drop_dm_object_name("Storage")` | `gcp_gcr_container_uploaded_filter` - -[ESCU - GCP Kubernetes cluster scan detection - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster -action.escu.mappings = {"kill_chain_phases": ["Reconnaissance"]} -action.escu.data_models = [] -action.escu.eli5 = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster -action.escu.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. -action.escu.known_false_positives = Not all unauthenticated requests are malicious, but frequency, User Agent and source IPs will provide context. -action.escu.creation_date = 2020-04-15 -action.escu.modification_date = 2020-04-15 -action.escu.confidence = high -action.escu.full_search_name = ESCU - GCP Kubernetes cluster scan detection - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Kubernetes Scanning Activity"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - GCP Kubernetes cluster scan detection - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `google_gcp_pubsub_message` data.protoPayload.requestMetadata.callerIp!=127.0.0.1 data.protoPayload.requestMetadata.callerIp!=::1 "data.labels.authorization.k8s.io/decision"=forbid "data.protoPayload.status.message"=PERMISSION_DENIED data.protoPayload.authenticationInfo.principalEmail="system:anonymous" | rename data.protoPayload.requestMetadata.callerIp as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(data.protoPayload.methodName) as method_name values(data.protoPayload.resourceName) as resource_name values(data.protoPayload.requestMetadata.callerSuppliedUserAgent) as http_user_agent by src_ip data.resource.labels.cluster_name | rename data.resource.labels.cluster_name as cluster_name| `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `gcp_kubernetes_cluster_scan_detection_filter` - -[ESCU - Hiding Files And Directories With Attrib exe - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = 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.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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -action.escu.known_false_positives = Some applications and users may legitimately use attrib.exe to interact with the files. -action.escu.creation_date = 2020-03-16 -action.escu.modification_date = 2020-03-16 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Hiding Files And Directories With Attrib exe - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Windows Persistence Techniques", "Windows Defense Evasion Tactics"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Hiding Files And Directories With Attrib exe - Rule -schedule_window = auto -action.notable = 1 -action.notable.param.nes_fields = ['user'] -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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) values(Processes.process) as process max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=attrib.exe (Processes.process=*+h*) by Processes.parent_process Processes.process_name Processes.user | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`| `hiding_files_and_directories_with_attrib_exe_filter` - -[ESCU - Hosts receiving high volume of network traffic from email server - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043"], "nist": ["PR.PT", "DE.CM", "DE.AE"]} -action.escu.data_models = ["Network_Traffic"] -action.escu.eli5 = 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.escu.how_to_implement = This search requires you to be ingesting your network traffic and populating the Network_Traffic data model. Your email servers must be categorized as "email_server" for the search to work, as well. You may need to adjust the deviation_threshold and minimum_data_samples values based on the network traffic in your environment. The "deviation_threshold" field is a multiplying factor to control how much variation you're willing to tolerate. The "minimum_data_samples" field is the minimum number of connections of data samples required for the statistic to be valid. -action.escu.known_false_positives = The false-positive rate will vary based on how you set the deviation_threshold and data_samples values. Our recommendation is to adjust these values based on your network traffic to and from your email servers. -action.escu.creation_date = 2017-12-20 -action.escu.modification_date = 2017-12-20 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Hosts receiving high volume of network traffic from email server - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Collection and Staging"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Hosts receiving high volume of network traffic from email server - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = | tstats `security_content_summariesonly` sum(All_Traffic.bytes_in) as bytes_in from datamodel=Network_Traffic where All_Traffic.dest_category=email_server by All_Traffic.src_ip _time span=1d | `drop_dm_object_name("All_Traffic")` | eventstats avg(bytes_in) as avg_bytes_in stdev(bytes_in) as stdev_bytes_in | eventstats count as num_data_samples avg(eval(if(_time < relative_time(now(), "@d"), bytes_in, null))) as per_source_avg_bytes_in stdev(eval(if(_time < relative_time(now(), "@d"), bytes_in, null))) as per_source_stdev_bytes_in by src_ip | eval minimum_data_samples = 4, deviation_threshold = 3 | where num_data_samples >= minimum_data_samples AND bytes_in > (avg_bytes_in + (deviation_threshold * stdev_bytes_in)) AND bytes_in > (per_source_avg_bytes_in + (deviation_threshold * per_source_stdev_bytes_in)) AND _time >= relative_time(now(), "@d") | eval num_standard_deviations_away_from_server_average = round(abs(bytes_in - avg_bytes_in) / stdev_bytes_in, 2), num_standard_deviations_away_from_client_average = round(abs(bytes_in - per_source_avg_bytes_in) / per_source_stdev_bytes_in, 2) | table src_ip, _time, bytes_in, avg_bytes_in, per_source_avg_bytes_in, num_standard_deviations_away_from_server_average, num_standard_deviations_away_from_client_average | `hosts_receiving_high_volume_of_network_traffic_from_email_server_filter` - -[ESCU - Identify New User Accounts - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1136"], "nist": ["PR.IP"]} -action.escu.data_models = [] -action.escu.eli5 = 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.escu.how_to_implement = To successfully implement this search, you need to be populating the Enterprise Security Identity_Management data model in the assets and identity framework. -action.escu.known_false_positives = If the Identity_Management data model is not updated regularly, this search could give you false positive alerts. Please consider this and investigate appropriately. -action.escu.creation_date = 2017-09-12 -action.escu.modification_date = 2017-09-12 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Identify New User Accounts - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Account Monitoring and Controls"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Identify New User Accounts - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = | from datamodel Identity_Management.All_Identities | eval empStatus=case((now()-startDate)<604800, "Accounts created in last week") | search empStatus="Accounts created in last week"| `security_content_ctime(endDate)` | `security_content_ctime(startDate)`| table identity empStatus endDate startDate | `identify_new_user_accounts_filter` - -[ESCU - Kubernetes Azure detect RBAC authorization by account - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"kill_chain_phases": ["Lateral Movement"]} -action.escu.data_models = [] -action.escu.eli5 = 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.escu.how_to_implement = You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics -action.escu.known_false_positives = Not all RBAC Authorications are malicious. RBAC authorizations can uncover malicious activity specially if sensitive Roles have been granted. -action.escu.creation_date = 2020-05-26 -action.escu.modification_date = 2020-05-26 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Kubernetes Azure detect RBAC authorization by account - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Kubernetes Sensitive Role Activity"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Kubernetes Azure detect RBAC authorization by account - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = sourcetype:mscs:storage:blob:json category=kube-audit | spath input=properties.log | search annotations.authorization.k8s.io/reason=* | table sourceIPs{} user.username userAgent annotations.authorization.k8s.io/reason |stats count by user.username annotations.authorization.k8s.io/reason | rare user.username annotations.authorization.k8s.io/reason |`kubernetes_azure_detect_rbac_authorization_by_account_filter` - -[ESCU - Kubernetes Azure detect most active service accounts by pod namespace - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search provides information on Kubernetes service accounts,accessing pods and namespaces by IP address and verb -action.escu.mappings = {"kill_chain_phases": ["Lateral Movement"]} -action.escu.data_models = [] -action.escu.eli5 = This search provides information on Kubernetes service accounts,accessing pods and namespaces by IP address and verb -action.escu.how_to_implement = You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics -action.escu.known_false_positives = Not all service accounts interactions are malicious. Analyst must consider IP and verb context when trying to detect maliciousness. -action.escu.creation_date = 2020-05-26 -action.escu.modification_date = 2020-05-26 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Kubernetes Azure detect most active service accounts by pod namespace - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Kubernetes Sensitive Role Activity"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Kubernetes Azure detect most active service accounts by pod namespace - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = sourcetype:mscs:storage:blob:json category=kube-audit | spath input=properties.log | search user.groups{}=system:serviceaccounts* | table sourceIPs{} user.username userAgent verb responseStatus.reason responseStatus.status properties.pod objectRef.namespace | top sourceIPs{} user.username verb responseStatus.status properties.pod objectRef.namespace |`kubernetes_azure_detect_most_active_service_accounts_by_pod_namespace_filter` - -[ESCU - Kubernetes Azure detect sensitive object access - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search provides information on Kubernetes accounts accessing sensitve objects such as configmpas or secrets -action.escu.mappings = {"kill_chain_phases": ["Lateral Movement"]} -action.escu.data_models = [] -action.escu.eli5 = This search provides information on Kubernetes accounts accessing sensitve objects such as configmpas or secrets -action.escu.how_to_implement = You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics -action.escu.known_false_positives = Sensitive object access is not necessarily malicious but user and object context can provide guidance for detection. -action.escu.creation_date = 2020-05-20 -action.escu.modification_date = 2020-05-20 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Kubernetes Azure detect sensitive object access - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Kubernetes Sensitive Object Access Activity"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Kubernetes Azure detect sensitive object access - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `kubernetes_azure` category=kube-audit | spath input=properties.log| search objectRef.resource=secrets OR configmaps |table user.username user.groups{} objectRef.resource objectRef.namespace objectRef.name annotations.authorization.k8s.io/reason |dedup user.username user.groups{} |`kubernetes_azure_detect_sensitive_object_access_filter` - -[ESCU - Kubernetes Azure detect sensitive role access - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search provides information on Kubernetes accounts accessing sensitve objects such as configmpas or secrets -action.escu.mappings = {"kill_chain_phases": ["Lateral Movement"]} -action.escu.data_models = [] -action.escu.eli5 = This search provides information on Kubernetes accounts accessing sensitve objects such as configmpas or secrets -action.escu.how_to_implement = You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics -action.escu.known_false_positives = Sensitive role resource access is necessary for cluster operation, however source IP, namespace and user group may indicate possible malicious use. -action.escu.creation_date = 2020-05-20 -action.escu.modification_date = 2020-05-20 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Kubernetes Azure detect sensitive role access - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Kubernetes Sensitive Role Activity"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Kubernetes Azure detect sensitive role access - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `kubernetes_azure` category=kube-audit | spath input=properties.log| search objectRef.resource=clusterroles OR clusterrolebindings | table sourceIPs{} user.username user.groups{} objectRef.namespace requestURI annotations.authorization.k8s.io/reason | dedup user.username user.groups{} |`kubernetes_azure_detect_sensitive_role_access_filter` - -[ESCU - Kubernetes Azure detect service accounts forbidden failure access - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search provides information on Kubernetes service accounts with failure or forbidden access status -action.escu.mappings = {"kill_chain_phases": ["Lateral Movement"]} -action.escu.data_models = [] -action.escu.eli5 = This search provides information on Kubernetes service accounts with failure or forbidden access status -action.escu.how_to_implement = You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics -action.escu.known_false_positives = This search can give false positives as there might be inherent issues with authentications and permissions at cluster. -action.escu.creation_date = 2020-05-20 -action.escu.modification_date = 2020-05-20 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Kubernetes Azure detect service accounts forbidden failure access - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Kubernetes Sensitive Object Access Activity"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Kubernetes Azure detect service accounts forbidden failure access - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `kubernetes_azure` category=kube-audit | spath input=properties.log | search user.groups{}=system:serviceaccounts* responseStatus.reason=Forbidden | table sourceIPs{} user.username userAgent verb responseStatus.reason responseStatus.status properties.pod objectRef.namespace |`kubernetes_azure_detect_service_accounts_forbidden_failure_access_filter` - -[ESCU - Kubernetes Azure detect suspicious kubectl calls - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search provides information on Kubectl calls with IP, verb namespace and object access context -action.escu.mappings = {"kill_chain_phases": ["Lateral Movement"]} -action.escu.data_models = [] -action.escu.eli5 = This search provides information on Kubectl calls with IP, verb namespace and object access context -action.escu.how_to_implement = You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics -action.escu.known_false_positives = Kubectl calls are not malicious by nature. However source IP, verb and Object can reveal potential malicious activity, specially suspicious IPs and sensitive objects such as configmaps or secrets -action.escu.creation_date = 2020-05-26 -action.escu.modification_date = 2020-05-26 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Kubernetes Azure detect suspicious kubectl calls - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Kubernetes Sensitive Object Access Activity"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Kubernetes Azure detect suspicious kubectl calls - Rule -schedule_window = auto -action.notable = 1 -action.notable.param.rule_description = This search provides information on 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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `kubernetes_azure` category=kube-audit | spath input=properties.log| search objectRef.resource=secrets OR configmaps |table user.username user.groups{} objectRef.resource objectRef.namespace objectRef.name annotations.authorization.k8s.io/reason |dedup user.username user.groups{} |`kubernetes_azure_detect_suspicious_kubectl_calls_filter` - -[ESCU - Kubernetes Azure pod scan fingerprint - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"kill_chain_phases": ["Reconnaissance"]} -action.escu.data_models = [] -action.escu.eli5 = 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.escu.how_to_implement = You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics -action.escu.known_false_positives = Not all unauthenticated requests are malicious, but source IPs, userAgent, verb, request URI and response status will provide context. -action.escu.creation_date = 2020-05-20 -action.escu.modification_date = 2020-05-20 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Kubernetes Azure pod scan fingerprint - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Kubernetes Scanning Activity"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Kubernetes Azure pod scan fingerprint - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `kubernetes_azure` category=kube-audit | spath input=properties.log | search responseStatus.code=401 | table sourceIPs{} userAgent verb requestURI responseStatus.reason properties.pod |`kubernetes_azure_pod_scan_fingerprint_filter` - -[ESCU - Kubernetes Azure scan fingerprint - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"kill_chain_phases": ["Reconnaissance"]} -action.escu.data_models = [] -action.escu.eli5 = This search provides information of unauthenticated requests via source IP user agent, request URI and response status data against Kubernetes cluster in Azure -action.escu.how_to_implement = You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics -action.escu.known_false_positives = Not all unauthenticated requests are malicious, but source IPs, userAgent, verb, request URI and response status will provide context. -action.escu.creation_date = 2020-05-19 -action.escu.modification_date = 2020-05-19 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Kubernetes Azure scan fingerprint - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Kubernetes Scanning Activity"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Kubernetes Azure scan fingerprint - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `kubernetes_azure` category=kube-audit | spath input=properties.log | search responseStatus.code=401 | table sourceIPs{} userAgent verb requestURI responseStatus.reason |`kubernetes_azure_scan_fingerprint_filter` - -[ESCU - Large Volume of DNS ANY Queries - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.AE", "PR.IP"]} -action.escu.data_models = ["Network_Resolution"] -action.escu.eli5 = The search is used to identify attempts to use your DNS Infrastructure for DDoS purposes via a DNS amplification attack leveraging ANY queries. -action.escu.how_to_implement = To successfully implement this search you must ensure that DNS data is populating the Network_Resolution data model. -action.escu.known_false_positives = Legitimate ANY requests may trigger this search, however it is unusual to see a large volume of them under typical circumstances. You may modify the threshold in the search to better suit your environment. -action.escu.creation_date = 2017-09-20 -action.escu.modification_date = 2017-09-20 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Large Volume of DNS ANY Queries - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["DNS Amplification Attacks"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Large Volume of DNS ANY Queries - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 from datamodel=Network_Resolution where nodename=DNS "DNS.message_type"="QUERY" "DNS.record_type"="ANY" by "DNS.dest" | `drop_dm_object_name("DNS")` | where count>200 | `large_volume_of_dns_any_queries_filter` - -[ESCU - MacOS - Re-opened Applications - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for processes referencing the plist files that determine which applications are re-opened when a user reboots their machine. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Installation", "Command and Control"], "nist": ["DE.DP", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for processes referencing the plist files that determine which applications are re-opened when a user reboots their machine. -action.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest process data from your osquery deployed agents with the [splunk.conf](https://github.com/splunk/TA-osquery/blob/master/config/splunk.conf) pack enabled. Also the [TA-OSquery](https://github.com/splunk/TA-osquery) must be deployed across your indexers and universal forwarders in order to have the data populate the Endpoint data model. -action.escu.known_false_positives = At this stage, there are no known false positives. During testing, no process events refering the com.apple.loginwindow.plist files were observed during normal operation of re-opening applications on reboot. Therefore, it can be asumed that any occurences of this in the process events would be worth investigating. In the event that the legitimate modification by the system of these files is in fact logged to the process log, then the process_name of that process can be whitelisted. -action.escu.creation_date = 2020-02-07 -action.escu.modification_date = 2020-02-07 -action.escu.confidence = high -action.escu.full_search_name = ESCU - MacOS - Re-opened Applications - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = [] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - MacOS - Re-opened Applications - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 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="*com.apple.loginwindow*" by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `macos___re_opened_applications_filter` - -[ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule] -action.escu = 0 -action.escu.enabled = 1 -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. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = 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. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -action.escu.known_false_positives = Legitimate process can have this combination of command-line options, but it's not common. -action.escu.creation_date = 2018-12-03 -action.escu.modification_date = 2018-12-03 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Malicious PowerShell"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule -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. -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 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 | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | search process="*-Exec*" process="*-WindowStyle*" process="*hidden*" process="*New-Object*" process="*System.Net.WebClient*" | `malicious_powershell_process___connect_to_internet_with_hidden_window_filter` - -[ESCU - Malicious PowerShell Process - Encoded Command - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = 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.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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -action.escu.known_false_positives = System administrators may use this option, but it's not common. -action.escu.creation_date = 2018-12-03 -action.escu.modification_date = 2018-12-03 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Malicious PowerShell Process - Encoded Command - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Malicious PowerShell"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Malicious PowerShell Process - Encoded Command - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 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 | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | search process=*-EncodedCommand* OR process=*-enc* | `malicious_powershell_process___encoded_command_filter` - -[ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = 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.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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -action.escu.known_false_positives = There may be legitimate reasons to bypass the PowerShell execution policy. The PowerShell script being run with this parameter should be validated to ensure that it is legitimate. -action.escu.creation_date = 2018-12-03 -action.escu.modification_date = 2018-12-03 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["DHS Report TA18-074A"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = | tstats `security_content_summariesonly` values(Processes.process_id) as process_id, values(Processes.parent_process_id) as parent_process_id values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=powershell.exe AND (Processes.process="* -ex*" OR Processes.process="* bypass *") by Processes.process_id, Processes.user, Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `malicious_powershell_process___execution_policy_bypass_filter` - -[ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule] -action.escu = 0 -action.escu.enabled = 1 -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. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = 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. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -action.escu.known_false_positives = Legitimate process can have this combination of command-line options, but it's not common. -action.escu.creation_date = 2018-12-03 -action.escu.modification_date = 2018-12-03 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Malicious PowerShell"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule -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. -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 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 | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| search (process=*-EncodedCommand* OR process=*-enc*) process=*-Exec* AND process=*-NonI* | `malicious_powershell_process___multiple_suspicious_command_line_arguments_filter` - -[ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for PowerShell processes launched with arguments that have characters indicative of obfuscation on the command-line. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for PowerShell processes launched with arguments that have characters indicative of obfuscation on the command-line. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -action.escu.known_false_positives = These characters might be legitimately on the command-line, but it is not common. -action.escu.creation_date = 2020-01-17 -action.escu.modification_date = 2020-01-17 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Malicious PowerShell"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 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) | `malicious_powershell_process_with_obfuscation_techniques_filter` | search num_obfuscation > 0 - -[ESCU - Monitor DNS For Brand Abuse - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for DNS requests for faux domains similar to the domains that you want to have monitored for abuse. -action.escu.mappings = {"kill_chain_phases": ["Delivery", "Actions on Objectives"]} -action.escu.data_models = ["Network_Resolution"] -action.escu.eli5 = This search looks for DNS requests for faux domains similar to the domains that you want to have monitored for abuse. -action.escu.how_to_implement = You need to ingest data from your DNS logs. Specifically you must ingest the domain that is being queried and the IP of the host originating the request. Ideally, you should also be ingesting the answer to the query and the query type. This approach allows you to also create your own localized passive DNS capability which can aid you in future investigations. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for. -action.escu.known_false_positives = None at this time -action.escu.creation_date = 2017-09-23 -action.escu.modification_date = 2017-09-23 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Monitor DNS For Brand Abuse - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Brand Monitoring"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Monitor DNS For Brand Abuse - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = | tstats `security_content_summariesonly` values(DNS.answer) as IPs min(_time) as firstTime from datamodel=Network_Resolution by DNS.src, DNS.query | `drop_dm_object_name("DNS")` | `security_content_ctime(firstTime)`| `brand_abuse_dns` | `monitor_dns_for_brand_abuse_filter` - -[ESCU - Monitor Email For Brand Abuse - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"]} -action.escu.data_models = ["Email"] -action.escu.eli5 = This search looks for emails claiming to be sent from a domain similar to one that you want to have monitored for abuse. -action.escu.how_to_implement = You need to ingest email header data. Specifically the sender's address (src_user) must be populated. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for. -action.escu.known_false_positives = None at this time -action.escu.creation_date = 2018-01-05 -action.escu.modification_date = 2018-01-05 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Monitor Email For Brand Abuse - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Emails", "Brand Monitoring"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Monitor Email For Brand Abuse - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = | tstats `security_content_summariesonly` values(All_Email.recipient) as recipients, min(_time) as firstTime, max(_time) as lastTime from datamodel=Email by All_Email.src_user, All_Email.message_id | `drop_dm_object_name("All_Email")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | eval temp=split(src_user, "@") | eval email_domain=mvindex(temp, 1) | lookup update=true brandMonitoring_lookup domain as email_domain OUTPUT domain_abuse | search domain_abuse=true | table message_id, src_user, email_domain, recipients, firstTime, lastTime | `monitor_email_for_brand_abuse_filter` - -[ESCU - Monitor Registry Keys for Print Monitors - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 8", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM", "PR.AC"]} -action.escu.data_models = [] -action.escu.eli5 = 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.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report registry modifications. -action.escu.known_false_positives = You will encounter noise from legitimate print-monitor registry entries. -action.escu.creation_date = 2018-11-02 -action.escu.modification_date = 2018-11-02 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Monitor Registry Keys for Print Monitors - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Persistence Techniques"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Monitor Registry Keys for Print Monitors - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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.action=modified AND Registry.registry_path="*CurrentControlSet\\Control\\Print\\Monitors*" by Registry.dest, Registry.registry_key_name Registry.status Registry.user Registry.registry_path Registry.action | `drop_dm_object_name(Registry)` | `monitor_registry_keys_for_print_monitors_filter` - -[ESCU - Monitor Web Traffic For Brand Abuse - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for Web requests to faux domains similar to the one that you want to have monitored for abuse. -action.escu.mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"]} -action.escu.data_models = ["Web"] -action.escu.eli5 = This search looks for Web requests to faux domains similar to the one that you want to have monitored for abuse. -action.escu.how_to_implement = You need to ingest data from your web traffic. This can be accomplished by indexing data from a web proxy, or using a network traffic analysis tool, such as Bro or Splunk Stream. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for. -action.escu.known_false_positives = None at this time -action.escu.creation_date = 2017-09-23 -action.escu.modification_date = 2017-09-23 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Monitor Web Traffic For Brand Abuse - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Brand Monitoring"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Monitor Web Traffic For Brand Abuse - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = | tstats `security_content_summariesonly` values(Web.url) as urls min(_time) as firstTime from datamodel=Web by Web.src | `drop_dm_object_name("Web")` | `security_content_ctime(firstTime)` | `brand_abuse_web` | `monitor_web_traffic_for_brand_abuse_filter` - -[ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search detects Okta login failures due to bad credentials for multiple users originating from the same ip address. -action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} -action.escu.data_models = [] -action.escu.eli5 = This search detects Okta login failures due to bad credentials for multiple users originating from the same ip address. -action.escu.how_to_implement = This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment. -action.escu.known_false_positives = A single public IP address servicing multiple legitmate users may trigger this search. In addition, the threshold of 5 distinct users may be too low for your needs. You may modify the included filter macro XXXXXXXXXXXXX to raise the threshold or except specific IP adresses from triggering this search. -action.escu.creation_date = 2020-04-01 -action.escu.modification_date = 2020-04-01 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Okta Activity"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule -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 Credentails From The Same IP -action.notable.param.security_domain = access -action.notable.param.severity = high -alert.digest_mode = 1 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `okta` outcome.reason=INVALID_CREDENTIALS | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | stats min(_time) as firstTime max(_time) as lastTime dc(user) as distinct_users values(user) as users by src_ip, displayMessage, outcome.reason, country, state, city | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | search distinct_users > 5| `multiple_okta_users_with_invalid_credentails_from_the_same_ip_filter` - -[ESCU - New container uploaded to AWS ECR - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {} -action.escu.data_models = [] -action.escu.eli5 = 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.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. You must also install Cloud Infrastructure data model. Please also customize the `container_implant_aws_detection_filter` macro to filter out the false positives. -action.escu.known_false_positives = Uploading container is a normal behavior from developers or users with access to container registry. -action.escu.creation_date = 2020-02-20 -action.escu.modification_date = 2020-02-20 -action.escu.confidence = high -action.escu.full_search_name = ESCU - New container uploaded to AWS ECR - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Container Implantation Monitoring and Investigation"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - New container uploaded to AWS ECR - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = | tstats count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Cloud_Infrastructure.Compute where Compute.user_type!="AssumeRole" AND Compute.http_user_agent="AWS Internal" AND Compute.event_name="PutImage" by Compute.image_id Compute.src_user Compute.src Compute.region Compute.msg Compute.user_type | `drop_dm_object_name("Compute")` | `new_container_uploaded_to_aws_ecr_filter` - -[ESCU - No Windows Updates in a time frame - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 18"], "nist": ["PR.PT", "PR.MA"]} -action.escu.data_models = ["Updates"] -action.escu.eli5 = 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.escu.how_to_implement = To successfully implement this search, it requires that the 'Update' data model is being populated. This can be accomplished by ingesting Windows events or the Windows Update log via a universal forwarder on the Windows endpoints you wish to monitor. The Windows add-on should be also be installed and configured to properly parse Windows events in Splunk. There may be other data sources which can populate this data model, including vulnerability management systems. -action.escu.known_false_positives = None identified -action.escu.creation_date = 2017-09-15 -action.escu.modification_date = 2017-09-15 -action.escu.confidence = high -action.escu.full_search_name = ESCU - No Windows Updates in a time frame - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Monitor for Updates"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - No Windows Updates in a time frame - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = | tstats `security_content_summariesonly` max(_time) as lastTime from datamodel=Updates where Updates.status=Installed Updates.vendor_product="Microsoft Windows" by Updates.dest Updates.status Updates.vendor_product | rename Updates.dest as Host | rename Updates.status as "Update Status" | rename Updates.vendor_product as Product | eval isOutlier=if(lastTime <= relative_time(now(), "-60d@d"), 1, 0) | `security_content_ctime(lastTime)` | search isOutlier=1 | rename lastTime as "Last Update Time", | table Host, "Update Status", Product, "Last Update Time" | `no_windows_updates_in_a_time_frame_filter` - -[ESCU - Okta Account Lockout Events - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = Detect Okta user lockout events -action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} -action.escu.data_models = [] -action.escu.eli5 = Detect Okta user lockout events -action.escu.how_to_implement = This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment. -action.escu.known_false_positives = None. Account lockouts should be followed up on to determine if the actual user was the one who caused the lockout, or if it was an unauthorized actor. -action.escu.creation_date = 2020-04-01 -action.escu.modification_date = 2020-04-01 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Okta Account Lockout Events - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Okta Activity"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Okta Account Lockout Events - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `okta` displayMessage="Max sign in attempts exceeded" | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, country, state, city, src_ip |`okta_account_lockout_events_filter` - -[ESCU - Okta Failed SSO Attempts - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = Detect failed Okta SSO events -action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} -action.escu.data_models = [] -action.escu.eli5 = Detect failed Okta SSO events -action.escu.how_to_implement = This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment. -action.escu.known_false_positives = There may be a faulty config preventing legitmate users from accessing apps they should have access to. -action.escu.creation_date = 2020-04-01 -action.escu.modification_date = 2020-04-01 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Okta Failed SSO Attempts - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Okta Activity"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Okta Failed SSO Attempts - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `okta` displayMessage="User attempted unauthorized access to app" | stats min(_time) as firstTime max(_time) as lastTime values(app) as Apps count by user, result ,displayMessage, src_ip | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`|`okta_failed_sso_attempts_filter` - -[ESCU - Okta User Logins From Multiple Cities - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search detects logins from the same user from different states in a 24 hour period. -action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} -action.escu.data_models = [] -action.escu.eli5 = This search detects logins from the same user from different states in a 24 hour period. -action.escu.how_to_implement = This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment. -action.escu.known_false_positives = Users in your enviornment may legitmately be travelling and loggin in from different locations. This search is useful for those users that should *not* be travelling for some reason, such as the COVID-19 pandemic. The search also relies on the geographical information being populated in the Okta logs. It is also possible that a connection from another region may be attributed to a login from a remote VPN endpoint. -action.escu.creation_date = 2020-04-01 -action.escu.modification_date = 2020-04-01 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Okta User Logins From Multiple Cities - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Okta Activity"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Okta User Logins From Multiple Cities - Rule -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 states 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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `okta` displayMessage="User login to Okta" client.geographicalContext.city!=null | stats min(_time) as firstTime max(_time) as lastTime dc(client.geographicalContext.city) as locations values(client.geographicalContext.city) as cities values(client.geographicalContext.state) as states by user | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` |`okta_user_logins_from_multiple_cities_filter`| search locations > 1 - -[ESCU - Open Redirect in Splunk Web - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search allows you to look for evidence of exploitation for CVE-2016-4859, the Splunk Open Redirect Vulnerability. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "RS.MI", "PR.PT", "PR.AC", "PR.IP", "DE.CM"]} -action.escu.data_models = [] -action.escu.eli5 = This search allows you to look for evidence of exploitation for CVE-2016-4859, the Splunk Open Redirect Vulnerability. -action.escu.how_to_implement = No extra steps needed to implement this search. -action.escu.known_false_positives = None identified -action.escu.creation_date = 2017-09-19 -action.escu.modification_date = 2017-09-19 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Open Redirect in Splunk Web - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Splunk Enterprise Vulnerability"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Open Redirect in Splunk Web - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = index=_internal sourcetype=splunk_web_access return_to="/%09/*" | `open_redirect_in_splunk_web_filter` - -[ESCU - Osquery pack - ColdRoot detection - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for ColdRoot events from the osx-attacks osquery pack. -action.escu.mappings = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Installation", "Command and Control"], "nist": ["DE.DP", "DE.CM", "PR.PT"]} -action.escu.data_models = [] -action.escu.eli5 = This search looks for ColdRoot events from the osx-attacks osquery pack. -action.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest data from your osquery deployed agents with the [osx-attacks.conf](https://github.com/facebook/osquery/blob/experimental/packs/osx-attacks.conf#L599) pack enabled. Also the [TA-OSquery](https://github.com/d1vious/TA-osquery) must be deployed across your indexers and universal forwarders in order to have the osquery data populate the Alerts data model -action.escu.known_false_positives = There are no known false positives. -action.escu.creation_date = 2019-01-29 -action.escu.modification_date = 2019-01-29 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Osquery pack - ColdRoot detection - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["ColdRoot MacOS RAT"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Osquery pack - ColdRoot detection - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = | from datamodel Alerts.Alerts | search app=osquery:results (name=pack_osx-attacks_OSX_ColdRoot_RAT_Launchd OR name=pack_osx-attacks_OSX_ColdRoot_RAT_Files) | rename columns.path as path | bucket _time span=30s | stats count(path) by _time, host, user, path | `osquery_pack___coldroot_detection_filter` - -[ESCU - Overwriting Accessibility Binaries - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = 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.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 = Microsoft may provide updates to these binaries. Verify that these changes do not correspond with your normal software update cycle. -action.escu.creation_date = 2020-03-16 -action.escu.modification_date = 2020-03-16 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Overwriting Accessibility Binaries - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Windows Privilege Escalation"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Overwriting Accessibility Binaries - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 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 - Process Execution via WMI - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for processes launched via WMI. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} -action.escu.data_models = [] -action.escu.eli5 = This search looks for processes launched via WMI. -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. The command-line arguments are mapped to the "process" field in the Endpoint data model. -action.escu.known_false_positives = Although unlikely, administrators may use wmi to execute commands for legitimate purposes. -action.escu.creation_date = 2020-03-16 -action.escu.modification_date = 2020-03-16 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Process Execution via WMI - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious WMI Use"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Process Execution via WMI - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes where Processes.parent_process_name = *WmiPrvSE.exe by Processes.user Processes.dest Processes.process_name | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| `process_execution_via_wmi_filter` - -[ESCU - Processes Tapping Keyboard Events - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Command and Control"], "nist": ["DE.DP"]} -action.escu.data_models = [] -action.escu.eli5 = 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.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest data from your osquery deployed agents with the [osx-attacks.conf](https://github.com/facebook/osquery/blob/experimental/packs/osx-attacks.conf#L599) pack enabled. Also the [TA-OSquery](https://github.com/d1vious/TA-osquery) must be deployed across your indexers and universal forwarders in order to have the osquery data populate the Alerts data model. -action.escu.known_false_positives = There might be some false positives as keyboard event taps are used by processes like Siri and Zoom video chat, for some good examples of processes to exclude please see [this](https://github.com/facebook/osquery/pull/5345#issuecomment-454639161) comment. -action.escu.creation_date = 2019-01-25 -action.escu.modification_date = 2019-01-25 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Processes Tapping Keyboard Events - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["ColdRoot MacOS RAT"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Processes Tapping Keyboard Events - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = | from datamodel Alerts.Alerts | search app=osquery:results name=pack_osx-attacks_Keyboard_Event_Taps | rename columns.cmdline as cmd, columns.name as process_name, columns.pid as process_id| dedup host,process_name | table host,process_name, cmd, process_id | `processes_tapping_keyboard_events_filter` - -[ESCU - Processes created by netsh - Rule] -action.escu = 0 -action.escu.enabled = 1 -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. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = 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. -action.escu.how_to_implement = To successfully implement this search, you must be ingesting logs with the process name, command-line arguments, and parent processes from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. -action.escu.known_false_positives = It is unusual for netsh.exe to have any child processes in most environments. It makes sense to investigate the child process and verify whether the process spawned is legitimate. -action.escu.creation_date = 2020-03-02 -action.escu.modification_date = 2020-03-02 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Processes created by netsh - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Netsh Abuse"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Processes created by netsh - Rule -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. -action.notable.param.rule_title = Processes created by netsh -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -alert.digest_mode = 1 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.parent_process="*C:\\Windows\\System32\\netsh.exe*" by Processes.user Processes.dest Processes.parent_process Processes.parent_process_name Processes.process_name | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `processes_created_by_netsh_filter` - -[ESCU - Processes launching netsh - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059", "T1089"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = 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.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model -action.escu.known_false_positives = Some VPN applications are known to launch netsh.exe. Outside of these instances, it is unusual for an executable to launch netsh.exe and run commands. -action.escu.creation_date = 2018-11-02 -action.escu.modification_date = 2018-11-02 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Processes launching netsh - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Netsh Abuse", "Disabling Security Tools", "DHS Report TA18-074A"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Processes launching netsh - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 values(Processes.process) min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process=netsh.exe by Processes.parent_process Processes.process_name Processes.user Processes.dest | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | `processes_launching_netsh_filter` - -[ESCU - Prohibited Network Traffic Allowed - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Delivery", "Command and Control"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "PR.AC"]} -action.escu.data_models = ["Network_Traffic"] -action.escu.eli5 = 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.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest data from firewalls or other network control devices that mediate the traffic allowed into an environment. This is necessary so that the search can identify an 'action' taken on the traffic of interest. The search requires the Network_Traffic data model be populated. -action.escu.known_false_positives = None identified -action.escu.creation_date = 2017-09-11 -action.escu.modification_date = 2017-09-11 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Prohibited Network Traffic Allowed - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Command and Control", "Ransomware", "Prohibited Traffic Allowed or Protocol Mismatch"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Prohibited Network Traffic Allowed - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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=Network_Traffic where All_Traffic.action = allowed by All_Traffic.src_ip All_Traffic.dest_ip All_Traffic.dest_port All_Traffic.action | lookup update=true interesting_ports_lookup dest_port as All_Traffic.dest_port OUTPUT app is_prohibited note transport | search is_prohibited=true | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name("All_Traffic")` | `prohibited_network_traffic_allowed_filter` - -[ESCU - Prohibited Software On Endpoint - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for applications on the endpoint that you have marked as prohibited. -action.escu.mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for applications on the endpoint that you have marked as prohibited. -action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. This is typically populated via endpoint detection-and-response products, such as Carbon Black or endpoint data sources, such as Sysmon. The data used for this search is usually generated via logs that report process tracking in your Windows audit settings. In addition, you must also have only the `process_name` (not the entire process path) marked as "prohibited" in the Enterprise Security `interesting processes` table. To include the process names marked as "prohibited", which is included with ES Content Updates, run the included search Add Prohibited Processes to Enterprise Security. -action.escu.known_false_positives = None identified -action.escu.creation_date = 2019-10-11 -action.escu.modification_date = 2019-10-11 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Prohibited Software On Endpoint - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["SamSam Ransomware", "Emotet Malware DHS Report TA18-201A ", "Monitor for Unauthorized Software"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Prohibited Software On Endpoint - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 by Processes.dest Processes.user Processes.process_name | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `drop_dm_object_name(Processes)` | `prohibited_softwares` | `prohibited_software_on_endpoint_filter` - -[ESCU - Protocol or Port Mismatch - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE", "PR.AC"]} -action.escu.data_models = ["Network_Traffic"] -action.escu.eli5 = 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.escu.how_to_implement = Running this search properly requires a technology that can inspect network traffic and identify common protocols. Technologies such as Bro and Palo Alto Networks firewalls are two examples that will identify protocols via inspection, and not just assume a specific protocol based on the transport protocol and ports. -action.escu.known_false_positives = None identified -action.escu.creation_date = 2017-09-11 -action.escu.modification_date = 2017-09-11 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Protocol or Port Mismatch - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Command and Control", "Prohibited Traffic Allowed or Protocol Mismatch"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Protocol or Port Mismatch - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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=Network_Traffic where (All_Traffic.app=dns NOT All_Traffic.dest_port=53) OR ((All_Traffic.app=web-browsing OR All_Traffic.app=http) NOT (All_Traffic.dest_port=80 OR All_Traffic.dest_port=8080 OR All_Traffic.dest_port=8000)) OR (All_Traffic.app=ssl NOT (All_Traffic.dest_port=443 OR All_Traffic.dest_port=8443)) OR (All_Traffic.app=smtp NOT All_Traffic.dest_port=25) by All_Traffic.src_ip, All_Traffic.dest_ip, All_Traffic.app, All_Traffic.dest_port |`security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name("All_Traffic")` | `protocol_or_port_mismatch_filter` - -[ESCU - Protocols passing authentication in cleartext - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 9", "CIS 14"], "kill_chain_phases": ["Reconnaissance", "Actions on Objectives"], "nist": ["PR.PT", "DE.AE", "PR.AC", "PR.DS"]} -action.escu.data_models = ["Network_Traffic"] -action.escu.eli5 = 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.escu.how_to_implement = This search requires you to be ingesting your network traffic, and populating the Network_Traffic data model. -action.escu.known_false_positives = Some networks may use kerberized FTP or telnet servers, however, this is rare. -action.escu.creation_date = 2017-09-15 -action.escu.modification_date = 2017-09-15 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Protocols passing authentication in cleartext - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Use of Cleartext Protocols"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Protocols passing authentication in cleartext - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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=Network_Traffic where All_Traffic.protocol="tcp" AND (All_Traffic.dest_port="23" OR All_Traffic.dest_port="143" OR All_Traffic.dest_port="110" OR (All_Traffic.dest_port="21" AND All_Traffic.user != "anonymous")) groupby All_Traffic.user All_Traffic.src All_Traffic.dest All_Traffic.dest_port | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name("All_Traffic")` | `protocols_passing_authentication_in_cleartext_filter` - -[ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = The search looks for reg.exe modifying registry keys that define Windows services and their configurations. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack": ["T1050", "T1031", "T1089"], "nist": ["PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.CM"]} -action.escu.data_models = [] -action.escu.eli5 = The search looks for reg.exe modifying registry keys that define Windows services and their configurations. -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 = It is unusual for a service to be created or modified by directly manipulating the registry. However, there may be legitimate instances of this behavior. It is important to validate and investigate, as appropriate. -action.escu.creation_date = 2019-03-01 -action.escu.modification_date = 2019-03-01 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Windows Persistence Techniques", "Windows Service Abuse"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule -schedule_window = auto -action.notable = 1 -action.notable.param.nes_fields = ['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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 values(Processes.process_name) as process_name values(Processes.parent_process_name) as parent_process_name FROM datamodel=Endpoint.Processes where Processes.process_name = reg.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="*\\services\\*" by Registry.process_id Registry.dest | `drop_dm_object_name("Registry")` | table process_id dest registry_path] | `reg_exe_manipulating_windows_services_registry_keys_filter` - -[ESCU - Reg exe used to hide files directories via registry keys - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = The search looks for command-line arguments used to hide a file or directory using the reg add command. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = The search looks for command-line arguments used to hide a file or directory using the reg add command. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -action.escu.known_false_positives = None at the moment -action.escu.creation_date = 2019-02-27 -action.escu.modification_date = 2019-02-27 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Reg exe used to hide files directories via registry keys - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Persistence Techniques", "Windows Defense Evasion Tactics"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Reg exe used to hide files directories via registry keys - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = | tstats `security_content_summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = reg.exe Processes.process="*add*" Processes.process="*Hidden*" Processes.process="*REG_DWORD*" by Processes.process_name Processes.parent_process_name Processes.dest Processes.user| `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` |`security_content_ctime(lastTime)`| regex process = "(/d\s+2)" | `reg_exe_used_to_hide_files_directories_via_registry_keys_filter` - -[ESCU - Registry Keys Used For Persistence - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = The search looks for modifications to registry keys that can be used to launch an application or service at system startup. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1103", "T1131"], "nist": ["PR.PT", "DE.CM", "DE.AE"]} -action.escu.data_models = [] -action.escu.eli5 = The search looks for modifications to registry keys that can be used to launch an application or service at system startup. -action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, 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. -action.escu.known_false_positives = There are many legitimate applications that must execute on system startup and will use these registry keys to accomplish that task. -action.escu.creation_date = 2017-10-10 -action.escu.modification_date = 2017-10-10 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Registry Keys Used For Persistence - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Persistence Techniques", "Emotet Malware DHS Report TA18-201A ", "Ransomware", "DHS Report TA18-074A", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Suspicious MSHTA Activity"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Registry Keys Used For Persistence - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 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=*currentversion\\run* OR Registry.registry_path=*currentVersion\\Windows\\Appinit_Dlls* OR Registry.registry_path=CurrentVersion\\Winlogon\\Shell* OR Registry.registry_path=*CurrentVersion\\Winlogon\\Userinit* OR Registry.registry_path=*CurrentVersion\\Winlogon\\VmApplet* OR Registry.registry_path=*currentversion\\policies\\explorer\\run* OR Registry.registry_path=*currentversion\\runservices* OR Registry.registry_path=*\\CurrentControlSet\\Control\\Lsa\\* OR Registry.registry_path="*Microsoft\\Windows NT\\CurrentVersion\\Image File Execution Options*" OR Registry.registry_path=HKLM\\SOFTWARE\\Microsoft\\Netsh\\*) by Registry.dest , Registry.status, Registry.user | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `drop_dm_object_name(Registry)` | `registry_keys_used_for_persistence_filter` - -[ESCU - Registry Keys Used For Privilege Escalation - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [] -action.escu.eli5 = 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.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, 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. -action.escu.known_false_positives = There are many legitimate applications that must execute upon system startup and will use these registry keys to accomplish that task. -action.escu.creation_date = 2020-03-02 -action.escu.modification_date = 2020-03-02 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Registry Keys Used For Privilege Escalation - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Windows Privilege Escalation", "Suspicious Windows Registry Activities"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Registry Keys Used For Privilege Escalation - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 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="*Microsoft\\Windows NT\\CurrentVersion\\Image File Execution Options*") AND (Registry.registry_key_name=GlobalFlag OR Registry.registry_key_name=Debugger) by Registry.dest Registry.user | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `drop_dm_object_name(Registry)` | `registry_keys_used_for_privilege_escalation_filter` - -[ESCU - Registry Keys for Creating SHIM Databases - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for registry activity associated with application compatibility shims, which can be leveraged by attackers for various nefarious purposes. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1138"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [] -action.escu.eli5 = This search looks for registry activity associated with application compatibility shims, which can be leveraged by attackers for various nefarious purposes. -action.escu.how_to_implement = To successfully implement this search, you must populate the Change_Analysis data model. This is typically populated via endpoint detection and response products, such as Carbon Black or other 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. -action.escu.known_false_positives = There are many legitimate applications that leverage shim databases for compatibility purposes for legacy applications -action.escu.creation_date = 2017-09-15 -action.escu.modification_date = 2017-09-15 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Registry Keys for Creating SHIM Databases - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Persistence Techniques"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Registry Keys for Creating SHIM Databases - Rule -schedule_window = auto -action.notable = 1 -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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=Change_Analysis.All_Changes where All_Changes.object_category=registry AND (All_Changes.object_path="*CurrentVersion\\AppCompatFlags\\Custom*" OR All_Changes.object_path="*CurrentVersion\\AppCompatFlags\\InstalledSDB*") by All_Changes.dest, All_Changes.command, All_Changes.user, All_Changes.object, All_Changes.object_path | `drop_dm_object_name("All_Changes")` | `registry_keys_for_creating_shim_databases_filter` - -[ESCU - Remote Desktop Network Bruteforce - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 12", "CIS 9", "CIS 16"], "kill_chain_phases": ["Reconnaissance", "Delivery"], "mitre_attack": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -action.escu.data_models = ["Network_Traffic"] -action.escu.eli5 = 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.escu.how_to_implement = You must ensure that your network traffic data is populating the Network_Traffic data model. -action.escu.known_false_positives = RDP gateways may have unusually high amounts of traffic from all other hosts' RDP applications in the network. -action.escu.creation_date = 2018-12-14 -action.escu.modification_date = 2018-12-14 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Remote Desktop Network Bruteforce - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["SamSam Ransomware"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Remote Desktop Network Bruteforce - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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=Network_Traffic where All_Traffic.app=rdp by All_Traffic.src All_Traffic.dest All_Traffic.dest_port | eventstats stdev(count) AS stdev avg(count) AS avg p50(count) AS p50 | where count>(avg + stdev*2) | rename All_Traffic.src AS src All_Traffic.dest AS dest | table firstTime lastTime src dest count avg p50 stdev | `remote_desktop_network_bruteforce_filter` - -[ESCU - Remote Desktop Network Traffic - Rule] -action.escu = 0 -action.escu.enabled = 1 -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 allows for whitelisting both source and destination hosts to remove them from the output of the search so you can focus on the uncommon uses of remote desktop on your network. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 9", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -action.escu.data_models = ["Network_Traffic"] -action.escu.eli5 = 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 allows for whitelisting both source and destination hosts to remove them from the output of the search so you can focus on the uncommon uses of remote desktop on your network. -action.escu.how_to_implement = To successfully implement this search you need to identify systems that commonly originate remote desktop traffic and that commonly receive remote desktop traffic. You can use the included support search "Identify Systems Creating Remote Desktop Traffic" to identify systems that originate the traffic and the search "Identify Systems Receiving Remote Desktop Traffic" to identify systems that receive a lot of remote desktop traffic. After identifying these systems, you will need to add the "common_rdp_source" or "common_rdp_destination" category to that system depending on the usage, using the Enterprise Security Assets and Identities framework. This can be done by adding an entry in the assets.csv file located in SA-IdentityManagement/lookups. -action.escu.known_false_positives = Remote Desktop may be used legitimately by users on the network. -action.escu.creation_date = 2020-01-10 -action.escu.modification_date = 2020-01-10 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Remote Desktop Network Traffic - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["SamSam Ransomware", "Hidden Cobra Malware", "Lateral Movement"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Remote Desktop Network Traffic - Rule -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 allows for whitelisting both source and destination hosts to remove them from the output of the search 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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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=Network_Traffic where All_Traffic.dest_port=3389 AND All_Traffic.dest_category!=common_rdp_destination AND All_Traffic.src_category!=common_rdp_source by All_Traffic.src All_Traffic.dest All_Traffic.dest_port | `drop_dm_object_name("All_Traffic")` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `remote_desktop_network_traffic_filter` - -[ESCU - Remote Desktop Process Running On System - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 3", "CIS 9", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = 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.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. The search requires you to identify systems that do not commonly use remote desktop. You can use the included support search "Identify Systems Using Remote Desktop" to identify these systems. After identifying them, you will need to add the "common_rdp_source" category to that system using the Enterprise Security Assets and Identities framework. This can be done by adding an entry in the assets.csv file located in `SA-IdentityManagement/lookups`. -action.escu.known_false_positives = Remote Desktop may be used legitimately by users on the network. -action.escu.creation_date = 2020-01-13 -action.escu.modification_date = 2020-01-13 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Remote Desktop Process Running On System - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Hidden Cobra Malware", "Lateral Movement"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Remote Desktop Process Running On System - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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=*mstsc.exe AND Processes.dest_category!=common_rdp_source by Processes.dest Processes.user Processes.process | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `drop_dm_object_name(Processes)` | `remote_desktop_process_running_on_system_filter` - -[ESCU - Remote Process Instantiation via WMI - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for wmic.exe being launched with parameters to spawn a process on a remote system. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for wmic.exe being launched with parameters to spawn a process on a remote system. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -action.escu.known_false_positives = The wmic.exe utility is a benign Windows application. It may be used legitimately by Administrators with these parameters for remote system administration, but it's relatively uncommon. -action.escu.creation_date = 2019-02-27 -action.escu.modification_date = 2019-02-27 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Remote Process Instantiation via WMI - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Ransomware", "Suspicious WMI Use"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Remote Process Instantiation via WMI - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = | tstats `security_content_summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = wmic.exe Processes.process="*/node*" Processes.process="*process*" Processes.process="*call*" Processes.process="*create*" by Processes.process_name Processes.parent_process_name Processes.dest Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` |`security_content_ctime(lastTime)` | `remote_process_instantiation_via_wmi_filter` - -[ESCU - Remote Registry Key modifications - Rule] -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.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 products, 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. -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. -action.escu.creation_date = 2020-03-02 -action.escu.modification_date = 2020-03-02 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Remote Registry Key modifications - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Persistence Techniques", "Windows Defense Evasion Tactics"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Remote Registry Key modifications - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 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 -action.escu.enabled = 1 -description = This search looks for wmic.exe being launched with parameters to operate on remote systems. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for wmic.exe being launched with parameters to operate on remote systems. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -action.escu.known_false_positives = Administrators may use this legitimately to gather info from remote systems. -action.escu.creation_date = 2018-12-03 -action.escu.modification_date = 2018-12-03 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Remote WMI Command Attempt - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious WMI Use"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Remote WMI Command Attempt - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 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=wmic.exe AND Processes.process= */node* by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `remote_wmi_command_attempt_filter` - -[ESCU - RunDLL Loading DLL By Ordinal - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for DLLs under %AppData% being loaded by rundll32.exe that are calling the exported function at ordinal 2. Calling exported functions by ordinal is not as common as calling by exported name. There was a bug fixed in IDAPro on 2016-08-08 that would not display functions without names. Calling functions by ordinal would overcome the lack of name and make it harder for analyst to reverse engineer. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack": ["T1085"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for DLLs under %AppData% being loaded by rundll32.exe that are calling the exported function at ordinal 2. Calling exported functions by ordinal is not as common as calling by exported name. There was a bug fixed in IDAPro on 2016-08-08 that would not display functions without names. Calling functions by ordinal would overcome the lack of name and make it harder for analyst to reverse engineer. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -action.escu.known_false_positives = While not common, loading a DLL under %AppData% and calling a function by ordinal is possible by a legitimate process -action.escu.creation_date = 2019-02-27 -action.escu.modification_date = 2019-02-27 -action.escu.confidence = high -action.escu.full_search_name = ESCU - RunDLL Loading DLL By Ordinal - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Unusual Processes"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - RunDLL Loading DLL By Ordinal - Rule -schedule_window = auto -action.notable = 1 -action.notable.param.nes_fields = ['user', 'dest'] -action.notable.param.rule_description = This search looks for DLLs under %AppData% being loaded by rundll32.exe that are calling the exported function at ordinal 2. Calling exported functions by ordinal is not as common as calling by exported name. There was a bug fixed in IDAPro on 2016-08-08 that would not display functions without names. Calling functions by ordinal would overcome the lack of name and make it harder for analyst to reverse engineer. -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = | tstats `security_content_summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = rundll32.exe Processes.process="*AppData*" Processes.process="*,#2" by Processes.process_name Processes.parent_process_name Processes.dest Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `rundll_loading_dll_by_ordinal_filter` - -[ESCU - SMB Traffic Spike - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for spikes in the number of Server Message Block (SMB) traffic connections. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -action.escu.data_models = ["Network_Traffic"] -action.escu.eli5 = This search looks for spikes in the number of Server Message Block (SMB) traffic connections. -action.escu.how_to_implement = This search requires you to be ingesting your network traffic logs and populating the `Network_Traffic` data model. -action.escu.known_false_positives = A file server may experience high-demand loads that could cause this analytic to trigger. -action.escu.creation_date = 2020-01-22 -action.escu.modification_date = 2020-01-22 -action.escu.confidence = high -action.escu.full_search_name = ESCU - SMB Traffic Spike - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Ransomware", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "DHS Report TA18-074A"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - SMB Traffic Spike - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 from datamodel=Network_Traffic where All_Traffic.dest_port=139 OR All_Traffic.dest_port=445 OR All_Traffic.app=smb by _time span=1h, All_Traffic.src | `drop_dm_object_name("All_Traffic")` | eventstats max(_time) as maxtime | stats count as num_data_samples max(eval(if(_time >= relative_time(maxtime, "-70m@m"), count, null))) as count avg(eval(if(_time upperBound AND num_data_samples >=50, 1, 0) | where isOutlier=1 | table src count | `smb_traffic_spike_filter` - -[ESCU - SMB Traffic Spike - MLTK - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search uses the Machine Learning Toolkit (MLTK) to identify spikes in the number of Server Message Block (SMB) connections. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -action.escu.data_models = ["Network_Traffic"] -action.escu.eli5 = This search uses the Machine Learning Toolkit (MLTK) to identify spikes in the number of Server Message Block (SMB) connections. -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, the Machine Learning Toolkit (MLTK) version 4.2 or greater must be installed on your search heads, along with any required dependencies. Finally, the support search "Baseline of SMB Traffic - MLTK" must be executed before this detection search, because it builds a machine-learning (ML) model over the historical data used by this search. It is important that this search is run in the same app context as the associated support search, so that the model created by the support search is available for use. You should periodically re-run the support search to rebuild the model with the latest data available in your environment.\ -This search produces a field (Number of events,count) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. This field contributes additional context to the notable. To see the additional metadata, add the following field, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry): \ -1. **Label:** Number of events, **Field:** count\ -Detailed documentation on how to create a new field within Incident Review is found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -action.escu.known_false_positives = If you are seeing more results than desired, you may consider reducing the value of the threshold in the search. You should also periodically re-run the support search to re-build the ML model on the latest data. Please update the `smb_traffic_spike_mltk_filter` macro to filter out false positive results -action.escu.creation_date = 2020-01-22 -action.escu.modification_date = 2020-01-22 -action.escu.confidence = high -action.escu.full_search_name = ESCU - SMB Traffic Spike - MLTK - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Ransomware", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "DHS Report TA18-074A"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - SMB Traffic Spike - MLTK - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 values(All_Traffic.dest_ip) as dest values(All_Traffic.dest_port) as port from datamodel=Network_Traffic where All_Traffic.dest_port=139 OR All_Traffic.dest_port=445 OR All_Traffic.app=smb by _time span=1h, All_Traffic.src | eval HourOfDay=strftime(_time, "%H") | eval DayOfWeek=strftime(_time, "%A") | `drop_dm_object_name(All_Traffic)` | apply smb_pdfmodel threshold=0.001 | rename "IsOutlier(count)" as isOutlier | search isOutlier > 0 | sort -count | table _time src dest port count | `smb_traffic_spike___mltk_filter` - -[ESCU - SQL Injection with Long URLs - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for long URLs that have several SQL commands visible within them. -action.escu.mappings = {"cis20": ["CIS 4", "CIS 13", "CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1043"], "nist": ["PR.DS", "ID.RA", "PR.PT", "PR.IP", "DE.CM"]} -action.escu.data_models = ["Web"] -action.escu.eli5 = This search looks for long URLs that have several SQL commands visible within them. -action.escu.how_to_implement = To successfully implement this search, you need to be monitoring network communications to your web servers or ingesting your HTTP logs and populating the Web data model. You must also identify your web servers in the Enterprise Security assets table. -action.escu.known_false_positives = It's possible that legitimate traffic will have long URLs or long user agent strings and that common SQL commands may be found within the URL. Please investigate as appropriate. -action.escu.creation_date = 2017-09-19 -action.escu.modification_date = 2017-09-19 -action.escu.confidence = high -action.escu.full_search_name = ESCU - SQL Injection with Long URLs - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["SQL Injection"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - SQL Injection with Long URLs - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 from datamodel=Web where Web.dest_category=web_server AND (Web.url_length > 1024 OR Web.http_user_agent_length > 200) by Web.src Web.dest Web.url Web.url_length Web.http_user_agent | `drop_dm_object_name("Web")` | eval num_sql_cmds=mvcount(split(url, "alter%20table")) + mvcount(split(url, "between")) + mvcount(split(url, "create%20table")) + mvcount(split(url, "create%20database")) + mvcount(split(url, "create%20index")) + mvcount(split(url, "create%20view")) + mvcount(split(url, "delete")) + mvcount(split(url, "drop%20database")) + mvcount(split(url, "drop%20index")) + mvcount(split(url, "drop%20table")) + mvcount(split(url, "exists")) + mvcount(split(url, "exec")) + mvcount(split(url, "group%20by")) + mvcount(split(url, "having")) + mvcount(split(url, "insert%20into")) + mvcount(split(url, "inner%20join")) + mvcount(split(url, "left%20join")) + mvcount(split(url, "right%20join")) + mvcount(split(url, "full%20join")) + mvcount(split(url, "select")) + mvcount(split(url, "distinct")) + mvcount(split(url, "select%20top")) + mvcount(split(url, "union")) + mvcount(split(url, "xp_cmdshell")) - 24 | where num_sql_cmds > 3 | `sql_injection_with_long_urls_filter` - -[ESCU - Samsam Test File Write - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = The search looks for a file named "test.txt" written to the windows system directory tree, which is consistent with Samsam propagation. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Delivery"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = The search looks for a file named "test.txt" written to the windows system directory tree, which is consistent with Samsam propagation. -action.escu.how_to_implement = You must be ingesting data that records the file-system 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 = No false positives have been identified. -action.escu.creation_date = 2018-12-14 -action.escu.modification_date = 2018-12-14 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Samsam Test File Write - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["SamSam Ransomware"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Samsam Test File Write - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_name) as file_name from datamodel=Endpoint.Filesystem where Filesystem.file_path=*\\windows\\system32\\test.txt by Filesystem.file_path | `drop_dm_object_name(Filesystem)` | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `samsam_test_file_write_filter` - -[ESCU - Sc exe Manipulating Windows Services - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for arguments to sc.exe indicating the creation or modification of a Windows service. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack": ["T1050", "T1031", "T1089"], "nist": ["PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for arguments to sc.exe indicating the creation or modification of a Windows service. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -action.escu.known_false_positives = Using sc.exe to manipulate Windows services is uncommon. However, there may be legitimate instances of this behavior. It is important to validate and investigate as appropriate. -action.escu.creation_date = 2019-02-27 -action.escu.modification_date = 2019-02-27 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Sc exe Manipulating Windows Services - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Windows Persistence Techniques", "Windows Service Abuse", "Disabling Security Tools", "DHS Report TA18-074A", "Orangeworm Attack Group"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Sc exe Manipulating Windows Services - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = | tstats `security_content_summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = sc.exe (Processes.process="* create *" OR Processes.process="* config *") by Processes.process_name Processes.parent_process_name Processes.dest Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `sc_exe_manipulating_windows_services_filter` - -[ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for flags passed to schtasks.exe on the command-line that indicate a task name associated with the Dragonfly threat actor was created or deleted. -action.escu.mappings = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053"], "nist": ["PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for flags passed to schtasks.exe on the command-line that indicate a task name associated with the Dragonfly threat actor was created or deleted. -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. The command-line arguments are mapped to the "process" field in the Endpoint data model. -action.escu.known_false_positives = No known false positives -action.escu.creation_date = 2020-03-16 -action.escu.modification_date = 2020-03-16 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["DHS Report TA18-074A"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule -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 name associated with the Dragonfly threat actor was created or deleted. -action.notable.param.rule_title = Scheduled Task Name Used by Dragonfly Threat Actors -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -alert.digest_mode = 1 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 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=schtasks.exe by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | search (process=*delete* OR process=*create*) process=*reset* | `scheduled_task_name_used_by_dragonfly_threat_actors_filter` - -[ESCU - Scheduled tasks used in BadRabbit ransomware - Rule] -action.escu = 0 -action.escu.enabled = 1 -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. -action.escu.mappings = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053"], "nist": ["PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = 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. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -action.escu.known_false_positives = No known false positives -action.escu.creation_date = 2019-02-28 -action.escu.modification_date = 2019-02-28 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Scheduled tasks used in BadRabbit ransomware - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Ransomware"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Scheduled tasks used in BadRabbit ransomware - Rule -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. -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 values(Processes.process) as process from datamodel=Endpoint.Processes where Processes.process_name=schtasks.exe (Processes.process= "*create*" OR Processes.process= "*delete*") by Processes.parent_process Processes.process_name Processes.user | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | search (process=*rhaegal* OR process=*drogon* OR *viserion_*) | `scheduled_tasks_used_in_badrabbit_ransomware_filter` - -[ESCU - Schtasks scheduling job on remote system - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053"], "nist": ["PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = 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.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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -action.escu.known_false_positives = Administrators may create jobs on remote systems, but this activity is usually limited to a small set of hosts or users. It is important to validate and investigate as appropriate. -action.escu.creation_date = 2020-01-10 -action.escu.modification_date = 2020-01-10 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Schtasks scheduling job on remote system - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Lateral Movement"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Schtasks scheduling job on remote system - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 = schtasks.exe Processes.process="*/create*" Processes.process="* /s *" 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)` | `schtasks_scheduling_job_on_remote_system_filter` - -[ESCU - Schtasks used for forcing a reboot - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053"], "nist": ["PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for flags passed to schtasks.exe on the command-line that indicate that a forced reboot of system is scheduled. -action.escu.how_to_implement = To successfully implement this search 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. -action.escu.known_false_positives = Administrators may create jobs on systems forcing reboots to perform updates, maintenance, etc. -action.escu.creation_date = 2019-02-27 -action.escu.modification_date = 2019-02-27 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Schtasks used for forcing a reboot - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Windows Persistence Techniques", "Ransomware"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Schtasks used for forcing a reboot - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = | tstats `security_content_summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = schtasks.exe Processes.process="*shutdown*" Processes.process="*/r*" Processes.process="*/f*" by Processes.process_name Processes.parent_process_name Processes.dest Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `schtasks_used_for_forcing_a_reboot_filter` - -[ESCU - Script Execution via WMI - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for scripts launched via WMI. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} -action.escu.data_models = [] -action.escu.eli5 = This search looks for scripts launched via WMI. -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. The command-line arguments are mapped to the "process" field in the Endpoint data model. -action.escu.known_false_positives = Although unlikely, administrators may use wmi to launch scripts for legitimate purposes. -action.escu.creation_date = 2020-03-16 -action.escu.modification_date = 2020-03-16 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Script Execution via WMI - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious WMI Use"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Script Execution via WMI - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes where Processes.process_name = "scrcons.exe" by Processes.user Processes.dest Processes.process_name | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| `script_execution_via_wmi_filter` - -[ESCU - Shim Database File Creation - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1138"], "nist": ["DE.CM"]} -action.escu.data_models = [] -action.escu.eli5 = 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.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 = Because legitimate shim files are created and used all the time, this event, in itself, is not suspicious. However, if there are other correlating events, it may warrant further investigation. -action.escu.creation_date = 2018-11-02 -action.escu.modification_date = 2018-11-02 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Shim Database File Creation - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Windows Persistence Techniques"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Shim Database File Creation - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 values(Filesystem.action) values(Filesystem.file_hash) as file_hash values(Filesystem.file_path) as file_path min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Filesystem where Filesystem.file_path=*Windows\AppPatch\Custom* by Filesystem.file_name Filesystem.dest | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` |`drop_dm_object_name(Filesystem)` | `shim_database_file_creation_filter` - -[ESCU - Shim Database Installation With Suspicious Parameters - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1138"], "nist": ["DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = 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.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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -action.escu.known_false_positives = None identified -action.escu.creation_date = 2019-03-01 -action.escu.modification_date = 2019-03-01 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Shim Database Installation With Suspicious Parameters - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Windows Persistence Techniques"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Shim Database Installation With Suspicious Parameters - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = | tstats `security_content_summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = sdbinst.exe Processes.process="*-p*" Processes.process="*-q*" by Processes.process_name Processes.parent_process_name Processes.dest Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `shim_database_installation_with_suspicious_parameters_filter` - -[ESCU - Short Lived Windows Accounts - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search detects accounts that were created and deleted in a short time period. -action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1136"], "nist": ["PR.IP"]} -action.escu.data_models = ["Change"] -action.escu.eli5 = This search detects accounts that were created and deleted in a short time period. -action.escu.how_to_implement = This search requires you to have enabled your Group Management Audit Logs in your Local Windows Security Policy and be ingesting those logs. More information on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/ -action.escu.known_false_positives = It is possible that an administrator created and deleted an account in a short time period. Verifying activity with an administrator is advised. -action.escu.creation_date = 2018-01-05 -action.escu.modification_date = 2018-01-05 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Short Lived Windows Accounts - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Account Monitoring and Controls"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Short Lived Windows Accounts - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = | tstats `security_content_summariesonly` values(All_Changes.result_id) as result_id count min(_time) as firstTime max(_time) as lastTime from datamodel=Change where All_Changes.result_id=4720 OR All_Changes.result_id=4726 by _time span=4h All_Changes.user All_Changes.dest | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `drop_dm_object_name("All_Changes")` | search result_id = 4720 result_id=4726 | transaction user connected=false maxspan=240m | table firstTime lastTime count user dest result_id | `short_lived_windows_accounts_filter` - -[ESCU - Single Letter Process On Endpoint - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for process names that consist only of a single letter. -action.escu.mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["ID.AM", "PR.DS"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for process names that consist only of a single letter. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -action.escu.known_false_positives = Single-letter executables are not always malicious. Investigate this activity with your normal incident-response process. -action.escu.creation_date = 2019-04-01 -action.escu.modification_date = 2019-04-01 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Single Letter Process On Endpoint - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["DHS Report TA18-074A"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Single Letter Process On Endpoint - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 by Processes.dest, Processes.user, Processes.process, Processes.process_name | `drop_dm_object_name(Processes)` | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | eval process_name_length = len(process_name), endExe = if(substr(process_name, -4) == ".exe", 1, 0) | search process_name_length=5 AND endExe=1 | table count, firstTime, lastTime, dest, user, process, process_name | `single_letter_process_on_endpoint_filter` - -[ESCU - Spectre and Meltdown Vulnerable Systems - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = The search is used to detect systems that are still vulnerable to the Spectre and Meltdown vulnerabilities. -action.escu.mappings = {"cis20": ["CIS 4"], "nist": ["ID.RA", "RS.MI", "PR.IP", "DE.CM"]} -action.escu.data_models = ["Vulnerabilities"] -action.escu.eli5 = The search is used to detect systems that are still vulnerable to the Spectre and Meltdown vulnerabilities. -action.escu.how_to_implement = The search requires that you are ingesting your vulnerability-scanner data and that it reports the CVE of the vulnerability identified. -action.escu.known_false_positives = It is possible that your vulnerability scanner is not detecting that the patches have been applied. -action.escu.creation_date = 2017-01-07 -action.escu.modification_date = 2017-01-07 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Spectre and Meltdown Vulnerable Systems - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Spectre And Meltdown Vulnerabilities"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Spectre and Meltdown Vulnerable Systems - Rule -schedule_window = auto -action.notable = 1 -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = | tstats `security_content_summariesonly` min(_time) as firstTime max(_time) as lastTime from datamodel=Vulnerabilities where Vulnerabilities.cve ="CVE-2017-5753" OR Vulnerabilities.cve ="CVE-2017-5715" OR Vulnerabilities.cve ="CVE-2017-5754" by Vulnerabilities.dest| `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `spectre_and_meltdown_vulnerable_systems_filter` - -[ESCU - Spike in File Writes - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = The search looks for a sharp increase in the number of files written to a particular host -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM"]} -action.escu.data_models = [] -action.escu.eli5 = The search looks for a sharp increase in the number of files written to a particular host -action.escu.how_to_implement = In order to implement this search, you must populate the Endpoint file-system data model node. This is typically populated via endpoint detection and response products, 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 file system. -action.escu.known_false_positives = It is important to understand that if you happen to install any new applications on your hosts or are copying a large number of files, you can expect to see a large increase of file modifications. -action.escu.creation_date = 2020-03-16 -action.escu.modification_date = 2020-03-16 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Spike in File Writes - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["SamSam Ransomware", "Ransomware"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Spike in File Writes - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 FROM datamodel=Endpoint.Filesystem where Filesystem.action=created by _time span=1h, Filesystem.dest | `drop_dm_object_name(Filesystem)` | eventstats max(_time) as maxtime | stats count as num_data_samples max(eval(if(_time >= relative_time(maxtime, "-1d@d"), count, null))) as "count" avg(eval(if(_time upperBound) AND num_data_samples >=20, 1, 0) | search isOutlier=1 | `spike_in_file_writes_filter` - -[ESCU - Splunk Enterprise Information Disclosure - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search allows you to look for evidence of exploitation for CVE-2018-11409, a Splunk Enterprise Information Disclosure Bug. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "RS.MI", "PR.PT", "PR.AC", "PR.IP", "DE.CM"]} -action.escu.data_models = [] -action.escu.eli5 = This search allows you to look for evidence of exploitation for CVE-2018-11409, a Splunk Enterprise Information Disclosure Bug. -action.escu.how_to_implement = The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Whitelisting your Splunk systems will reduce false positives. -action.escu.known_false_positives = Retrieving server information may be a legitimate API request. Verify that the attempt is a valid request for information. -action.escu.creation_date = 2018-06-14 -action.escu.modification_date = 2018-06-14 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Splunk Enterprise Information Disclosure - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Splunk Enterprise Vulnerability CVE-2018-11409"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Splunk Enterprise Information Disclosure - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = index=_internal sourcetype=splunkd_ui_access server-info | search clientip!=127.0.0.1 uri_path="*raw/services/server/info/server-info" | rename clientip as src_ip, splunk_server as dest | stats earliest(_time) as firstTime, latest(_time) as lastTime, values(uri) as uri, values(useragent) as http_user_agent, values(user) as user by src_ip, dest | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `splunk_enterprise_information_disclosure_filter` - -[ESCU - Suspicious Changes to File Associations - Rule] -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": ["T1042"], "nist": ["DE.CM", "PR.PT", "PR.IP"]} -action.escu.data_models = [] -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. -action.escu.creation_date = 2020-03-16 -action.escu.modification_date = 2020-03-16 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Suspicious Changes to File Associations - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows File Extension and Association Abuse"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Suspicious Changes to File Associations - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 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 Email - UBA Anomaly - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"]} -action.escu.data_models = ["UEBA"] -action.escu.eli5 = 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.escu.how_to_implement = You must be ingesting data from email logs and have Splunk integrated with UBA. This anomaly is raised by a UBA detection model called "SuspiciousEmailDetectionModel." Ensure that this model is enabled on your UBA instance. -action.escu.known_false_positives = This detection model will alert on any sender domain that is seen for the first time. This could be a potential false positive. The next step is to investigate and whitelist the URL if you determine that it is a legitimate sender. -action.escu.creation_date = 2019-07-21 -action.escu.modification_date = 2019-07-21 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Suspicious Email - UBA Anomaly - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Emails"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Suspicious Email - UBA Anomaly - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 values(All_UEBA_Events.category) as category from datamodel=UEBA where nodename=All_UEBA_Events.UEBA_Anomalies All_UEBA_Events.UEBA_Anomalies.uba_model = "SuspiciousEmailDetectionModel" by All_UEBA_Events.description All_UEBA_Events.severity All_UEBA_Events.user All_UEBA_Events.uba_event_type All_UEBA_Events.link All_UEBA_Events.signature All_UEBA_Events.url All_UEBA_Events.UEBA_Anomalies.uba_model | `drop_dm_object_name(All_UEBA_Events)` | `drop_dm_object_name(UEBA_Anomalies)`| `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `suspicious_email___uba_anomaly_filter` - -[ESCU - Suspicious Email Attachment Extensions - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for emails that have attachments with suspicious file extensions. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 12"], "kill_chain_phases": ["Delivery"], "nist": ["DE.AE", "PR.IP"]} -action.escu.data_models = ["Email"] -action.escu.eli5 = This search looks for emails that have attachments with suspicious file extensions. -action.escu.how_to_implement = You need to ingest data from emails. Specifically, the sender's address and the file names of any attachments must be mapped to the Email data model. \ - **Splunk Phantom Playbook Integration**\ -If Splunk Phantom is also configured in your environment, a Playbook called "Suspicious Email Attachment Investigate and Delete" can be configured to run when any results are found by this detection search. To use this integration, install the Phantom App for Splunk `https://splunkbase.splunk.com/app/3411/`, and add the correct hostname to the "Phantom Instance" field in the Adaptive Response Actions when configuring this detection search. The notable event will be sent to Phantom and the playbook will gather further information about the file attachment and its network behaviors. If Phantom finds malicious behavior and an analyst approves of the results, the email will be deleted from the user's inbox. -action.escu.known_false_positives = None identified -action.escu.creation_date = 2020-01-27 -action.escu.modification_date = 2020-01-27 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Suspicious Email Attachment Extensions - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Emails", "Emotet Malware DHS Report TA18-201A "] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Suspicious Email Attachment Extensions - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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=Email where All_Email.file_name="*" by All_Email.src_user, All_Email.file_name All_Email.message_id | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name("All_Email")` | `suspicious_email_attachments` | `suspicious_email_attachment_extensions_filter` - -[ESCU - Suspicious File Write - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = The search looks for files created with names that have been linked to malicious activity. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [] -action.escu.eli5 = The search looks for files created with names that have been linked to malicious activity. -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. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file system reads and writes. In addition, this search leverages an included lookup file that contains the names of the files to watch for, as well as a note to communicate why that file name is being monitored. This lookup file can be edited to add or remove file the file names you want to monitor. -action.escu.known_false_positives = It's possible for a legitimate file to be created with the same name as one noted in the lookup file. Filenames listed in the lookup file should be unique enough that collisions are rare. Looking at the location of the file and the process responsible for the activity can help determine whether or not the activity is legitimate. -action.escu.creation_date = 2019-04-25 -action.escu.modification_date = 2019-04-25 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Suspicious File Write - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Hidden Cobra Malware"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Suspicious File Write - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 values(Filesystem.action) as action values(Filesystem.file_path) as file_path min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Filesystem by Filesystem.file_name Filesystem.dest | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `drop_dm_object_name(Filesystem)` | `suspicious_writes` | `suspicious_file_write_filter` - -[ESCU - Suspicious Java Classes - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 7", "CIS 12"], "kill_chain_phases": ["Exploitation"], "nist": ["DE.AE"]} -action.escu.data_models = [] -action.escu.eli5 = 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.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest data from your web-traffic appliances that serve or sit in the path of your Struts application servers. This can be accomplished by indexing data from a web proxy, or by using network traffic-analysis tools, such as Splunk Stream or Bro. -action.escu.known_false_positives = There are no known false positives. -action.escu.creation_date = 2018-12-06 -action.escu.modification_date = 2018-12-06 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Suspicious Java Classes - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Apache Struts Vulnerability"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Suspicious Java Classes - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `stream_http` http_method=POST http_content_length>1 | regex form_data="(?i)java\.lang\.(?:runtime|processbuilder)" | rename src_ip as src | stats count earliest(_time) as firstTime, latest(_time) as lastTime, values(url) as uri, values(status) as status, values(http_user_agent) as http_user_agent by src, dest | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `suspicious_java_classes_filter` - -[ESCU - Suspicious LNK file launching a process - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for a ``*.lnk` file under `C:\User*` or `*\Local\Temp\*` executing a process. This is common behavior used by various spear phishing tools. -action.escu.mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1193"], "nist": ["ID.AM", "PR.DS"]} -action.escu.data_models = [] -action.escu.eli5 = This search looks for a ``*.lnk` file under `C:\User*` or `*\Local\Temp\*` executing a process. This is common behavior used by various spear phishing tools. -action.escu.how_to_implement = You must be ingesting data that records filesystem and process activity from your hosts to populate the Endpoint data model. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. -action.escu.known_false_positives = This detection should yield little or no false positive results. It is uncommon for LNK files to execute process from temporary or user directories. -action.escu.creation_date = 2020-03-16 -action.escu.modification_date = 2020-03-16 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Suspicious LNK file launching a process - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Phishing Payloads"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Suspicious LNK file launching a process - Rule -schedule_window = auto -action.notable = 1 -action.notable.param.nes_fields = ['user', 'dest'] -action.notable.param.rule_description = This search looks for a ``*.lnk` file under `C:\User*` or `*\Local\Temp\*` executing a process. This is common behavior used by various spear phishing tools. -action.notable.param.rule_title = Suspicious LNK file launching a process -action.notable.param.security_domain = network -action.notable.param.severity = high -alert.digest_mode = 1 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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.Filesystem where Filesystem.file_name="*.lnk" AND (Filesystem.file_path="C:\\Users*" OR Filesystem.file_path="*Local\\Temp*") by _time span=1h Filesystem.process_id Filesystem.file_name Filesystem.file_path Filesystem.file_hash Filesystem.user | `drop_dm_object_name(Filesystem)` | rename process_id as lnk_pid | join lnk_pid, _time [| tstats `security_content_summariesonly` count FROM datamodel=Endpoint.Processes where Processes.process_name=* by _time span=1h Processes.parent_process_id Processes.process_id Processes.process_name Processes.dest Processes.process_path Processes.process | `drop_dm_object_name(Processes)` | rename parent_process_id as lnk_pid | fields _time lnk_pid process_id dest process_name process_path process] | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | table firstTime, lastTime, lnk_pid, process_id, user, dest, file_name, file_path, process_name, process, process_path, file_hash | `suspicious_lnk_file_launching_a_process_filter` - -[ESCU - Suspicious Reg exe Process - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1112", "T1089"], "nist": ["DE.CM"]} -action.escu.data_models = [] -action.escu.eli5 = 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.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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -action.escu.known_false_positives = It's possible for system administrators to write scripts that exhibit this behavior. If this is the case, the search will need to be modified to filter them out. -action.escu.creation_date = 2020-03-16 -action.escu.modification_date = 2020-03-16 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Suspicious Reg exe Process - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Disabling Security Tools", "Windows Defense Evasion Tactics", "DHS Report TA18-074A"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Suspicious Reg exe Process - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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.parent_process_name != explorer.exe Processes.process_name =cmd.exe by Processes.user Processes.process_name Processes.parent_process_name Processes.dest Processes.process_id Processes.parent_process_id | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | search [| tstats `security_content_summariesonly` count FROM datamodel=Endpoint.Processes where Processes.parent_process_name=cmd.exe Processes.process_name= reg.exe by Processes.parent_process_id Processes.dest Processes.process_name | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | rename parent_process_id as process_id |dedup process_id| table process_id dest] | `suspicious_reg_exe_process_filter` - -[ESCU - Suspicious wevtutil Usage - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.DP", "PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.AE"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = 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.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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -action.escu.known_false_positives = The wevtutil.exe application is a legitimate Windows event log utility. Administrators may use it to manage Windows event logs. -action.escu.creation_date = 2019-02-28 -action.escu.modification_date = 2019-02-28 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Suspicious wevtutil Usage - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Windows Log Manipulation", "Ransomware"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Suspicious wevtutil Usage - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = | tstats `security_content_summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = wevtutil.exe Processes.process="*cl*" (Processes.process="*System*" OR Processes.process="*Security*" OR Processes.process="*Setup*" OR Processes.process="*Application*") by Processes.process_name Processes.parent_process_name Processes.dest Processes.user| `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` |`security_content_ctime(lastTime)` | `suspicious_wevtutil_usage_filter` - -[ESCU - Suspicious writes to System Volume Information - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search detects writes to the 'System Volume Information' folder by something other than the System process. -action.escu.mappings = {"cis20": ["CIS 8"], "mitre_attack": ["T1074"], "nist": ["DE.CM"]} -action.escu.data_models = [] -action.escu.eli5 = This search detects writes to the 'System Volume Information' folder by something other than the System process. -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. -action.escu.known_false_positives = It is possible that other utilities or system processes may legitimately write to this folder. Investigate and modify the search to include exceptions as appropriate. -action.escu.creation_date = 2018-01-08 -action.escu.modification_date = 2018-01-08 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Suspicious writes to System Volume Information - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Collection and Staging"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Suspicious writes to System Volume Information - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = (`sysmon` OR tag=process) EventCode=11 process_id!=4 file_path=*System\ Volume\ Information* | stats count min(_time) as firstTime max(_time) as lastTime by dest, Image, file_path | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `suspicious_writes_to_system_volume_information_filter` - -[ESCU - Suspicious writes to windows Recycle Bin - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search detects writes to the recycle bin by a process other than explorer.exe. -action.escu.mappings = {"cis20": ["CIS 8"], "mitre_attack": ["T1074"], "nist": ["DE.CM"]} -action.escu.data_models = [] -action.escu.eli5 = This search detects writes to the recycle bin by a process other than explorer.exe. -action.escu.how_to_implement = To successfully implement this search you need to be ingesting information on filesystem and process logs responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` and `Filesystem` nodes. -action.escu.known_false_positives = Because the Recycle Bin is a hidden folder in modern versions of Windows, it would be unusual for a process other than explorer.exe to write to it. Incidents should be investigated as appropriate. -action.escu.creation_date = 2020-02-03 -action.escu.modification_date = 2020-02-03 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Suspicious writes to windows Recycle Bin - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Collection and Staging"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Suspicious writes to windows Recycle Bin - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 values(Filesystem.file_path) as file_path values(Filesystem.file_name) as file_name FROM datamodel=Endpoint.Filesystem where Filesystem.file_path = "*$Recycle.Bin*" by Filesystem.process_id Filesystem.dest | `drop_dm_object_name("Filesystem")`| search [| tstats `security_content_summariesonly` values(Processes.user) as user 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" by Processes.process_id Processes.dest| `drop_dm_object_name("Processes")` | table process_id dest] | `suspicious_writes_to_windows_recycle_bin_filter` - -[ESCU - System Processes Run From Unexpected Locations - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1036"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [] -action.escu.eli5 = 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.escu.how_to_implement = To successfully implement this search you need to ingest details about process execution from your hosts. Specifically, this search requires the process name and the full path to the process executable. -action.escu.known_false_positives = None identified -action.escu.creation_date = 2020-02-04 -action.escu.modification_date = 2020-02-04 -action.escu.confidence = high -action.escu.full_search_name = ESCU - System Processes Run From Unexpected Locations - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Command-Line Executions", "Ransomware", "Unusual Processes"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - System Processes Run From Unexpected Locations - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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_path !="C:\\Windows\\System32*" Processes.process_path !="C:\\Windows\\SysWOW64*" by Processes.user Processes.dest Processes.process_name Processes.process_id Processes.process_path Processes.parent_process_name Processes.process_hash| `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| `is_windows_system_file` | `system_processes_run_from_unexpected_locations_filter` - -[ESCU - TOR Traffic - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE"]} -action.escu.data_models = ["Network_Traffic"] -action.escu.eli5 = 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.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest data from firewalls or other network control devices that mediate the traffic allowed into an environment. This is necessary so that the search can identify an 'action' taken on the traffic of interest. The search requires the Network_Traffic data model be populated. -action.escu.known_false_positives = None at this time -action.escu.creation_date = 2017-09-11 -action.escu.modification_date = 2017-09-11 -action.escu.confidence = high -action.escu.full_search_name = ESCU - TOR Traffic - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Command and Control", "Ransomware", "Prohibited Traffic Allowed or Protocol Mismatch"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - TOR Traffic - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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=Network_Traffic where All_Traffic.app=tor AND All_Traffic.action=allowed by All_Traffic.src_ip All_Traffic.dest_ip All_Traffic.dest_port All_Traffic.action | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name("All_Traffic")` | `tor_traffic_filter` - -[ESCU - USN Journal Deletion - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"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"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = 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.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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -action.escu.known_false_positives = None identified -action.escu.creation_date = 2018-12-03 -action.escu.modification_date = 2018-12-03 -action.escu.confidence = high -action.escu.full_search_name = ESCU - USN Journal Deletion - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Windows Log Manipulation", "Ransomware"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - USN Journal Deletion - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 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=fsutil.exe by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | search process="*deletejournal*" AND process="*usn*" | `usn_journal_deletion_filter` - -[ESCU - Uncommon Processes On Endpoint - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for applications on the endpoint that you have marked as uncommon. -action.escu.mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015"], "nist": ["ID.AM", "PR.DS"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for applications on the endpoint that you have marked as uncommon. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. This search uses a lookup file `uncommon_processes_default.csv` to track various features of process names that are usually uncommon in most environments. Please consider updating `uncommon_processes_local.csv` to hunt for processes that are uncommon in your environment. -action.escu.known_false_positives = None identified -action.escu.creation_date = 2020-03-16 -action.escu.modification_date = 2020-03-16 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Uncommon Processes On Endpoint - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Windows Privilege Escalation", "Unusual Processes"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Uncommon Processes On Endpoint - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 by Processes.dest Processes.user Processes.process Processes.process_name | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `drop_dm_object_name(Processes)` | `uncommon_processes` |`uncommon_processes_on_endpoint_filter` - -[ESCU - Unload Sysmon Filter Driver - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1089"], "nist": ["DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = 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.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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. This search is also shipped with `unload_sysmon_filter_driver_filter` macro, update this macro to filter out false positives. -action.escu.known_false_positives = -action.escu.creation_date = 2020-01-13 -action.escu.modification_date = 2020-01-13 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Unload Sysmon Filter Driver - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Disabling Security Tools"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Unload Sysmon Filter Driver - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 values(Processes.process) as process max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=fltMC.exe AND Processes.process=*unload* AND Processes.process=*SysmonDrv* by Processes.process_name Processes.process_id Processes.parent_process_name Processes.process Processes.dest Processes.user | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` |`unload_sysmon_filter_driver_filter`| table firstTime lastTime dest user count process_name process_id parent_process_name process - -[ESCU - Unsigned Image Loaded by LSASS - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search detects loading of unsigned images by LSASS. -action.escu.mappings = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} -action.escu.data_models = [] -action.escu.eli5 = This search detects loading of unsigned images by LSASS. -action.escu.how_to_implement = This search needs Sysmon Logs with a sysmon configuration, which includes EventCode 7 with lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon 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. -action.escu.known_false_positives = Other tools could load images into LSASS for legitimate reason. But enterprise tools should always use signed DLLs. -action.escu.creation_date = 2019-12-06 -action.escu.modification_date = 2019-12-06 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Unsigned Image Loaded by LSASS - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Credential Dumping"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Unsigned Image Loaded by LSASS - Rule -schedule_window = auto -action.notable = 1 -action.notable.param.nes_fields = ['dest'] -action.notable.param.rule_description = This search detects loading of unsigned images by LSASS. -action.notable.param.rule_title = Unsigned Image Loaded by LSASS -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -alert.digest_mode = 1 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `sysmon` EventID=7 Image=*lsass.exe Signed=false | stats count min(_time) as firstTime max(_time) as lastTime by Computer, Image, ImageLoaded, Signed, SHA1 | rename Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `unsigned_image_loaded_by_lsass_filter` - -[ESCU - Unsuccessful Netbackup backups - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search gives you the hosts where a backup was attempted and then failed. -action.escu.mappings = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} -action.escu.data_models = [] -action.escu.eli5 = This search gives you the hosts where a backup was attempted and then failed. -action.escu.how_to_implement = To successfully implement this search you need to obtain data from your backup solution, either from the backup logs on your endpoints or from a central server responsible for performing the backups. If you do not use Netbackup, you can modify this search for your specific backup solution. -action.escu.known_false_positives = None identified -action.escu.creation_date = 2017-09-12 -action.escu.modification_date = 2017-09-12 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Unsuccessful Netbackup backups - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Monitor Backup Solution"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Unsuccessful Netbackup backups - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `netbackup` | stats latest(_time) as latestTime by COMPUTERNAME, MESSAGE | search MESSAGE="An error occurred, failed to backup." | `security_content_ctime(latestTime)` | rename COMPUTERNAME as dest, MESSAGE as signature | table latestTime, dest, signature | `unsuccessful_netbackup_backups_filter` - -[ESCU - Unusually Long Command Line - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = Command lines that are extremely long may be indicative of malicious activity on your hosts. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [] -action.escu.eli5 = Command lines that are extremely long may be indicative of malicious activity on your hosts. -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. The command-line arguments are mapped to the "process" field in the Endpoint data model. -action.escu.known_false_positives = Some legitimate applications start with long command lines. -action.escu.creation_date = 2020-03-16 -action.escu.modification_date = 2020-03-16 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Unusually Long Command Line - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Ransomware", "Suspicious Command-Line Executions", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Unusual Processes"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Unusually Long Command Line - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 by Processes.user Processes.dest Processes.process_name Processes.process | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| eval processlen=len(process) | eventstats stdev(processlen) as stdev, avg(processlen) as avg by dest | stats max(processlen) as maxlen, values(stdev) as stdevperhost, values(avg) as avgperhost by dest, user, process_name, process| `unusually_long_command_line_filter` eval threshold = 10 | where maxlen > ((threshold*stdevperhost) + avgperhost) - -[ESCU - Unusually Long Command Line - MLTK - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [] -action.escu.eli5 = 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.escu.how_to_implement = You must be ingesting endpoint data that monitors command lines and populates the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. In addition, MLTK version >= 4.2 must be installed on your search heads, along with any required dependencies. Finally, the support search "Baseline of Command Line Length - MLTK" must be executed before this detection search, as it builds an ML model over the historical data used by this search. It is important that this search is run in the same app context as the associated support search, so that the model created by the support search is available for use. You should periodically re-run the support search to rebuild the model with the latest data available in your environment. -action.escu.known_false_positives = Some legitimate applications use long command lines for installs or updates. You should review identified command lines for legitimacy. You may modify the first part of the search to omit legitimate command lines from consideration. If you are seeing more results than desired, you may consider changing the value of threshold in the search to a smaller value. You should also periodically re-run the support search to re-build the ML model on the latest data. You may get unexpected results if the user identified in the results is not present in the data used to build the associated model. -action.escu.creation_date = 2019-05-08 -action.escu.modification_date = 2019-05-08 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Unusually Long Command Line - MLTK - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Ransomware", "Suspicious Command-Line Executions", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Unusual Processes"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Unusually Long Command Line - MLTK - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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 by Processes.user Processes.dest Processes.process_name Processes.process | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| eval processlen=len(process) | search user!=unknown | apply cmdline_pdfmodel threshold=0.01 | rename "IsOutlier(processlen)" as isOutlier | search isOutlier > 0 | table firstTime lastTime user dest process_name process processlen count | `unusually_long_command_line___mltk_filter` - -[ESCU - Unusually Long Content-Type Length - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for unusually long strings in the Content-Type http header that the client sends the server. -action.escu.mappings = {"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"]} -action.escu.data_models = [] -action.escu.eli5 = This search looks for unusually long strings in the Content-Type http header that the client sends the server. -action.escu.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. -action.escu.known_false_positives = Very few legitimate Content-Type fields will have a length greater than 100 characters. -action.escu.creation_date = 2017-10-13 -action.escu.modification_date = 2017-10-13 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Unusually Long Content-Type Length - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Apache Struts Vulnerability"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Unusually Long Content-Type Length - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `stream_http` | eval cs_content_type_length = len(cs_content_type) | where cs_content_type_length > 100 | table endtime src_ip dest_ip cs_content_type_length cs_content_type url | `unusually_long_content_type_length_filter` - -[ESCU - WMI Permanent Event Subscription - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for the creation of WMI permanent event subscriptions. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1084"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} -action.escu.data_models = [] -action.escu.eli5 = This search looks for the creation of WMI permanent event subscriptions. -action.escu.how_to_implement = To successfully implement this search, you must be ingesting the Windows WMI activity logs. This can be done by adding a stanza to inputs.conf on the system generating logs with a title of [WinEventLog://Microsoft-Windows-WMI-Activity/Operational]. -action.escu.known_false_positives = Although unlikely, administrators may use event subscriptions for legitimate purposes. -action.escu.creation_date = 2018-10-23 -action.escu.modification_date = 2018-10-23 -action.escu.confidence = high -action.escu.full_search_name = ESCU - WMI Permanent Event Subscription - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious WMI Use"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - WMI Permanent Event Subscription - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `wmi` EventCode=5861 Binding | rex field=Message "Consumer =\s+(?[^;|^$]+)" | search consumer!="NTEventLogEventConsumer=\"SCM Event Log Consumer\"" | stats count min(_time) as firstTime max(_time) as lastTime by ComputerName, consumer, Message | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | rename ComputerName as dest | `wmi_permanent_event_subscription_filter` - -[ESCU - WMI Permanent Event Subscription - Sysmon - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for the creation of WMI permanent event subscriptions. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1084"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} -action.escu.data_models = [] -action.escu.eli5 = This search looks for the creation of WMI permanent event subscriptions. -action.escu.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 alerts for WMI activity. In addition, you must have at least version 6.0.4 of the Sysmon TA installed to properly parse the fields. -action.escu.known_false_positives = Although unlikely, administrators may use event subscriptions for legitimate purposes. -action.escu.creation_date = 2018-10-23 -action.escu.modification_date = 2018-10-23 -action.escu.confidence = high -action.escu.full_search_name = ESCU - WMI Permanent Event Subscription - Sysmon - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious WMI Use"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - WMI Permanent Event Subscription - Sysmon - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `sysmon` EventCode=21 | rename host as dest | table _time, dest, user, Operation, EventType, Query, Consumer, Filter | `wmi_permanent_event_subscription___sysmon_filter` - -[ESCU - WMI Temporary Event Subscription - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for the creation of WMI temporary event subscriptions. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1084"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} -action.escu.data_models = [] -action.escu.eli5 = This search looks for the creation of WMI temporary event subscriptions. -action.escu.how_to_implement = To successfully implement this search, you must be ingesting the Windows WMI activity logs. This can be done by adding a stanza to inputs.conf on the system generating logs with a title of [WinEventLog://Microsoft-Windows-WMI-Activity/Operational]. -action.escu.known_false_positives = Some software may create WMI temporary event subscriptions for various purposes. The included search contains an exception for two of these that occur by default on Windows 10 systems. You may need to modify the search to create exceptions for other legitimate events. -action.escu.creation_date = 2018-10-23 -action.escu.modification_date = 2018-10-23 -action.escu.confidence = high -action.escu.full_search_name = ESCU - WMI Temporary Event Subscription - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious WMI Use"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - WMI Temporary Event Subscription - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `wmi` EventCode=5860 Temporary | rex field=Message "NotificationQuery =\s+(?[^;|^$]+)" | search query!="SELECT * FROM Win32_ProcessStartTrace WHERE ProcessName = 'wsmprovhost.exe'" AND query!="SELECT * FROM __InstanceOperationEvent WHERE TargetInstance ISA 'AntiVirusProduct' OR TargetInstance ISA 'FirewallProduct' OR TargetInstance ISA 'AntiSpywareProduct'" | stats count min(_time) as firstTime max(_time) as lastTime by ComputerName, query | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `wmi_temporary_event_subscription_filter` - -[ESCU - Web Fraud - Account Harvesting - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search is used to identify the creation of multiple user accounts using the same email domain name. -action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1136"], "nist": ["DE.CM", "DE.DP"]} -action.escu.data_models = [] -action.escu.eli5 = This search is used to identify the creation of multiple user accounts using the same email domain name. -action.escu.how_to_implement = We start with a dataset that provides visibility into the email address used for the account creation. In this example, we are narrowing our search down to the single web page that hosts the Magento2 e-commerce platform (via URI) used for account creation, the single http content-type to grab only the user's clicks, and the http field that provides the username (form_data), for performance reasons. After we have the username and email domain, we look for numerous account creations per email domain. Common data sources used for this detection are customized Apache logs or Splunk Stream. -action.escu.known_false_positives = As is common with many fraud-related searches, we are usually looking to attribute risk or synthesize relevant context with loosely written detections that simply detect anamolous behavior. This search will need to be customized to fit your environment—improving its fidelity by counting based on something much more specific, such as a device ID that may be present in your dataset. Consideration for whether the large number of registrations are occuring from a first-time seen domain may also be important. Extending the search window to look further back in time, or even calculating the average per hour/day for each email domain to look for an anomalous spikes, will improve this search. You can also use Shannon entropy or Levenshtein Distance (both courtesy of URL Toolbox) to consider the randomness or similarity of the email name or email domain, as the names are often machine-generated. -action.escu.creation_date = 2018-10-08 -action.escu.modification_date = 2018-10-08 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Web Fraud - Account Harvesting - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Web Fraud Detection"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Web Fraud - Account Harvesting - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `stream_http` http_content_type=text* uri="/magento2/customer/account/loginPost/" | rex field=cookie "form_key=(?\w+)" | rex field=form_data "login\[username\]=(?[^&|^$]+)" | search Username=* | rex field=Username "@(?.*)"|stats dc(Username) as UniqueUsernames list(Username) as src_user by email_domain|where UniqueUsernames> 25 | `web_fraud___account_harvesting_filter` - -[ESCU - Web Fraud - Anomalous User Clickspeed - Rule] -action.escu = 0 -action.escu.enabled = 1 -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.escu.mappings = {"cis20": ["CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078"], "nist": ["DE.AE", "DE.CM"]} -action.escu.data_models = [] -action.escu.eli5 = 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.escu.how_to_implement = Start with a dataset that allows you to see clickstream data for each user click on the website. That data must have a time stamp and must contain a reference to the session identifier being used by the website. This ties the clicks together into clickstreams. This value is usually found in the http cookie. With a bit of tuning, a version of this search could be used in high-volume scenarios, such as scraping, crawling, application DDOS, credit-card testing, account takeover, etc. Common data sources used for this detection are customized Apache logs, customized IIS, and Splunk Stream. -action.escu.known_false_positives = As is common with many fraud-related searches, we are usually looking to attribute risk or synthesize relevant context with loosly written detections that simply detect anamoluous behavior. -action.escu.creation_date = 2018-10-08 -action.escu.modification_date = 2018-10-08 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Web Fraud - Anomalous User Clickspeed - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Web Fraud Detection"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Web Fraud - Anomalous User Clickspeed - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `stream_http` http_content_type=text* | rex field=cookie "form_key=(?\w+)" | streamstats window=2 current=1 range(_time) as TimeDelta by session_id | where TimeDelta>0 |stats count stdev(TimeDelta) as ClickSpeedStdDev avg(TimeDelta) as ClickSpeedAvg by session_id | where count>5 AND (ClickSpeedStdDev<.5 OR ClickSpeedAvg<.5) | `web_fraud___anomalous_user_clickspeed_filter` - -[ESCU - Web Fraud - Password Sharing Across Accounts - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search is used to identify user accounts that share a common password. -action.escu.mappings = {"cis20": ["CIS 16"], "nist": ["DE.DP"]} -action.escu.data_models = [] -action.escu.eli5 = This search is used to identify user accounts that share a common password. -action.escu.how_to_implement = We need to start with a dataset that allows us to see the values of usernames and passwords that users are submitting to the website hosting the Magento2 e-commerce platform (commonly found in the HTTP form_data field). A tokenized or hashed value of a password is acceptable and certainly preferable to a clear-text password. Common data sources used for this detection are customized Apache logs, customized IIS, and Splunk Stream. -action.escu.known_false_positives = As is common with many fraud-related searches, we are usually looking to attribute risk or synthesize relevant context with loosely written detections that simply detect anamoluous behavior. -action.escu.creation_date = 2018-10-08 -action.escu.modification_date = 2018-10-08 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Web Fraud - Password Sharing Across Accounts - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Web Fraud Detection"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Web Fraud - Password Sharing Across Accounts - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = `stream_http` http_content_type=text* uri=/magento2/customer/account/loginPost* | rex field=form_data "login\[username\]=(?[^&|^$]+)" | rex field=form_data "login\[password\]=(?[^&|^$]+)" | stats dc(Username) as UniqueUsernames values(Username) as user list(src_ip) as src_ip by Password|where UniqueUsernames>5 | `web_fraud___password_sharing_across_accounts_filter` - -[ESCU - Web Servers Executing Suspicious Processes - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for suspicious processes on all systems labeled as web servers. -action.escu.mappings = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1082"], "nist": ["PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for suspicious processes on all systems labeled as web servers. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. In addition, web servers will need to be identified in the Assets and Identity Framework of Enterprise Security. -action.escu.known_false_positives = Some of these processes may be used legitimately on web servers during maintenance or other administrative tasks. -action.escu.creation_date = 2019-04-01 -action.escu.modification_date = 2019-04-01 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Web Servers Executing Suspicious Processes - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Apache Struts Vulnerability"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Web Servers Executing Suspicious Processes - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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.dest_category="web_server" AND (Processes.process="*whoami*" OR Processes.process="*ping*" OR Processes.process="*iptables*" OR Processes.process="*wget*" OR Processes.process="*service*" OR Processes.process="*curl*") by Processes.process Processes.process_name, Processes.dest Processes.user| `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `web_servers_executing_suspicious_processes_filter` - -[ESCU - Windows Event Log Cleared - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for Windows events that indicate one of the Windows event logs has been purged. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.DP", "PR.IP", "PR.AC", "PR.AT", "DE.AE"]} -action.escu.data_models = [] -action.escu.eli5 = This search looks for Windows events that indicate one of the Windows event logs has been purged. -action.escu.how_to_implement = To successfully implement this search, you need to be ingesting Windows event logs from your hosts. -action.escu.known_false_positives = It is possible that these logs may be legitimately cleared by Administrators. -action.escu.creation_date = 2019-02-27 -action.escu.modification_date = 2019-02-27 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Windows Event Log Cleared - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Windows Log Manipulation", "Ransomware"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Windows Event Log Cleared - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = ((`wineventlog_security` AND (signature_id=1102 OR signature_id=1100)) OR ((`wineventlog_system` AND signature_id=104) | stats count min(_time) as firstTime max(_time) as lastTime by signature_id dest user| `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `windows_event_log_cleared_filter` - -[ESCU - Windows hosts file modification - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = The search looks for modifications to the hosts file on all Windows endpoints across your environment. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "nist": ["PR.IP", "PR.PT", "PR.AC", "DE.AE", "DE.CM"]} -action.escu.data_models = [] -action.escu.eli5 = The search looks for modifications to the hosts file on all Windows endpoints across your environment. -action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records the file-system activity from your hosts to populate the Endpoint.Filesystem data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or by other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file-system reads and writes. -action.escu.known_false_positives = There may be legitimate reasons for system administrators to add entries to this file. -action.escu.creation_date = 2018-11-02 -action.escu.modification_date = 2018-11-02 -action.escu.confidence = high -action.escu.full_search_name = ESCU - Windows hosts file modification - Rule -action.escu.search_type = detection -action.escu.providing_technologies = [] -action.escu.analytic_story = ["Host Redirection"] -cron_schedule = */30 * * * * -dispatch.earliest_time = -30m -dispatch.latest_time = now -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - Windows hosts file modification - Rule -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 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -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.Filesystem by Filesystem.file_name Filesystem.file_path Filesystem.dest | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | search Filesystem.file_name=hosts AND Filesystem.file_path=*Windows\\System32\\* | `drop_dm_object_name(Filesystem)` | `windows_hosts_file_modification_filter` - -### END ESCU DETECTIONS ### - - -### ESCU BASELINES ### - -[ESCU - Add Prohibited Processes to Enterprise Security - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Add Prohibited Processes to Enterprise Security -description = This search takes the existing interesting process table from ES, filters out any existing additions added by ESCU and then updates the table with processes identified by ESCU that should be prohibited on your endpoints. -action.escu.creation_date = 2017-09-15 -action.escu.modification_date = 2017-09-15 -action.escu.analytic_story = ["Emotet Malware DHS Report TA18-201A ", "Monitor for Unauthorized Software", "SamSam Ransomware"] -action.escu.data_models = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search takes the existing interesting process table from ES, filters out any existing additions added by ESCU and then updates the table with processes identified by ESCU that should be prohibited on your endpoints. -action.escu.how_to_implement = This search should be run on each new install of ESCU. -disabled = true -is_visible = false -search = | inputlookup interesting_processes_lookup | search note!=ESCU* | inputlookup append=T prohibitedProcesses_lookup | fillnull value=* dest dest_pci_domain | fillnull value=false is_required is_secure | fillnull value=true is_prohibited | outputlookup interesting_processes_lookup | stats count - -[ESCU - Baseline of API Calls per User ARN - Baseline] -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 = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 - Baseline] -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 = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 - Baseline] -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"] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 - Baseline] -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 = ["Cloud Cryptomining", "Suspicious AWS EC2 Activities"] -action.escu.data_models = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 - Baseline] -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 = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 - Baseline] -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 = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 - Baseline] -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 = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 - Baseline] -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"] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 - Baseline] -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 = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 - Baseline] -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 = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 - Baseline] -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"] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 - Baseline] -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 = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 - Baseline] -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 = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 - Baseline] -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 = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 - Baseline] -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"] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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.csv - -[ESCU - Identify Systems Creating Remote Desktop Traffic - Baseline] -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"] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 - Baseline] -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"] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 - Baseline] -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"] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 - Baseline] -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 = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 - Baseline] -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 = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 - Baseline] -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 = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 Provisioning Activity Sources - Baseline] -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 = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 - Baseline] -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 = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 Compute Creations By User - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen Cloud Compute Creations By User -description = This search builds a table of previously seen users that have launched a cloud compute instance. -action.escu.creation_date = 2018-03-15 -action.escu.modification_date = 2018-03-15 -action.escu.analytic_story = ["Cloud Cryptomining"] -action.escu.data_models = ["Cloud_Infrastructure"] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 Security Research cloud data model installed. -disabled = true -is_visible = false -search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime from datamodel=Cloud_Infrastructure.Compute where Compute.action=run `previously_seen_cloud_compute_creations_by_user_input_filter` by Compute.src_user | `drop_dm_object_name("Compute")` | outputlookup previously_seen_cloud_compute_creations_by_user | stats count - -[ESCU - Previously Seen Cloud Compute Images - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen Cloud Compute Images -description = This search builds a table of previously seen images used to launch cloud compute instances -action.escu.creation_date = 2018-03-12 -action.escu.modification_date = 2018-03-12 -action.escu.analytic_story = ["Cloud Cryptomining"] -action.escu.data_models = ["Cloud_Infrastructure"] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 Security Research cloud data model installed. -disabled = true -is_visible = false -search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime from datamodel=Cloud_Infrastructure.Compute where Compute.action=run `previously_seen_cloud_compute_image_input_filter` by Compute.image_id | `drop_dm_object_name("Compute")` | outputlookup previously_seen_cloud_compute_images | stats count - -[ESCU - Previously Seen Cloud Compute Instance Types - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen Cloud Compute Instance Types -description = This search builds a table of previously seen cloud compute instance types -action.escu.creation_date = 2019-10-03 -action.escu.modification_date = 2019-10-03 -action.escu.analytic_story = ["Cloud Cryptomining"] -action.escu.data_models = ["Cloud_Infrastructure"] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 -is_visible = false -search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime from datamodel=Cloud_Infrastructure.Compute where Compute.action=run `previously_seen_cloud_compute_instance_types_input_filter` by Compute.instance_type | `drop_dm_object_name("Compute")` | outputlookup previously_seen_cloud_compute_instance_types | stats count - -[ESCU - Previously Seen Cloud Regions - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen Cloud Regions -description = 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.creation_date = 2019-10-02 -action.escu.modification_date = 2019-10-02 -action.escu.analytic_story = ["Cloud Cryptomining"] -action.escu.data_models = ["Cloud_Infrastructure"] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 -is_visible = false -search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime from datamodel=Cloud_Infrastructure.Compute where Compute.action=start `previously_seen_cloud_regions_input_filter` by Compute.region | `drop_dm_object_name("Compute")` | outputlookup previously_seen_cloud_regions | stats count - -[ESCU - Previously Seen EC2 AMIs - Baseline] -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 = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 - Baseline] -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 = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 - Baseline] -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 = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 - Baseline] -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 = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen Running Windows Services -description = This collects the services that have been started across your entire enterprise. -action.escu.creation_date = 2020-01-13 -action.escu.modification_date = 2020-01-13 -action.escu.analytic_story = ["Orangeworm Attack Group", "Windows Service Abuse"] -action.escu.data_models = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 5.0.0 or above. -disabled = true -is_visible = false -search = `wineventlog_system` signature_id=7036 | rename param1 as service_name | rename param2 as action | search action="running" | stats earliest(_time) as firstTime, latest(_time) as lastTime by service_name | outputlookup previously_seen_running_windows_services | stats count - -[ESCU - Previously seen API call per user roles in CloudTrail - Baseline] -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 = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 - Baseline] -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 = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 - Baseline] -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"] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 - Baseline] -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. -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 = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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. -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.csv`, 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.csv | stats count - -[ESCU - Systems Ready for Spectre-Meltdown Windows Patch - Baseline] -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 = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 - Baseline] -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. -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 = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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. -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.csv`, 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.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by user src City Region Country | outputlookup previously_seen_users_console_logins.csv - -[ESCU - Windows Updates Install Failures - Baseline] -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 = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 - Baseline] -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 = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -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 ### - -[ESCU - AWS Investigate User Activities By ARN - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - AWS Investigate User Activities By ARN -description = This search lists all the logged CloudTrail activities by a specific user ARN 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 all the user's identity information. -action.escu.creation_date = 2019-04-30 -action.escu.modification_date = 2019-04-30 -action.escu.analytic_story = ["AWS Cryptomining", "AWS Network ACL Activity", "Cloud Cryptomining", "Command and Control", "Suspicious AWS EC2 Activities", "Suspicious AWS Login Activities", "Suspicious AWS S3 Activities", "Suspicious AWS Traffic", "Unusual AWS EC2 Modifications"] -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 lists all the logged CloudTrail activities by a specific user ARN 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 all the user's identity information. -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=aws:cloudtrail userIdentity.arn=$user$ | table _time userIdentity.type userIdentity.userName userIdentity.arn aws_account_id src awsRegion eventName eventType - -[ESCU - AWS Investigate User Activities By AccessKeyId - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - AWS Investigate User Activities By AccessKeyId -description = This search retrieves the times, ARN, source IPs, AWS regions, event names, and the result of the event for specific credentials. -action.escu.creation_date = 2018-06-08 -action.escu.modification_date = 2018-06-08 -action.escu.analytic_story = ["AWS Cross Account 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 retrieves the times, ARN, source IPs, AWS regions, event names, and the result of the event for specific credentials. -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=aws:cloudtrail userIdentity.accessKeyId=$accessKeyId$ | spath output=user path=userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, awsRegion, eventName, errorCode, errorMessage - -[ESCU - AWS Investigate User Activities By Source User - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - AWS Investigate User Activities By Source User -description = This search retrieves the times, ARN, source IPs, AWS regions, event names, and the result of the event for specific ARNs. -action.escu.creation_date = 2018-06-08 -action.escu.modification_date = 2018-06-08 -action.escu.analytic_story = ["AWS Cross Account 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 retrieves the times, ARN, source IPs, AWS regions, event names, and the result of the event for specific ARNs. -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=aws:cloudtrail userIdentity.arn=$src_user$ | spath output=user path=userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, awsRegion, eventName, errorCode, errorMessage - -[ESCU - AWS Network ACL Details from ID - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - AWS Network ACL Details from ID -description = This search queries AWS description logs and returns all the information about a specific network ACL via network ACL ID -action.escu.creation_date = 2017-01-22 -action.escu.modification_date = 2017-01-22 -action.escu.analytic_story = ["AWS Network ACL Activity", "Command and Control", "Suspicious AWS Traffic"] -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 AWS description logs and returns all the information about a specific network ACL via network ACL ID -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=aws:description id=$networkAclId$ | table id account_id vpc_id network_acl_entries{}.* - -[ESCU - AWS Network Interface details via resourceId - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - AWS Network Interface details via resourceId -description = This search queries AWS configuration logs and returns the information about a specific network interface via network interface ID. The information will include the ARN of the network interface, its relationships with other AWS resources, the public and the private IP associated with the network interface. -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.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search queries AWS configuration logs and returns the information about a specific network interface via network interface ID. The information will include the ARN of the network interface, its relationships with other AWS resources, the public and the private IP associated with the network interface. -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=aws:config resourceId=$resourceId$ | table _time ARN relationships{}.resourceType relationships{}.name relationships{}.resourceId configuration.privateIpAddresses{}.privateIpAddress configuration.privateIpAddresses{}.association.publicIp - -[ESCU - AWS S3 Bucket details via bucketName - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - AWS S3 Bucket details via bucketName -description = This search queries AWS configuration logs and returns the information about a specific S3 bucket. The information returned includes the time the S3 bucket was created, the resource ID, the region it belongs to, the value of action performed, AWS account ID, and configuration values of the access-control lists associated with the bucket. -action.escu.creation_date = 2018-06-26 -action.escu.modification_date = 2018-06-26 -action.escu.analytic_story = ["Suspicious AWS S3 Activities"] -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 AWS configuration logs and returns the information about a specific S3 bucket. The information returned includes the time the S3 bucket was created, the resource ID, the region it belongs to, the value of action performed, AWS account ID, and configuration values of the access-control lists associated with the bucket. -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=aws:config resourceId=$bucketName$ | table resourceCreationTime resourceId awsRegion 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 -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 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - 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 -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, verb 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="aws:cloudwatchlogs:eks" sourceIPs{}=$src_ip$|rename sourceIPs{} as 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 -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" data.protoPayload.requestMetadata.callerIp={src_ip} | rename data.protoPayload.requestMetadata.callerIp as 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 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - 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. -action.escu.creation_date = 2018-03-19 -action.escu.modification_date = 2018-03-19 -action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] -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 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. -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=aws:cloudtrail | iplocation sourceIPAddress | search City=$City$ | 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, City, user, userName, userType, src_ip, awsRegion, eventName, errorCode - -[ESCU - Get All AWS Activity From Country - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get All AWS Activity From Country -description = This search retrieves all the activity from a specific country and will create a table containing the time, country, 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. -action.escu.creation_date = 2018-03-19 -action.escu.modification_date = 2018-03-19 -action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] -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 retrieves all the activity from a specific country and will create a table containing the time, country, 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. -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=aws:cloudtrail | iplocation sourceIPAddress | search Country=$Country$ | 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, Country, user, userName, userType, src_ip, awsRegion, eventName, errorCode - -[ESCU - Get All AWS Activity From IP Address - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get All AWS Activity From IP Address -description = This search retrieves all the activity from a specific IP address and will create a table containing the time, ARN, username, the type of user, the IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. -action.escu.creation_date = 2018-03-19 -action.escu.modification_date = 2018-03-19 -action.escu.analytic_story = ["AWS Network ACL Activity", "AWS Suspicious Provisioning Activities", "Command and Control", "Suspicious AWS S3 Activities", "Suspicious AWS Traffic"] -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 retrieves all the activity from a specific IP address and will create a table containing the time, ARN, username, the type of user, the IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. -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=aws:cloudtrail | iplocation sourceIPAddress | search sourceIPAddress=$src_ip$ | 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, user, userName, userType, src_ip, awsRegion, eventName, errorCode - -[ESCU - Get All AWS Activity From Region - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get All AWS Activity From Region -description = This search retrieves all the activity from a specific geographic region and will create a table containing the time, geographic region, 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. -action.escu.creation_date = 2018-03-19 -action.escu.modification_date = 2018-03-19 -action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] -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 retrieves all the activity from a specific geographic region and will create a table containing the time, geographic region, 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. -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=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 Authentication Logs For Endpoint - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Authentication Logs For Endpoint -description = This search returns all users that have attempted to access a particular endpoint. -action.escu.creation_date = 2017-11-01 -action.escu.modification_date = 2017-11-01 -action.escu.analytic_story = ["AWS Network ACL Activity", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Brand Monitoring", "ColdRoot MacOS RAT", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "Data Protection", "Disabling Security Tools", "Dynamic DNS", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Host Redirection", "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", "Router and Infrastructure Security", "SQL Injection", "SamSam Ransomware", "Spectre And Meltdown Vulnerabilities", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "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 = ["Authentication"] -action.escu.eli5 = This search returns all users that have attempted to access a particular 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 count from datamodel=Authentication where Authentication.dest=$dest$ by _time, Authentication.dest, Authentication.user, Authentication.app, Authentication.action | `drop_dm_object_name("Authentication")` - -[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 -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 -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 -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 -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 All_Traffic.src=$src_ip$ All_Traffic.dest=$dest_ip$ | eval ratio = (bytes_out/bytes_in) | table ratio - -[ESCU - Get EC2 Instance Details by instanceId - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - 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 -action.escu.creation_date = 2018-02-12 -action.escu.modification_date = 2018-02-12 -action.escu.analytic_story = ["AWS Cryptomining", "Cloud Cryptomining", "Suspicious AWS EC2 Activities", "Unusual AWS EC2 Modifications"] -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 AWS description logs and returns all the information about a specific instance via the instanceId field -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="aws:description" source="*:ec2_instances"| dedup id sortby -_time | search id=$instanceId$ | spath output=tags path=tags | eval tags=mvzip(key,value," = "), ip_address=if((ip_address == "null"),private_ip_address,ip_address) | table id, tags.Name, aws_account_id, placement, instance_type, key_name, ip_address, launch_time, state, vpc_id, subnet_id, tags | rename aws_account_id as "Account ID", id as ID, instance_type as Type, ip_address as "IP Address", key_name as "Key Pair", launch_time as "Launch Time", placement as "Availability Zone", state as State, subnet_id as Subnet, "tags.Name" as Name, vpc_id as VPC - -[ESCU - Get EC2 Launch Details - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get EC2 Launch Details -description = This search returns some of the launch details for a EC2 instance. -action.escu.creation_date = 2018-03-12 -action.escu.modification_date = 2018-03-12 -action.escu.analytic_story = ["AWS Cryptomining", "Cloud Cryptomining", "Suspicious AWS EC2 Activities"] -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 some of the launch details for a EC2 instance. -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=aws:cloudtrail responseElements.instancesSet.items{}.instanceId=$dest$ |rename userIdentity.arn as arn, responseElements.instancesSet.items{}.instanceId as instanceId, 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, instanceId, 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 -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 -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 -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 -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 = [] -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)` - -[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 -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 -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 -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 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"] -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, rule_name, owner, priority, severity, status_description - -[ESCU - Get Notable Info - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Notable Info -description = This search queries the notable index to retrieve detailed information captured within the notable. Every notable has a unique ID associated with it, which is used to point us directly to the notable event under investigation. -action.escu.creation_date = 2017-09-20 -action.escu.modification_date = 2017-09-20 -action.escu.analytic_story = ["AWS Cryptomining", "AWS Network ACL Activity", "AWS User Monitoring", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Asset Tracking", "Brand Monitoring", "Cloud Cryptomining", "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 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 Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "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", "Kubernetes Sensitive Role Activity", "Kubernetes Sensitive Object Access 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 queries the notable index to retrieve detailed information captured within the notable. Every notable has a unique ID associated with it, which is used to point us directly to the notable event 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_by_id($event_id$)` | table time, rule_name, dest, dest_asset_id, dest_owner, priority, severity, owner, 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 -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 = [] -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 -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 where Processes.process_name = $process_name$ Processes.dest = $dest$ by Processes.user Processes.parent_process_name Processes.process_name | `drop_dm_object_name("Processes")` | `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 -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"] -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_id) as process_id from datamodel=Endpoint.Filesystem where Filesystem.dest=$dest$ Filesystem.process_id=$process_id$ by Filesystem.file_path, Filesystem.action, _time | `drop_dm_object_name(Filesystem)` | sort _time | table _time, process_id, 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 -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 = ["Endpoint"] -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 `security_content_summariesonly` count min(_time) max(_time) as lastTime from datamodel=Endpoint.Processes where Proceses.dest=$dest$ Proceses.process_name=$process_name$ by Processes.parent_process Processes.process_name Processes.user Processes.dest | `drop_dm_object_name(Processes)` | `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 -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 where Processes.dest = $dest$ 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 [| tstats `security_content_summariesonly` count from datamodel=Endpoint.Ports where Ports.dest_port=$dest_port$ by Ports.process_id Ports.src | `drop_dm_object_name(Ports)` | rename src as dest] - -[ESCU - Get Process Registry Activity - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Process Registry Activity -description = This search returns the registry 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"] -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 registry 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(Registry.registry_key_name) as registry_key_name, values(Registry.dest) as dest, values(Registry.process_id) as process_id from datamodel=Endpoint.Registry where Registry.process_id=$process_id$ AND Registry.dest=$dest$ by Registry.registry_path, Registry.action, _time | `drop_dm_object_name(Registry)` | sort _time | table _time, process_id, dest, action, registry_key_name, registry_path - -[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 -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 where Processes.dest = $dest$ 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 [| 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 Registry Activities - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Registry Activities -description = This search queries the Endpoint Datamodel to give you details of the latest registry values for a specific destination computer. -action.escu.creation_date = 2019-03-01 -action.escu.modification_date = 2019-03-01 -action.escu.analytic_story = ["DHS Report TA18-074A", "Emotet Malware DHS Report TA18-201A ", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Ransomware", "Suspicious Command-Line Executions", "Suspicious MSHTA Activity", "Suspicious Windows Registry Activities", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Persistence Techniques", "Windows Privilege Escalation"] -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 Datamodel to give you details of the latest registry values for a specific destination computer. -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(Registry.registry_path) as registry_path values(Registry.registry_key_name) as registry_key_name count FROM datamodel=Endpoint.Registry where Registry.dest = "$dest$" by Registry.process_id Registry.dest | `drop_dm_object_name("Registry")` | join [| tstats `security_content_summariesonly` count values(Processes.user) as user values(Processes.process_name) as process_name values(Processes.parent_process_name) as parent_process_name FROM datamodel=Endpoint.Processes where Processes.process_name = reg.exe by Processes.process_id | `drop_dm_object_name("Processes")`] - -[ESCU - Get Risk Modifiers For Endpoint - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Risk Modifiers For Endpoint -description = For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk\_scores, names of the correlation searches that contributed to create a risk score for a specific endpoint(machine\_name) -action.escu.creation_date = 2017-10-19 -action.escu.modification_date = 2017-10-19 -action.escu.analytic_story = ["AWS Network ACL Activity", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Brand Monitoring", "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 Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Use of Cleartext Protocols", "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 = For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk\_scores, names of the correlation searches that contributed to create a risk score for a specific endpoint(machine\_name) -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:Risk.All_Risk | search risk_object_type=system risk_object=$dest$ | stats count sum(risk_score) as risk_score values(search_name) min(_time) as firstTime max(_time) as lastTime by risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - -[ESCU - Get Risk Modifiers For User - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Risk Modifiers For User -description = For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk_scores, names of the correlation searches that contributed to create a risk score for a specific user -action.escu.creation_date = 2017-10-19 -action.escu.modification_date = 2017-10-19 -action.escu.analytic_story = ["AWS Network ACL Activity", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Brand Monitoring", "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", "Lateral Movement", "Malicious PowerShell", "Monitor Backup Solution", "Monitor for Unauthorized Software", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "Router and Infrastructure Security", "SamSam Ransomware", "Spectre And Meltdown Vulnerabilities", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Use of Cleartext Protocols", "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 = For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk_scores, names of the correlation searches that contributed to create a risk score for 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 = | from datamodel:Risk.All_Risk | search risk_object_type=user risk_object=$user$ | stats count sum(risk_score) as risk_score values(search_name) min(_time) as firstTime max(_time) as lastTime by risk_object |`security_content_ctime(firstTime)` |`security_content_ctime(lastTime)` - -[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 -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 host=$dest$ | rename host as dest | table _time, dest, user, Name, Operation, EventType, Type, Query, Consumer, Filter - -[ESCU - Get Update Logs For Endpoint - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Update Logs For Endpoint -description = This search will tell you give you the update logs for a specific endpoint for the last week. -action.escu.creation_date = 2017-08-24 -action.escu.modification_date = 2017-08-24 -action.escu.analytic_story = ["Emotet Malware DHS Report TA18-201A ", "Monitor for Unauthorized Software", "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 give you the update logs for 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 = | from datamodel Updates.Updates | search (vendor_product="Microsoft Windows" OR vendor_product="OSX:Update" OR vendor_product="Linux:Update") dest=$dest$ - -[ESCU - Get User Information from Identity Table - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get User Information from Identity Table -description = Gather more information about the user identified in the Notable Event. -action.escu.creation_date = 2017-09-20 -action.escu.modification_date = 2017-09-20 -action.escu.analytic_story = ["AWS Cryptomining", "AWS Network ACL Activity", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Brand Monitoring", "Cloud Cryptomining", "ColdRoot MacOS RAT", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "Data Protection", "Disabling Security Tools", "Dynamic DNS", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Host Redirection", "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", "Router and Infrastructure Security", "SamSam Ransomware", "Spectre And Meltdown Vulnerabilities", "Suspicious AWS EC2 Activities", "Suspicious AWS S3 Activities", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Use of Cleartext Protocols", "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 = Gather more information about the user identified in the Notable Event. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | `identities` | search identity=$user$ | table _time, identity, first, last, email, category, watchlist - -[ESCU - Get Vulnerability Logs For Endpoint - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Vulnerability Logs For Endpoint -description = This search will show you any vulnerabilities noted for a specific endpoint for the last week. -action.escu.creation_date = 2017-09-10 -action.escu.modification_date = 2017-09-10 -action.escu.analytic_story = ["ColdRoot MacOS RAT", "DHS Report TA18-074A", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "JBoss Vulnerability", "Monitor for Unauthorized Software", "Ransomware", "SamSam Ransomware", "Windows Log Manipulation"] -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 show you any vulnerabilities noted for 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 = | from datamodel Vulnerabilities.Vulnerabilities | search dest=$dest$ - -[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 -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 $session_id$ | stats values(url) values(http_user_agent) by src_ip status - -[ESCU - Investigate AWS ECR container listing activity - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate AWS ECR container listing activity -description = This search lists all the users performing a list image operation on AWS Elastic Container Registry. Listing source user, image id, source IP, user type, http user agent. This search also gives counts of unique user agents per listing source. -action.escu.creation_date = 2020-02-20 -action.escu.modification_date = 2020-02-20 -action.escu.analytic_story = ["Container Implantation Monitoring and Investigation"] -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 lists all the users performing a list image operation on AWS Elastic Container Registry. Listing source user, image id, source IP, user type, http user agent. This search also gives counts of unique user agents per listing 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 count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Cloud_Infrastructure.Compute where Compute.user_type!="AssumeRole" AND Compute.event_name="ListImages" by Compute.image_id Compute.src_user Compute.src Compute.http_user_agent Compute.user_type | rename "Compute.*" as * |stats values(http_user_agent) as http_user_agent distinct_count(http_user_agent) as unique_ua_count by src_user, image_id, src, user_type | where unique_ua_count > 1 - -[ESCU - Investigate AWS User Activities by user field - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - 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. -action.escu.creation_date = 2018-03-12 -action.escu.modification_date = 2018-03-12 -action.escu.analytic_story = ["AWS User Monitoring"] -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 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. -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=aws:cloudtrail user=$user$ | table _time userIdentity.type userIdentity.userName userIdentity.arn aws_account_id src awsRegion eventName eventType - -[ESCU - Investigate AWS activities via region name - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate AWS activities via region name -description = This search lists all the user activities logged by CloudTrail for a specific region in question and will create a table of the values of parameters requested, the type of the event and the response from the AWS API by each user -action.escu.creation_date = 2018-02-09 -action.escu.modification_date = 2018-02-09 -action.escu.analytic_story = ["AWS Cryptomining", "Cloud Cryptomining", "Suspicious AWS EC2 Activities", "Suspicious AWS S3 Activities"] -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 lists all the user activities logged by CloudTrail for a specific region in question and will create a table of the values of parameters requested, the type of the event and the response from the AWS API by each 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 = | search sourcetype=aws:cloudtrail awsRegion=$awsRegion$| rename requestParameters.instancesSet.items{}.instanceId as instanceId| stats values(eventName) by userName instanceId - -[ESCU - Investigate Cloud Compute Instance Activities - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Cloud Compute Instance Activities -description = This search returns a logs of events that operated on the compute instance. -action.escu.creation_date = 2018-03-12 -action.escu.modification_date = 2018-03-12 -action.escu.analytic_story = ["Cloud Cryptomining"] -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 a logs of events that operated on the compute instance. -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:Cloud_Infrastructure.Compute | search dest=$dest$ | fields - _* - -[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 -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")` - -[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 -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 -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 -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 -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)` - -[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 -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 | stats count BY user, dest, EventCode | stats max(count) AS max_count sum(count) AS sum_count BY user, dest | where sum_count/max_count!=2 - -[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 -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")` - -[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 -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")`| 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 -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 src_ip="$src_ip$" 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 All Cloud Regions - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate User Activities In All Cloud Regions -description = This search lists all the logged cloud infrastructure activities by a specific cloud user -action.escu.creation_date = 2019-04-30 -action.escu.modification_date = 2019-04-30 -action.escu.analytic_story = ["Cloud Cryptomining"] -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 lists all the logged cloud infrastructure activities by a specific cloud 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 = | from datamodel:Cloud_Infrastructure.Compute | search user=$src_user$ | fields - _* - -[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 -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 User Activities In Single Cloud Region - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate User Activities In Single Cloud Region -description = This search lists all the logged cloud infrastructure activities by a specific cloud user in a specific cloud region -action.escu.creation_date = 2019-04-30 -action.escu.modification_date = 2019-04-30 -action.escu.analytic_story = ["Cloud Cryptomining"] -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 lists all the logged cloud infrastructure activities by a specific cloud user in a specific cloud region -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:Cloud_Infrastructure.Compute | search region=$region$ user=$src_user$ | fields - _* - -[ESCU - Investigate Web Activity From Host - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Web Activity From Host -description = This search allows you to find all the web activity from a specific host. During an investigation, it is important to profile web activity to characterize user or host activity. -action.escu.creation_date = 2017-11-09 -action.escu.modification_date = 2017-11-09 -action.escu.analytic_story = ["Brand Monitoring", "DHS Report TA18-074A", "Disabling Security Tools", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "JBoss Vulnerability", "Monitor for Unauthorized Software", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Ransomware", "SamSam Ransomware", "Suspicious Command-Line Executions", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious Windows Registry Activities", "Unusual Processes", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation"] -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 web activity from a specific host. During an investigation, it is important to profile web activity to characterize user or host activity. -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 Web.Web | search src=$dest$ - -[ESCU - Investigate Web Activity From src ip - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Web Activity From src ip -description = This search searches for all web activity from a specific host. During an investigation, it is important to profile web activity to characterize user or host activity. -action.escu.creation_date = 2018-06-15 -action.escu.modification_date = 2018-06-15 -action.escu.analytic_story = ["ColdRoot MacOS RAT", "Dynamic DNS", "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 searches for all web activity from a specific host. During an investigation, it is important to profile web activity to characterize user or host activity. -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 Web.Web | search src=$src_ip$ - -[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 -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")`| where like(src, "$src$") and like(http_method, "POST") - -[ESCU - Process Chain Analysis - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Process Chain Analysis -description = Analyze the Process Chain and identify the malicious file. By analyzing the parent process guid and searching for the process guid, the spawning process chain can be identified. -action.escu.creation_date = 2020-04-29 -action.escu.modification_date = 2020-04-29 -action.escu.analytic_story = [] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = Analyze the Process Chain and identify the malicious file. By analyzing the parent process guid and searching for the process guid, the spawning process chain can be identified. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = `sysmon` EventCode=1 NOT process=*Splunk* | rename process_guid AS out_process_guid process_name AS out_process_name parent_process_guid AS out_parent_process_guid parent_process_name AS out_parent_process_name | stats count by out_process_guid out_process_name out_parent_process_guid out_parent_process_name | eval join_process_guid = out_process_guid | join join_process_guid [ search `sysmon` process_guid={process_guid} EventCode=1 | rename process_name AS sub_process_name process_guid AS sub_process_guid parent_process_name AS sub_parent_process_name parent_process_guid AS sub_parent_process_guid | stats count by sub_process_name sub_process_guid sub_parent_process_name sub_parent_process_guid | eval join_process_guid = sub_parent_process_guid] | rename sub_process_guid AS process_guid sub_process_name AS process_name out_process_guid AS parent_process_guid out_process_name AS parent_process_name out_parent_process_guid AS grandparent_process_guid out_parent_process_name AS grandparent_process_name | stats count by process_guid process_name parent_process_guid parent_process_name grandparent_process_guid grandparent_process_name | head 1 | fields - count - - - -### END ESCU RESPONSE TASKS ### - -### USAGE DASHBOARD CONFIGURATIONS ### - -[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=* - -### END OF USAGE DASHBOARD CONFIGURATIONS ### \ No newline at end of file diff --git a/package/default/transforms.conf b/package/default/transforms.conf deleted file mode 100644 index 5a6491027d..0000000000 --- a/package/default/transforms.conf +++ /dev/null @@ -1,202 +0,0 @@ -############# -# Automatically generated by generator.py in splunk/security-content -# On Date: 2020-06-03T20:28:01 UTC -# Author: Splunk Security Research -# Contact: research@splunk.com -############# - -[api_call_by_user_baseline] -filename = api_call_by_user_baseline.csv -# description = A lookup file that will contain the baseline information for number of AWS API calls per user - -[aws_service_accounts] -filename = aws_service_accounts.csv -# description = A lookup file that will contain AWS Service accounts - -[baseline_blocked_outbound_connections] -filename = baseline_blocked_outbound_connections.csv -# description = A lookup file that will contain the baseline information for number of blocked outbound connections - -[brandMonitoring_lookup] -filename = brand_monitoring.csv -default_match = false -# description = A file that contains look-a-like domains for brands that you want to monitor -match_type = WILDCARD(domain) -min_matches = 1 - -[csc_lookup] -filename = csc_lookup.csv -# description = The CSC control numbers and names -min_matches = 1 - -[discovered_dns_records] -filename = discovered_dns_records.csv -default_match = false -# description = A placeholder for a list of discovered DNS records generated by the baseline discover_dns_records -min_matches = 1 - -[domains] -filename = domains.csv -# description = A list of domains that can be whitelisted - -[dynamic_dns_providers_default] -filename = dynamic_dns_providers_default.csv -case_sensitive_match = false -# description = A list of dynammic dns providers that should not be modified -match_type = WILDCARD(dynamic_dns_domains) - -[dynamic_dns_providers_local] -filename = dynamic_dns_providers_local.csv -case_sensitive_match = false -# description = A list of dynammic dns providers that can be modified -match_type = WILDCARD(dynamic_dns_domains) - -[escu_search_id_lookup] -filename = escu_search_id.csv -# description = A placeholder lookup file to hold information for ESCU Usage dashboard - -[is_suspicious_file_extension_lookup] -filename = is_suspicious_file_extension_lookup.csv -# description = A list of suspicious extensions for email attachments -match_type = WILDCARD(file_name) - -[is_windows_system_file] -filename = is_windows_system_file.csv -default_match = false -# description = A list of executable files in Windows\System32 -min_matches = 1 - -[legit_domains] -filename = legit_domains.csv -# description = A list of legit domains to be used to whitelist possible phishing sites - -[lookup_rare_process_whitelist_default] -filename = rare_process_whitelist_default.csv -default_match = false -case_sensitive_match = false -# description = A list of rare processes that are legitimate provided by Splunk -match_type = WILDCARD(process) -min_matches = 1 - -[lookup_rare_process_whitelist_local] -filename = rare_process_whitelist_local.csv -default_match = false -case_sensitive_match = false -# description = A list of rare processes that are legitimate provided by the end user -match_type = WILDCARD(process) -min_matches = 1 - -[lookup_uncommon_processes_default] -filename = uncommon_processes_default.csv -case_sensitive_match = false -# description = A list of processes that are not common -match_type = WILDCARD(process) - -[lookup_uncommon_processes_local] -filename = uncommon_processes_local.csv -case_sensitive_match = false -# description = A list of processes that are not common -match_type = WILDCARD(process) - -[network_acl_activity_baseline] -filename = network_acl_activity_baseline.csv -# description = A lookup file that will contain the baseline information for number of AWS Network ACL Activity - -[previously_seen_S3_access_from_remote_ip] -filename = previously_seen_S3_access_from_remote_ip.csv -# description = A placeholder for a list of IPs that have access S3 - -[previously_seen_api_calls_from_user_roles] -filename = previously_seen_api_calls_from_user_roles.csv -# description = A placeholder for a list of AWS API calls for each user role - -[previously_seen_aws_cross_account_activity] -filename = previously_seen_aws_cross_account_activity.csv -# description = A placeholder for a list of AWS accounts and assumed roles - -[previously_seen_aws_regions] -filename = previously_seen_aws_regions.csv -default_match = false -# description = A place holder for a list of used AWS regions -min_matches = 1 - -[previously_seen_cloud_compute_creations_by_user] -filename = previously_seen_cloud_compute_creations_by_user.csv -default_match = false -# description = A place holder for a list of users that have created cloud compute instances -min_matches = 1 - -[previously_seen_cloud_compute_images] -filename = previously_seen_cloud_compute_images.csv -default_match = false -# description = A place holder for a list of used cloud compute images -min_matches = 1 - -[previously_seen_cloud_compute_instance_types] -filename = previously_seen_cloud_compute_instance_types.csv -default_match = false -# description = A place holder for a list of used cloud compute instance types -min_matches = 1 - -[previously_seen_cloud_regions] -filename = previously_seen_cloud_regions.csv -default_match = false -# description = A place holder for a list of used cloud compute images -min_matches = 1 - -[previously_seen_cmd_line_arguments] -filename = previously_seen_cmd_line_arguments.csv -# description = A placeholder for a list of cmd line arugments that been seen before - -[previously_seen_ec2_modifications_by_user] -filename = previously_seen_ec2_modifications_by_user.csv -# description = A place holder for a list of AWS EC2 modifications done by each user - -[previously_seen_running_windows_services] -filename = previously_seen_running_windows_services.csv -# description = A placeholder for the list of Windows Services running - -[prohibitedProcesses_lookup] -filename = prohibited_processes.csv -# description = A list of processes that have been marked as prohibited - -[prohibited_apps_launching_cmd] -filename = prohibited_apps_launching_cmd.csv -# description = A list of processes that should not be launching cmd.exe -match_type = WILDCARD(prohibited_applications) - -[ransomware_extensions_lookup] -filename = ransomware_extensions.csv -default_match = false -# description = A list of file extensions that are associated with ransomware -min_matches = 1 - -[ransomware_notes_lookup] -filename = ransomware_notes.csv -default_match = false -# description = A list of file names that are ransomware note files -match_type = WILDCARD(ransomware_notes) -min_matches = 1 - -[s3_deletion_baseline] -filename = s3_deletion_baseline.csv -# description = A placeholder for the baseline information for AWS S3 deletions - -[security_group_activity_baseline] -filename = security_group_activity_baseline.csv -# description = A placeholder for the baseline information for AWS security groups - -[security_services_lookup] -filename = security_services.csv -default_match = false -# description = A list of services that deal with security -match_type = WILDCARD(service) -min_matches = 1 - -[suspicious_writes_lookup] -filename = suspicious_files.csv -default_match = false -# description = A list of suspicious file names -match_type = WILDCARD(file) -min_matches = 1 - diff --git a/package/default/use_case_library.conf b/package/default/use_case_library.conf deleted file mode 100644 index 1404585c4d..0000000000 --- a/package/default/use_case_library.conf +++ /dev/null @@ -1,3818 +0,0 @@ -############# -# Automatically generated by generator.py in splunk/security-content -# On Date: 2020-06-03T20:28:01 UTC -# Author: Splunk Security Research -# Contact: research@splunk.com -############# - -### STORIES ### - -[analytic_story://AWS Cross Account Activity] -category = Cloud Security -last_updated = 2018-06-04 -version = 1 -references = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] -maintainers = "David Dorsey, Splunk" -spec_version = 3 -searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - AWS Investigate User Activities By Source User", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By AccessKeyId"] -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.\ -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. - -[analytic_story://AWS Cryptomining] -category = Cloud Security -last_updated = 2018-03-08 -version = 1 -references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] -maintainers = "David Dorsey, Splunk" -spec_version = 3 -searches = ["ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get EC2 Launch Details", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] -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. \ -hen 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. - -[analytic_story://AWS Network ACL Activity] -category = Cloud Security -last_updated = 2018-05-21 -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 = "Bhavin Patel, Splunk" -spec_version = 3 -searches = ["ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network ACL Details from ID", "ESCU - Get User Information from Identity Table"] -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. - -[analytic_story://AWS Suspicious Provisioning Activities] -category = Cloud Security -last_updated = 2018-03-16 -version = 1 -references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] -maintainers = "David Dorsey, Splunk" -spec_version = 3 -searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Country"] -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 whitelist specific IPs (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. - -[analytic_story://AWS User Monitoring] -category = Cloud Security -last_updated = 2018-03-12 -version = 1 -references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] -maintainers = "Bhavin Patel, Splunk" -spec_version = 3 -searches = ["ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Get Notable History", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable Info"] -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. \ -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. - -[analytic_story://Account Monitoring and Controls] -category = Best Practices -last_updated = 2017-09-06 -version = 1 -references = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] -maintainers = "David Dorsey, Splunk" -spec_version = 3 -searches = ["ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Short Lived Windows Accounts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] -description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. -narrative = Monitoring user accounts within your enterprise is a critical analytic function that helps ensure that credential and access policies/procedures are properly implemented and are being enforced. Proactive ad-hoc hunting, as well as routine monitoring, can ensure user or system accounts are not being abused by unauthorized individuals or processes. In the event of a network event or breach, user-authentication logs are a key resource in determining if or how an account might have been compromised or co-opted, leading to suspicious or malicious activity. - -[analytic_story://Apache Struts Vulnerability] -category = Vulnerability -last_updated = 2018-12-06 -version = 1 -references = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] -maintainers = "Rico Valdez, Splunk" -spec_version = 3 -searches = ["ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Suspicious Java Classes - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Investigate Web POSTs From src", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Suspicious Strings in HTTP Header"] -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.\ -This Analytic Story contains two different searches that help to identify activity that may be related to this issue. The first search looks for characteristics of the `Content-Type` header consistent with attempts to exploit the vulnerability. This should be a relatively pertinent indicator, as the `Content-Type` header is generally consistent and does not have a large degree of variation.\ -The second search looks for the execution of various commands typically entered on the command shell when an attacker first lands on a system. These commands are not generally executed on web servers during the course of day-to-day operation, but they may be used when the system is undergoing maintenance or troubleshooting.\ -First, it is helpful is to understand how often the notable event is generated, as well as the commonalities in some of these events. This may help determine whether this is a common occurrence that is of a lesser concern or a rare event that may require more extensive investigation. It can also help to understand whether the issue is restricted to a single user or system or is broader in scope.\ -hen looking at the target of the behavior illustrated by the event, you should note the sensitivity of the user and or/system to help determine the potential impact. It is also helpful to see what other events involving the target have occurred in the recent past. This can help tie different events together and give further situational awareness regarding the target.\ -Various types of information for external systems should be reviewed and (potentially) collected if the incident is, indeed, judged to be malicious. Information like this can be useful in generating your own threat intelligence to create alerts in the future.\ -Looking at the country, responsible party, and fully qualified domain names associated with the external IP address--as well as the registration information associated with those domain names, if they are frequently visited by others--can help you answer the question of "who," in regard to the external system. Answering that can help qualify the event and may serve useful for tracking. In addition, there are various sources that can provide some reputation information on the IP address or domain name, which can assist in determining if the event is malicious in nature. Finally, determining whether or not there are other events associated with the IP address may help connect some dots or show other events that should be brought into scope.\ -Gathering various data elements on the system of interest can sometimes help quickly determine that something suspicious may be happening. Some of these items include determining who else may have recently logged into the system, whether any unusual scheduled tasks exist, whether the system is communicating on suspicious ports, whether there are modifications to sensitive registry keys, and whether there are any known vulnerabilities on the system. This information can often highlight other activity commonly seen in attack scenarios or give more information about how the system may have been targeted.\ -hen a specific service or application is targeted, it is often helpful to know the associated version to help determine whether or not it is vulnerable to a specific exploit.\ -hen it is suspected there is an attack targeting a web server, it is helpful to look at some of the behavior of the web service to see if there is evidence that the service has been compromised. Some indications of this might be network connections to external resources, the web service spawning child processes that are not associated with typical behavior, and whether the service wrote any files that might be malicious in nature.\ -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. - -[analytic_story://Asset Tracking] -category = Best Practices -last_updated = 2017-09-13 -version = 1 -references = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] -maintainers = "Bhavin Patel, Splunk" -spec_version = 3 -searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address"] -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://Brand Monitoring] -category = Abuse -last_updated = 2017-12-19 -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 = "David Dorsey, Splunk" -spec_version = 3 -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 Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get User Information from Identity Table", "ESCU - Get Email Info"] -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.\ -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. - -[analytic_story://Cloud Cryptomining] -category = Cloud Security -last_updated = 2019-10-02 -version = 1 -references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] -maintainers = "David Dorsey, Splunk" -spec_version = 3 -searches = ["ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get EC2 Launch Details", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] -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. \ -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. - -[analytic_story://ColdRoot MacOS RAT] -category = Malware -last_updated = 2019-01-09 -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 = "Jose Hernandez, Splunk" -spec_version = 3 -searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable History", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get User Information from Identity Table"] -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.\ -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. - -[analytic_story://Collection and Staging] -category = Adversary Tactics -last_updated = 2020-02-03 -version = 1 -references = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] -maintainers = "Rico Valdez, Splunk" -spec_version = 3 -searches = ["ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -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. \ -Use the searches to detect and monitor suspicious behavior related to these activities. - -[analytic_story://Command and Control] -category = Adversary Tactics -last_updated = 2018-06-01 -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 = "Rico Valdez, Splunk" -spec_version = 3 -searches = ["ESCU - Excessive DNS Failures - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - TOR Traffic - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network ACL Details from ID", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -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. - -[analytic_story://Common Phishing Frameworks] -category = Adversary Tactics -last_updated = 2019-04-29 -version = 1 -references = ["https://github.com/kgretzky/evilginx2", "https://attack.mitre.org/techniques/T1192/", "https://breakdev.org/evilginx-advanced-phishing-with-two-factor-authentication-bypass/"] -maintainers = "Splunk Research Team, Splunk" -spec_version = 3 -searches = ["ESCU - Detect DNS requests to Phishing Sites leveraging EvilGinx2 - Rule", "ESCU - Get Certificate logs for a domain"] -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. - -[analytic_story://Container Implantation Monitoring and Investigation] -category = Cloud Security -last_updated = 2020-02-20 -version = 1 -references = ["https://github.com/splunk/cloud-datamodel-security-research"] -maintainers = "Rod Soto, Rico Valdez, Splunk" -spec_version = 3 -searches = ["ESCU - New container uploaded to AWS ECR - Rule", "ESCU - GCP GCR container uploaded - Rule", "ESCU - Investigate AWS ECR container listing activity"] -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. - -[analytic_story://Credential Dumping] -category = Adversary Tactics -last_updated = 2020-02-04 -version = 3 -references = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] -maintainers = "Rico Valdez, Splunk" -spec_version = 3 -searches = ["ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Pass the Ticket Attempts"] -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.\ -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. - -[analytic_story://DHS Report TA18-074A] -category = Malware -last_updated = 2020-01-22 -version = 2 -references = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] -maintainers = "Rico Valdez, Splunk" -spec_version = 3 -searches = ["ESCU - Suspicious Reg exe Process - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process File Activity", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Registry Activity", "ESCU - Get Parent Process Info"] -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. \ -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. - -[analytic_story://DNS Amplification Attacks] -category = Abuse -last_updated = 2016-09-13 -version = 1 -references = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] -maintainers = "Bhavin Patel, Splunk" -spec_version = 3 -searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info"] -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. - -[analytic_story://DNS Hijacking] -category = Adversary Tactics -last_updated = 2020-02-04 -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 = "Bhavin Patel, Splunk" -spec_version = 3 -searches = ["ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple 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"] -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. \ -On January 22, 2019, the US Department of Homeland Security 2019's Cybersecurity and Infrastructure Security Agency (CISA) raised awareness of some high-profile DNS hijacking attacks against infrastructure, both in the United States and abroad. It issued Emergency Directive 19-01 (see https://cyber.dhs.gov/ed/19-01/), which summarized the activity and required government agencies to take the following four actions, all within 10 days: \ -1. For all .gov or other agency-managed domains, audit public DNS records on all authoritative and secondary DNS servers, verify that they resolve to the intended location or report them to CISA.\ -1. Update the passwords for all accounts on systems that can make changes to each agency 2019's DNS records.\ -1. Implement multi-factor authentication (MFA) for all accounts on systems that can make changes to each agency's 2019 DNS records or, if impossible, provide CISA with the names of systems, the reasons why MFA cannot be enabled within the required timeline, and an ETA for when it can be enabled.\ -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. - -[analytic_story://Data Protection] -category = Abuse -last_updated = 2017-09-14 -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 = "Bhavin Patel, Splunk" -spec_version = 3 -searches = ["ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio", "ESCU - Get User Information from Identity Table"] -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. - -[analytic_story://Disabling Security Tools] -category = Adversary Tactics -last_updated = 2020-02-04 -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 = "Rico Valdez, Splunk" -spec_version = 3 -searches = ["ESCU - Suspicious Reg exe Process - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -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 blacklist (which would prevent them from running). - -[analytic_story://Dynamic DNS] -category = Malware -last_updated = 2018-09-06 -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 = "Bhavin Patel, Splunk" -spec_version = 3 -searches = ["ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio", "ESCU - Get User Information from Identity Table"] -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 blacklists. -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 blacklists 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. - -[analytic_story://Emotet Malware DHS Report TA18-201A ] -category = Malware -last_updated = 2020-01-27 -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 = "Bhavin Patel, Splunk" -spec_version = 3 -searches = ["ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -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.\ -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. - -[analytic_story://Hidden Cobra Malware] -category = Malware -last_updated = 2020-01-22 -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 = "Rico Valdez, Splunk" -spec_version = 3 -searches = ["ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -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.\ -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. - -[analytic_story://Host Redirection] -category = Abuse -last_updated = 2017-09-14 -version = 1 -references = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] -maintainers = "Rico Valdez, Splunk" -spec_version = 3 -searches = ["ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] -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. - -[analytic_story://JBoss Vulnerability] -category = Vulnerability -last_updated = 2017-09-14 -version = 1 -references = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] -maintainers = "Bhavin Patel, Splunk" -spec_version = 3 -searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info"] -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.\ -hen looking at the target of the behavior uncovered by the event, you should note the sensitivity of the user and or/system to help determine the potential impact. It is also helpful to identify other recent events involving the target. This can help tie different events together and give further situational awareness regarding the target host.\ -Various types of information for external systems should be reviewed and, potentially, collected if the incident is, indeed, judged to be malicious. This data may be useful for generating your own threat intelligence, so you can create future alerts.\ -The following factors may assist you in determining whether the event is malicious: \ -1. Country of origin\ -1. Responsible party\ -1. Fully qualified domain names associated with the external IP address\ -1. Registration of fully qualified domain names associated with external IP address Determining whether it is a dynamic domain frequently visited by others and/or how third parties categorize it can also help you qualify and understand the event and possible motivation for the attack. In addition, there are various sources that may provide reputation information on the IP address or domain name, which can assist you in determining whether the event is malicious in nature. Finally, determining whether there are other events associated with the IP address may help connect data points or expose other historic events that might be brought back into scope.\ -Gathering various data on the system of interest can sometimes help quickly determine whether something suspicious is happening. Some of these items include determining who else may have logged into the system recently, whether any unusual scheduled tasks exist, whether the system is communicating on suspicious ports, whether there are modifications to sensitive registry keys, and/or whether there are any known vulnerabilities on the system. This information can often highlight other activity commonly seen in attack scenarios or give more information about how the system may have been targeted.\ -hen a specific service or application is targeted, it is often helpful to know the associated version, to help determine whether it is vulnerable to a specific exploit.\ -If you suspect an attack targeting a web server, it is helpful to look at some of the behavior of the web service to see if there is evidence that the service has been compromised. Some indications of this might be network connections to external resources, the web service spawning child processes that are not associated with typical behavior, and whether the service wrote any files that might be malicious in nature.\ -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. - -[analytic_story://Kubernetes Scanning Activity] -category = Cloud Security -last_updated = 2020-04-15 -version = 1 -references = ["https://github.com/splunk/cloud-datamodel-security-research"] -maintainers = "Rod Soto, Splunk" -spec_version = 3 -searches = ["ESCU - Kubernetes Azure scan fingerprint - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Kubernetes Azure pod scan fingerprint - Rule", "ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Amazon EKS Kubernetes activity by src ip"] -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. - -[analytic_story://Kubernetes Sensitive Object Access Activity] -category = Cloud Security -last_updated = 2020-05-20 -version = 1 -references = ["https://www.splunk.com/en_us/blog/security/approaching-kubernetes-security-detecting-kubernetes-scan-with-splunk.html"] -maintainers = "Rod Soto, Splunk" -spec_version = 3 -searches = ["ESCU - Kubernetes Azure detect suspicious kubectl calls - Rule", "ESCU - Kubernetes Azure detect service accounts forbidden failure access - Rule", "ESCU - Kubernetes Azure detect sensitive object access - Rule", "ESCU - Get Notable Info"] -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. - -[analytic_story://Kubernetes Sensitive Role Activity] -category = Cloud Security -last_updated = 2020-05-20 -version = 1 -references = ["https://www.splunk.com/en_us/blog/security/approaching-kubernetes-security-detecting-kubernetes-scan-with-splunk.html"] -maintainers = "Rod Soto, Splunk" -spec_version = 3 -searches = ["ESCU - Kubernetes Azure detect sensitive role access - Rule", "ESCU - Kubernetes Azure detect most active service accounts by pod namespace - Rule", "ESCU - Kubernetes Azure detect RBAC authorization by account - Rule", "ESCU - Get Notable Info"] -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 - -[analytic_story://Lateral Movement] -category = Adversary Tactics -last_updated = 2020-02-04 -version = 2 -references = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] -maintainers = "David Dorsey, Splunk" -spec_version = 3 -searches = ["ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -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.\ -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. - -[analytic_story://Malicious PowerShell] -category = Adversary Tactics -last_updated = 2017-08-23 -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 = "David Dorsey, Splunk" -spec_version = 3 -searches = ["ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - 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 - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -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: \ -1. Country of origin\ -1. Responsible party\ -1. Fully qualified domain names associated with the external IP address\ -1. Registration of fully qualified domain names associated with external IP addressDetermining whether it is a dynamic domain frequently visited by others and/or how third parties categorize it can also help you answer some questions surrounding the attacker and details related to the external system. In addition, there are various sources--such as VirusTotal— that can provide some reputation information on the IP address or domain name, which can assist in determining whether the event is malicious. Finally, determining whether there are other events associated with the IP address may help connect data points or show other events that should be brought into scope.\ -Gathering data on the system of interest can sometimes help you quickly determine whether something suspicious is happening. Some of these items include finding out who else may have recently logged into the system, whether any unusual scheduled tasks exist, whether the system is communicating on suspicious ports, whether there are modifications to sensitive registry keys, and whether there are any known vulnerabilities on the system. This information can often highlight other activity commonly seen in attack scenarios or give more information about how the system may have been targeted.\ -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. - -[analytic_story://Monitor Backup Solution] -category = Best Practices -last_updated = 2017-09-12 -version = 1 -references = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] -maintainers = "David Dorsey, Splunk" -spec_version = 3 -searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - All backup logs for host", "ESCU - Get Risk Modifiers For User"] -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. - -[analytic_story://Monitor for Unauthorized Software] -category = Best Practices -last_updated = 2017-09-15 -version = 1 -references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] -maintainers = "David Dorsey, Splunk" -spec_version = 3 -searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Update Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -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. - -[analytic_story://Monitor for Updates] -category = Best Practices -last_updated = 2017-09-15 -version = 1 -references = ["https://learn.cisecurity.org/20-controls-download"] -maintainers = "Rico Valdez, Splunk" -spec_version = 3 -searches = ["ESCU - No Windows Updates in a time frame - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] -description = Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches. -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. - -[analytic_story://Netsh Abuse] -category = Abuse -last_updated = 2017-01-05 -version = 1 -references = ["https://technet.microsoft.com/library/bb490939.aspx", "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 = "Bhavin Patel, Splunk" -spec_version = 3 -searches = ["ESCU - Processes launching netsh - Rule", "ESCU - Processes created by netsh - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -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`. - -[analytic_story://Orangeworm Attack Group] -category = Malware -last_updated = 2020-01-22 -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 = "David Dorsey, Splunk" -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 Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -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.\ -Although the group's motivation is unknown, its goal may be stealing patient information to sell on the black market. Another possible explanation is corporate espionage. \ -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. - -[analytic_story://Phishing Payloads] -category = Adversary Tactics -last_updated = 2019-04-29 -version = 1 -references = ["https://www.fireeye.com/blog/threat-research/2019/04/spear-phishing-campaign-targets-ukraine-government.html"] -maintainers = "Splunk Research Team, Splunk" -spec_version = 3 -searches = ["ESCU - Detect Oulook exe writing a zip file - Rule", "ESCU - Suspicious LNK file launching a process - Rule", "ESCU - Get Parent Process Info"] -description = Detect signs of malicious payloads that may indicate that your environment has been breached via a phishing attack. -narrative = Despite its simplicity, phishing remains the most pervasive and dangerous cyberthreat. In fact, research shows that as many as [91% of all successful attacks](https://digitalguardian.com/blog/91-percent-cyber-attacks-start-phishing-email-heres-how-protect-against-phishing) are initiated via a phishing email. \ -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. Worse, because its success relies on the gullibility of humans, it's impossible to completely "automate" it out of your environment. However, you can use ES and ESCU to detect and investigate potentially malicious payloads injected into your environment subsequent to a phishing attack. \ -hile any kind of file may contain a malicious payload, some are more likely to be perceived as benign (and thus more often escape notice) by the average victim—especially when the attacker sends an email that seems to be from one of their contacts. An example is Microsoft Office files. Most corporate users are familiar with documents with the following suffixes: .doc/.docx (MS Word), .xls/.xlsx (MS Excel), and .ppt/.pptx (MS PowerPoint), so they may click without a second thought, slashing a hole in their organizations' security. \ -Following is a typical series of events, according to an [article by Trend Micro](https://blog.trendmicro.com/trendlabs-security-intelligence/rising-trend-attackers-using-lnk-files-download-malware/):\ -1. Attacker sends a phishing email. Recipient downloads the attached file, which is typically a .docx or .zip file with an embedded .lnk file\ -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. - -[analytic_story://Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns] -category = Adversary Tactics -last_updated = 2020-01-22 -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 = "iDefense Cyber Espionage Team, iDefense" -spec_version = 3 -searches = ["ESCU - Registry Keys Used For Persistence - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -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.\ -The MUDCARP techniques include the use of the compressed-folders module from Microsoft, zipfldr.dll, with RouteTheCall export to run the malicious process or command. After a successful reboot, the malware is made persistent by a manipulating `[HKEY_CURRENT_USER\SOFTWARE\Microsoft\Windows\CurrentVersion\Run]'help'='c:\\windows\\system32\\rundll32.exe c:\\windows\\system32\\zipfldr.dll,RouteTheCall c:\\programdata\\winapp.exe'`. Though this technique is not exclusive to MUDCARP, it has been spotted in the group's arsenal of advanced techniques seen in the wild.\ -This Analytic Story searches for evidence of tactics, techniques, and procedures (TTPs) that allow for the use of a endpoint detection-and-response (EDR) bypass technique to mask the true parent of a malicious process. It can also be set as a registry key for further sandbox evasion and to allow the malware to launch only after reboot.\ -If behavioral searches included in this story yield positive hits, iDefense recommends conducting IOC searches for the following:\ -\ -1. www.chemscalere[.]com\ -1. chemscalere[.]com\ -1. about.chemscalere[.]com\ -1. autoconfig.chemscalere[.]com\ -1. autodiscover.chemscalere[.]com\ -1. catalog.chemscalere[.]com\ -1. cpanel.chemscalere[.]com\ -1. db.chemscalere[.]com\ -1. ftp.chemscalere[.]com\ -1. mail.chemscalere[.]com\ -1. news.chemscalere[.]com\ -1. update.chemscalere[.]com\ -1. webmail.chemscalere[.]com\ -1. www.candlelightparty[.]org\ -1. candlelightparty[.]org\ -1. newapp.freshasianews[.]comIn addition, iDefense also recommends that organizations review their environments for activity related to the following hashes:\ -\ -1. cd195ee448a3657b5c2c2d13e9c7a2e2\ -1. b43ad826fe6928245d3c02b648296b43\ -1. 889a9b52566448231f112a5ce9b5dfaf\ -1. b8ec65dab97cdef3cd256cc4753f0c54\ -1. 04d83cd3813698de28cfbba326d7647c - -[analytic_story://Prohibited Traffic Allowed or Protocol Mismatch] -category = Best Practices -last_updated = 2017-09-11 -version = 1 -references = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] -maintainers = "Rico Valdez, Splunk" -spec_version = 3 -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 Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -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. - -[analytic_story://Ransomware] -category = Malware -last_updated = 2020-02-04 -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 = "David Dorsey, Splunk" -spec_version = 3 -searches = ["ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Backup Logs For Endpoint"] -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. - -[analytic_story://Router and Infrastructure Security] -category = Best Practices -last_updated = 2017-09-12 -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 = "Bhavin Patel, Splunk" -spec_version = 3 -searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] -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. - -[analytic_story://SQL Injection] -category = Adversary Tactics -last_updated = 2017-09-19 -version = 1 -references = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] -maintainers = "Bhavin Patel, Splunk" -spec_version = 3 -searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable Info"] -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. - -[analytic_story://SamSam Ransomware] -category = Malware -last_updated = 2018-12-13 -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 = "Rico Valdez, Splunk" -spec_version = 3 -searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Batch File Write to System32 - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Update Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Backup Logs For Endpoint"] -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.\ -SamSam attacks are different beasts. They have become progressively more targeted and skillful than typical ransomware attacks. First, malicious actors break into a victim's network, surveil it, then run the malware manually. The attacks are tailored to cause maximum damage and the threat actors usually demand amounts in the tens of thousands of dollars.\ -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. - -[analytic_story://Spectre And Meltdown Vulnerabilities] -category = Vulnerability -last_updated = 2018-01-08 -version = 1 -references = ["https://meltdownattack.com/"] -maintainers = "David Dorsey, Splunk" -spec_version = 3 -searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] -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. - -[analytic_story://Splunk Enterprise Vulnerability] -category = Vulnerability -last_updated = 2017-09-19 -version = 1 -references = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] -maintainers = "Bhavin Patel, Splunk" -spec_version = 3 -searches = ["ESCU - Open Redirect in Splunk Web - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] -description = Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains. -narrative = This Analytic Story is associated with CVE-2016-4859, an open-redirect vulnerability in the following versions of Splunk Enterprise:\ -\ -1. Splunk Enterprise 6.4.x, prior to 6.4.3\ -1. Splunk Enterprise 6.3.x, prior to 6.3.6\ -1. Splunk Enterprise 6.2.x, prior to 6.2.10\ -1. Splunk Enterprise 6.1.x, prior to 6.1.11\ -1. Splunk Enterprise 6.0.x, prior to 6.0.12\ -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. - -[analytic_story://Splunk Enterprise Vulnerability CVE-2018-11409] -category = Vulnerability -last_updated = 2018-06-14 -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 = "David Dorsey, Splunk" -spec_version = 3 -searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From src ip"] -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.\ -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. - -[analytic_story://Suspicious AWS EC2 Activities] -category = Cloud Security -last_updated = 2018-02-09 -version = 1 -references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] -maintainers = "Bhavin Patel, Splunk" -spec_version = 3 -searches = ["ESCU - EC2 Instance Started In Previously Unseen Region - 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 - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get EC2 Launch Details", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] -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. - -[analytic_story://Suspicious AWS Login Activities] -category = Cloud Security -last_updated = 2019-05-01 -version = 1 -references = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] -maintainers = "Bhavin Patel, Splunk" -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 - Detect new user AWS Console Login - Rule", "ESCU - AWS Investigate User Activities By ARN"] -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. - -[analytic_story://Suspicious AWS S3 Activities] -category = Cloud Security -last_updated = 2018-07-24 -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 = "Bhavin Patel, Splunk" -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 - AWS Investigate User Activities By ARN", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get Notable History", "ESCU - Investigate AWS activities via region name", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] -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. - -[analytic_story://Suspicious AWS Traffic] -category = Cloud Security -last_updated = 2018-05-07 -version = 1 -references = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] -maintainers = "Bhavin Patel, Splunk" -spec_version = 3 -searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network ACL Details from ID", "ESCU - Get User Information from Identity Table"] -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.\ - 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. - -[analytic_story://Suspicious Command-Line Executions] -category = Adversary Tactics -last_updated = 2020-02-03 -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 = "Bhavin Patel, Splunk" -spec_version = 3 -searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -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. - -[analytic_story://Suspicious DNS Traffic] -category = Adversary Tactics -last_updated = 2017-09-18 -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 = "Rico Valdez, Splunk" -spec_version = 3 -searches = ["ESCU - Excessive DNS Failures - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -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. - -[analytic_story://Suspicious Emails] -category = Adversary Tactics -last_updated = 2020-01-27 -version = 1 -references = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] -maintainers = "Bhavin Patel, Splunk" -spec_version = 3 -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 Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get User Information from Identity Table", "ESCU - Get Email Info"] -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: \ -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. - -[analytic_story://Suspicious MSHTA Activity] -category = Adversary Tactics -last_updated = 2020-02-03 -version = 1 -references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] -maintainers = "Bhavin Patel, Splunk" -spec_version = 3 -searches = ["ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -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 white-listing solutions via the mshta.exe process, which executes Microsoft HTML applications with the .hta suffix. In these cases, attackers use the trusted Windows utility to eproxy execution of malicious files, whether an .hta application, javascript, or VBScript.\ -One example of a notable mshta.exe attack was the Kovter malware (https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5) that was implicated in ransomware and click-fraud attacks. Kovter utilized .hta to execute a series of javascript commands, each progressively more dangerous. According to the Mitre Parternship Network (https://attack.mitre.org/wiki/Technique/T1170), FIN7 has leveraged mshta.exe, as has the MuddyWater group, who used it to execute its POWERSTATS payload (which then used the utility to execute additional payloads).\ -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. - -[analytic_story://Suspicious Okta Activity] -category = Adversary Tactics -last_updated = 2020-04-02 -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 = "Rico Valdez, Splunk" -spec_version = 3 -searches = ["ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by IP Address"] -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. \ -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. - -[analytic_story://Suspicious WMI Use] -category = Adversary Tactics -last_updated = 2018-10-23 -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 = "Rico Valdez, Splunk" -spec_version = 3 -searches = ["ESCU - Script Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - WMI Temporary Event Subscription - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Process Execution via WMI - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -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.\ -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. - -[analytic_story://Suspicious Windows Registry Activities] -category = Adversary Tactics -last_updated = 2018-05-31 -version = 1 -references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] -maintainers = "Bhavin Patel, Splunk" -spec_version = 3 -searches = ["ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -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.\ - The searches in this story are designed to help you detect behaviors associated with manipulation of the Windows registry. - -[analytic_story://Unusual AWS EC2 Modifications] -category = Cloud Security -last_updated = 2018-04-09 -version = 1 -references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] -maintainers = "David Dorsey, Splunk" -spec_version = 3 -searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN"] -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. - -[analytic_story://Unusual Processes] -category = Malware -last_updated = 2020-02-04 -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 = "Bhavin Patel, Splunk" -spec_version = 3 -searches = ["ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -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.\ -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. - -[analytic_story://Use of Cleartext Protocols] -category = Best Practices -last_updated = 2017-09-15 -version = 1 -references = ["https://www.monkey.org/~dugsong/dsniff/"] -maintainers = "Bhavin Patel, Splunk" -spec_version = 3 -searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] -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. - -[analytic_story://Web Fraud Detection] -category = Abuse -last_updated = 2018-10-08 -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 = "Jim Apger, Splunk" -spec_version = 3 -searches = ["ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Get Web Session Information via session id", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Notable Info"] -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.\ -hen developing a strategy for preventing fraud in your environment, its important to look across all of your web services for evidence that attackers are abusing enterprise resources to enumerate systems, harvest data for secondary fraudulent activity, or abuse terms of service.This Analytic Story looks for evidence of common Internet attack techniques that could be indicative of web fraud in your environmentincluding account harvesting, anomalous user clickspeed, and password sharing across accounts, to name just a few.\ -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. - -[analytic_story://Windows Defense Evasion Tactics] -category = Adversary Tactics -last_updated = 2018-05-31 -version = 1 -references = ["https://attack.mitre.org/wiki/Defense_Evasion"] -maintainers = "David Dorsey, Splunk" -spec_version = 3 -searches = ["ESCU - Suspicious Reg exe Process - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -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. - -[analytic_story://Windows File Extension and Association Abuse] -category = Malware -last_updated = 2018-01-26 -version = 1 -references = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] -maintainers = "Rico Valdez, Splunk" -spec_version = 3 -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 Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -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. \ - 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. - -[analytic_story://Windows Log Manipulation] -category = Adversary Tactics -last_updated = 2017-09-12 -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 = "Rico Valdez, Splunk" -spec_version = 3 -searches = ["ESCU - Windows Event Log Cleared - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -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). - -[analytic_story://Windows Persistence Techniques] -category = Adversary Tactics -last_updated = 2018-05-31 -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 = "Bhavin Patel, Splunk" -spec_version = 3 -searches = ["ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -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. - -[analytic_story://Windows Privilege Escalation] -category = Adversary Tactics -last_updated = 2020-02-04 -version = 2 -references = ["https://attack.mitre.org/tactics/TA0004/"] -maintainers = "David Dorsey, Splunk" -spec_version = 3 -searches = ["ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -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. - -[analytic_story://Windows Service Abuse] -category = Malware -last_updated = 2017-11-02 -version = 3 -references = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] -maintainers = "Rico Valdez, Splunk" -spec_version = 3 -searches = ["ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info"] -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. - -### END STORIES ### - -### DETECTIONS ### - -[savedsearch://ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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." -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. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. -annotations = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -known_false_positives = This is a strictly behavioral search, so we define "false positive" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching within, plus what is stored in the cache feature. But while there are really no "false positives" in a traditional sense, there is definitely lots of noise.\ - This search will fire any time a new city is seen in the **GeoIP** database for any kind of provisioning activity. If you typically do all provisioning from tools inside of your city, there should be few false positives. If you are located in countries where the free version of **MaxMind GeoIP** that ships by default with Splunk has weak resolution (particularly small countries in less economically powerful regions), this may be much less valuable to you. -providing_technologies = none - -[savedsearch://ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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." -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. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. -annotations = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -known_false_positives = This is a strictly behavioral search, so we define "false positive" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching over plus what is stored in the cache feature. But while there are really no "false positives" in a traditional sense, there is definitely lots of noise.\ - This search will fire any time a new country is seen in the **GeoIP** database for any kind of provisioning activity. If you typically do all provisioning from tools inside of your country, there should be few false positives. If you are located in countries where the free version of **MaxMind GeoIP** that ships by default with Splunk has weak resolution (particularly small countries in less economically powerful regions), this may be much less valuable to you. -providing_technologies = none - -[savedsearch://ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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." -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. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. -annotations = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -known_false_positives = This is a strictly behavioral search, so we define "false positive" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching within, plus what is stored in the cache feature. But while there are really no "false positives" in a traditional sense, there is definitely lots of noise.\ - This search will fire any time a new IP address is seen in the **GeoIP** database for any kind of provisioning activity. If you typically do all provisioning from tools inside of your country, there should be few false positives. If you are located in countries where the free version of **MaxMind GeoIP** that ships by default with Splunk has weak resolution (particularly small countries in less economically powerful regions), this may be much less valuable to you. -providing_technologies = none - -[savedsearch://ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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." -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. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. -annotations = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -known_false_positives = This is a strictly behavioral search, so we define "false positive" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching within, plus what is stored in the cache feature. But while there are really no "false positives" in a traditional sense, there is definitely lots of noise.\ - This search will fire any time a new region is seen in the **GeoIP** database for any kind of provisioning activity. If you typically do all provisioning from tools inside of your region, there should be few false positives. If you are located in regions where the free version of **MaxMind GeoIP** that ships by default with Splunk has weak resolution (particularly small countries in less economically powerful regions), this may be much less valuable to you. -providing_technologies = none - -[savedsearch://ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for AssumeRole events where an IAM role in a different account is requested for the first time. -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. Run the `Previously Seen AWS Cross Account Activity` support search only once to create the baseline of previously seen cross account activity. Thanks to Pablo Vega at Recurly for suggesting improvements to the search. -annotations = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.AC", "PR.DS", "DE.AE"]} -known_false_positives = Using multiple AWS accounts and roles is perfectly valid behavior. It's suspicious when an account requests privileges of an account it hasn't before. You should validate with the account owner that this is a legitimate request. -providing_technologies = none - -[savedsearch://ESCU - AWS Network Access Control List Created with All Open Ports - Rule] -type = detection -asset_type = -confidence = medium -explanation = The search looks for CloudTrail events to detect if any network ACLs were created with all the ports open to a specified CIDR. -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, and configure your CloudTrail inputs. -annotations = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} -known_false_positives = It's possible that an admin has created this ACL with all ports open for some legitimate purpose however, this should be scoped and not allowed in production environment. -providing_technologies = none - -[savedsearch://ESCU - AWS Network Access Control List Deleted - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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 AWS 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 CloudTrail logs to detect users deleting network ACLs. -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. -annotations = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} -known_false_positives = It's possible that a user has legitimately deleted a network ACL. -providing_technologies = none - -[savedsearch://ESCU - Abnormally High AWS Instances Launched by User - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for CloudTrail events where a user successfully launches an abnormally high number of 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. The threshold value should be tuned to your environment. -annotations = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} -known_false_positives = Many service accounts configured within an AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify if this search alerted on a human user. -providing_technologies = none - -[savedsearch://ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for CloudTrail events where a user successfully launches an abnormally high number of 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. The threshold value should be tuned to your environment. -annotations = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} -known_false_positives = Many service accounts configured within an AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify if this search alerted on a human user. -providing_technologies = none - -[savedsearch://ESCU - Abnormally High AWS Instances Terminated by User - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for CloudTrail events where an abnormally high number of instances were successfully terminated by a user in a 10-minute 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. -annotations = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} -known_false_positives = Many service accounts configured with your AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify whether this search alerted on a human user. -providing_technologies = none - -[savedsearch://ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for CloudTrail events where a user successfully terminates an abnormally high number of 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. The threshold value should be tuned to your environment. -annotations = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} -known_false_positives = Many service accounts configured within an AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify if this search alerted on a human user. -providing_technologies = none - -[savedsearch://ESCU - Access LSASS Memory for Dump Creation - Rule] -type = detection -asset_type = -confidence = medium -explanation = Detect memory dumping of the LSASS process. -how_to_implement = This search requires Sysmon Logs and a Sysmon configuration, which includes EventCode 10 for lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon 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. -annotations = {"cis20": ["CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} -known_false_positives = Administrators can create memory dumps for debugging purposes, but memory dumps of the LSASS process would be unusual. -providing_technologies = none - -[savedsearch://ESCU - Amazon EKS Kubernetes Pod scan detection - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search provides detection information on unauthenticated requests against Kubernetes' Pods API -how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on forAWS (version 4.4.0 or later), then configure your AWS CloudWatch EKS Logs.Please also customize the `kubernetes_pods_aws_scan_fingerprint_detection` macro to filter out the false positives. -annotations = {"kill_chain_phases": ["Reconnaissance"]} -known_false_positives = Not all unauthenticated requests are malicious, but frequency, UA and source IPs and direct request to API provide context. -providing_technologies = none - -[savedsearch://ESCU - Amazon EKS Kubernetes cluster scan detection - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster in AWS -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 CloudWatch EKS Logs inputs. -annotations = {"kill_chain_phases": ["Reconnaissance"]} -known_false_positives = Not all unauthenticated requests are malicious, but frequency, UA and source IPs will provide context. -providing_technologies = none - -[savedsearch://ESCU - Attempt To Add Certificate To Untrusted Store - Rule] -type = detection -asset_type = -confidence = medium -explanation = Attempt to add a certificate to the untrusted certificate store -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1089"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -known_false_positives = There may be legitimate reasons for administrators to add a certificate to the untrusted certificate store. In such cases, this will typically be done on a large number of systems. -providing_technologies = none - -[savedsearch://ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule] -type = detection -asset_type = -confidence = medium -explanation = Monitor for changes of the ExecutionPolicy in the registry to the values "unrestricted" or "bypass," which allows the execution of malicious scripts. -how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Registry node. You must also be ingesting logs with the fields registry_path, registry_key_name, and registry_value_name from your endpoints. -annotations = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["DE.CM"]} -known_false_positives = Administrators may attempt to change the default execution policy on a system for a variety of reasons. However, setting the policy to "unrestricted" or "bypass" as this search is designed to identify, would be unusual. Hits should be reviewed and investigated as appropriate. -providing_technologies = none - -[savedsearch://ESCU - Attempt To Stop Security Service - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for attempts to stop security-related services on the endpoint. -how_to_implement = You must be ingesting data that records the file-system 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. The search is shipped with a lookup file, `security_services.csv`, that can be edited to update the list of services to monitor. This lookup file can be edited directly where it lives in `$SPLUNK_HOME/etc/apps/DA-ESS-ContentUpdate/lookups`, or via the Splunk console. You should add the names of services an attacker might use on the command line and surround with asterisks (*****), so that they work properly when searching the command line. The file should be updated with the names of any services you would like to monitor for attempts to stop the service., -annotations = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1089"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -known_false_positives = None identified. Attempts to disable security-related services should be identified and understood. -providing_technologies = none - -[savedsearch://ESCU - Attempted Credential Dump From Registry via Reg exe - Rule] -type = detection -asset_type = -confidence = medium -explanation = Monitor for execution of reg.exe with parameters specifying an export of keys that contain hashed credentials that attackers may try to crack offline. -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. -annotations = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} -known_false_positives = None identified. -providing_technologies = none - -[savedsearch://ESCU - Batch File Write to System32 - Rule] -type = detection -asset_type = -confidence = medium -explanation = The search looks for a batch file (.bat) written to the Windows system directory tree. -how_to_implement = You must be ingesting data that records the file-system 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 = {"cis20": ["CIS 8"], "kill_chain_phases": ["Delivery"], "nist": ["PR.PT", "DE.CM"]} -known_false_positives = It is possible for this search to generate a notable event for a batch file write to a path that includes the string "system32", but is not the actual Windows system directory. As such, you should confirm the path of the batch file identified by the search. In addition, a false positive may be generated by an administrator copying a legitimate batch file in this directory tree. You should confirm that the activity is legitimate and modify the search to add exclusions, as necessary. -providing_technologies = none - -[savedsearch://ESCU - Child Processes of Spoolsv exe - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -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. Update the `children_of_spoolsv_filter` macro to filter out legitimate child processes spawned by spoolsv.exe. -annotations = {"cis20": ["CIS 5", "CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1068"], "nist": ["PR.AC", "PR.PT", "DE.CM"]} -known_false_positives = Some legitimate printer-related processes may show up as children of spoolsv.exe. You should confirm that any activity as legitimate and may be added as exclusions in the search. -providing_technologies = none - -[savedsearch://ESCU - Clients Connecting to Multiple DNS Servers - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -how_to_implement = This search requires that DNS data is being ingested and populating the `Network_Resolution` data model. This data can come from DNS logs or from solutions that parse network traffic for this data, such as Splunk Stream or Bro.\ -This search produces fields (`dest_count`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** Distinct DNS Connections, **Field:** dest_count\ -Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -annotations = {"cis20": ["CIS 9", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048"], "nist": ["PR.PT", "DE.AE", "PR.DS"]} -known_false_positives = It's possible that an enterprise has more than five DNS servers that are configured in a round-robin rotation. Please customize the search, as appropriate. -providing_technologies = none - -[savedsearch://ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for cloud compute instances created by users who have not created them before. -how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the "Previously Seen Cloud Compute Creations By User" support search to create of baseline of previously seen users. -annotations = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -known_false_positives = It's possible that a user will start to create compute instances for the first time, for any number of reasons. Verify with the user launching instances that this is the intended behavior. -providing_technologies = none - -[savedsearch://ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for cloud compute instances being created with previously unseen image IDs. -how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the "Previously Seen Cloud Compute Images" support search to create a baseline of previously seen images. -annotations = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -known_false_positives = After a new image is created, the first systems created with that image will cause this alert to fire. Verify that the image being used was created by a legitimate user. -providing_technologies = none - -[savedsearch://ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule] -type = detection -asset_type = -confidence = medium -explanation = Find EC2 instances being created with previously unseen instance types. -how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the " Previously Seen Cloud Compute Instance Types" support search to create a baseline of previously seen regions. -annotations = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -known_false_positives = It is possible that an admin will create a new system using a new instance type that has never been used before. Verify with the creator that they intended to create the system with the new instance type. -providing_technologies = none - -[savedsearch://ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks at cloud-infrastructure events where an instance is created in any region within the last hour and then compares it to a lookup file of previously seen regions where instances have been created. -how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the \"Previously Seen Cloud Compute Instance Types\" support search to create a baseline of previously seen regions. -annotations = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} -known_false_positives = It's possible that a user has unknowingly started an instance in a new region. Please verify that this activity is legitimate. -providing_technologies = none - -[savedsearch://ESCU - Common Ransomware Extensions - Rule] -type = detection -asset_type = -confidence = medium -explanation = The search looks for file modifications with extensions commonly used by Ransomware -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.\ -This search produces fields (`query`,`query_length`,`count`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** Name, **Field:** Name\ -1. \ -1. **Label:** File Extension, **Field:** file_extension\ -Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} -known_false_positives = It is possible for a legitimate file with these extensions to be created. If this is a true ransomware attack, there will be a large number of files created with these extensions. -providing_technologies = none - -[savedsearch://ESCU - Common Ransomware Notes - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -how_to_implement = You must be ingesting data that records file-system activity from your hosts to populate the Endpoint Filesystem data-model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file-system reads and writes. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} -known_false_positives = It's possible that a legitimate file could be created with the same name used by ransomware note files. -providing_technologies = none - -[savedsearch://ESCU - Create Remote Thread into LSASS - Rule] -type = detection -asset_type = -confidence = medium -explanation = Detect remote thread creation into LSASS consistent with credential dumping. -how_to_implement = This search needs Sysmon Logs with a Sysmon configuration, which includes EventCode 8 with lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon 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. -annotations = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} -known_false_positives = Other tools can access LSASS for legitimate reasons and generate an event. In these cases, tweaking the search may help eliminate noise. -providing_technologies = none - -[savedsearch://ESCU - Create local admin accounts using net exe - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for the creation of local administrator accounts using net.exe. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} -known_false_positives = Administrators often leverage net.exe to create admin accounts. -providing_technologies = none - -[savedsearch://ESCU - Create or delete windows shares using net exe - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for the creation or deletion of hidden shares using net.exe. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} -known_false_positives = Administrators often leverage net.exe to create or delete network shares. You should verify that the activity was intentional and is legitimate. -providing_technologies = none - -[savedsearch://ESCU - Creation of Shadow Copy - Rule] -type = detection -asset_type = -confidence = medium -explanation = Monitor for signs that Ntdsutil, Vssadmin, or Wmic has been used to create a shadow copy. -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. -annotations = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} -known_false_positives = Legtimate administrator usage of Ntdsutil, Vssadmin, or Wmic will create false positives. -providing_technologies = none - -[savedsearch://ESCU - Creation of Shadow Copy with wmic and powershell - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search detects the use of wmic and Powershell to create a shadow copy. -how_to_implement = You must enable Powershell scriptblock logging in order to detect this attack.This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon 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. -annotations = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} -known_false_positives = Legtimate administrator usage of wmic to create a shadow copy. -providing_technologies = none - -[savedsearch://ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search detects credential dumping using copy command from a shadow copy. -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. -annotations = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} -known_false_positives = unknown -providing_technologies = none - -[savedsearch://ESCU - Credential Dumping via Symlink to Shadow Copy - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search detects the creation of a symlink to a shadow copy. -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. -annotations = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} -known_false_positives = unknown -providing_technologies = none - -[savedsearch://ESCU - DNS Query Length Outliers - MLTK - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search allows you to identify DNS requests that are unusually large for the record type being requested in your environment. -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, the Machine Learning Toolkit (MLTK) version 4.2 or greater must be installed on your search heads, along with any required dependencies. Finally, the support search "Baseline of DNS Query Length - MLTK" must be executed before this detection search, because it builds a machine-learning (ML) model over the historical data used by this search. It is important that this search is run in the same app context as the associated support search, so that the model created by the support search is available for use. You should periodically re-run the support search to rebuild the model with the latest data available in your environment.\ -This search produces fields (`query`,`query_length`,`count`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** DNS Query, **Field:** query\ -1. \ -1. **Label:** DNS Query Length, **Field:** query_length\ -1. \ -1. **Label:** Number of events, **Field:** count\ -Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -annotations = {"cis20": ["CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1043"], "nist": ["PR.PT", "DE.AE", "DE.CM"]} -known_false_positives = If you are seeing more results than desired, you may consider reducing the value for threshold in the search. You should also periodically re-run the support search to re-build the ML model on the latest data. -providing_technologies = none - -[savedsearch://ESCU - DNS Query Length With High Standard Deviation - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. -annotations = {"cis20": ["CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1043"], "nist": ["PR.PT", "DE.AE", "DE.CM"]} -known_false_positives = It's possible there can be long domain names that are legitimate. -providing_technologies = none - -[savedsearch://ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -how_to_implement = To successfully implement this search you will need to ensure that DNS data is populating the Network_Resolution data model. It also requires that your DNS servers are identified correctly in the Assets and Identity table of Enterprise Security. -annotations = {"cis20": ["CIS 1", "CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"]} -known_false_positives = Legitimate DNS activity can be detected in this search. Investigate, verify and update the list of authorized DNS servers as appropriate. -providing_technologies = none - -[savedsearch://ESCU - DNS record changed - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -how_to_implement = To successfully implement this search you will need to ensure that DNS data is populating the `Network_Resolution` data model. It also requires that the `discover_dns_record` lookup table be populated by the included support search "Discover DNS record". \ - **Splunk>Phantom Playbook Integration**\ -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/`).\ - -annotations = {"cis20": ["CIS 1", "CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"]} -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 = none - -[savedsearch://ESCU - Deleting Shadow Copies - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -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. -annotations = {"cis20": ["CIS 8", "CIS 10"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -known_false_positives = vssadmin.exe and wmic.exe are standard applications shipped with modern versions of windows. They may be used by administrators to legitimately delete old backup copies, although this is typically rare. -providing_technologies = none - -[savedsearch://ESCU - Detect API activity from users without MFA - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -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. Leverage the support search `Create a list of approved AWS service accounts`: run it once every 30 days to create a list of service accounts and validate them.\ -This search produces fields (`eventName`,`userIdentity.type`,`userIdentity.arn`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** AWS Event Name, **Field:** eventName\ -1. \ -1. **Label:** AWS User ARN, **Field:** userIdentity.arn\ -1. \ -1. **Label:** AWS User Type, **Field:** userIdentity.type\ -Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -annotations = {"cis20": ["CIS 16"], "nist": ["DE.DP", "PR.AC"]} -known_false_positives = Many service accounts configured within an AWS infrastructure do not have multi factor authentication enabled. Please ignore the service accounts, if triggered and instead add them to the aws_service_accounts.csv file to fine tune the detection. It is also possible that the search detects users in your environment using Single Sign-On systems, since the MFA is not handled by AWS. -providing_technologies = none - -[savedsearch://ESCU - Detect AWS API Activities From Unapproved Accounts - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -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. You must also populate the `identity_lookup_expanded` lookup shipped with the Asset and Identity framework to be able to look up users in your identity table in Enterprise Security (ES). Leverage the support search called "Create a list of approved AWS service accounts": run it once every 30 days to create and validate a list of service accounts.\ -This search produces fields (`eventName`,`firstTime`,`lastTime`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** AWS Event Name, **Field:** eventName\ -1. \ -1. **Label:** First Time, **Field:** firstTime\ -1. \ -1. **Label:** Last Time, **Field:** lastTime\ -Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -annotations = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC", "ID.AM"]} -known_false_positives = It's likely that you'll find activity detected by users/service accounts that are not listed in the `identity_lookup_expanded` or ` aws_service_accounts.csv` file. If the user is a legitimate service account, update the `aws_service_accounts.csv` table with that entry. -providing_technologies = none - -[savedsearch://ESCU - Detect AWS Console Login by User from New City - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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 -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. Run the "Previously seen users in CloudTrail" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run "Update previously seen users in CloudTrail" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines. -annotations = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} -known_false_positives = When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate. -providing_technologies = none - -[savedsearch://ESCU - Detect AWS Console Login by User from New Country - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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 -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. Run the "Previously seen users in CloudTrail" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run "Update previously seen users in CloudTrail" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines. -annotations = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} -known_false_positives = When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate. -providing_technologies = none - -[savedsearch://ESCU - Detect AWS Console Login by User from New Region - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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 -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. Run the "Previously seen users in CloudTrail" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run "Update previously seen users in CloudTrail" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines. -annotations = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} -known_false_positives = When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate. -providing_technologies = none - -[savedsearch://ESCU - Detect Activity Related to Pass the Hash Attacks - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for specific authentication events from the Windows Security Event logs to detect potential attempts at using the Pass-the-Hash technique. -how_to_implement = To successfully implement this search, you must ingest your Windows Security Event logs and leverage the latest TA for Windows. -annotations = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1075"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} -known_false_positives = Legitimate logon activity by authorized NTLM systems may be detected by this search. Please investigate as appropriate. -providing_technologies = none - -[savedsearch://ESCU - Detect Credential Dumping through LSASS access - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for reading lsass memory consistent with credential dumping. -how_to_implement = This search needs Sysmon Logs and a sysmon configuration, which includes EventCode 10 with lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon 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. -annotations = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["PR.IP", "PR.AC", "DE.CM"]} -known_false_positives = The activity may be legitimate. Other tools can access lsass for legitimate reasons, and it's possible this event could be generated in those cases. In these cases, false positives should be fairly obvious and you may need to tweak the search to eliminate noise. -providing_technologies = none - -[savedsearch://ESCU - Detect DNS requests to Phishing Sites leveraging EvilGinx2 - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for DNS requests for phishing domains that are leveraging EvilGinx tools to mimic websites. -how_to_implement = You need to ingest data from your DNS logs in the Network_Resolution datamodel. Specifically you must ingest the domain that is being queried and the IP of the host originating the request. Ideally, you should also be ingesting the answer to the query and the query type. This approach allows you to also create your own localized passive DNS capability which can aid you in future investigations. You will have to add legitimate domain names to the `legit_domains.csv` file shipped with the app. \ - **Splunk>Phantom Playbook Integration**\ -If Splunk>Phantom is also configured in your environment, a Playbook called `Lets Encrypt Domain Investigate` can be configured to run when any results are found by this detection search. 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/lets-encrypt-domain-investigate/`).\ - -annotations = {"cis20": ["CIS 8", "CIS 7"], "kill_chain_phases": ["Delivery", "Command and Control"], "mitre_attack": ["T1192"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"]} -known_false_positives = If a known good domain is not listed in the legit_domains.csv file, then the search could give you false postives. Please update that lookup file to filter out DNS requests to legitimate domains. -providing_technologies = none - -[savedsearch://ESCU - Detect Excessive Account Lockouts From Endpoint - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search identifies endpoints that have caused a relatively high number of account lockouts in a short period. -how_to_implement = You must ingest your Windows security event logs in the `Change` datamodel under the nodename is `Account_Management`, for this search to execute successfully. Please consider updating the cron schedule and the count of lockouts you want to monitor, according to your environment. \ - **Splunk>Phantom Playbook Integration**\ -If Splunk>Phantom is also configured in your environment, a Playbook called "Excessive Account Lockouts Enrichment and Response" can be configured to run when any results are found by this detection search. The Playbook executes the Contextual and Investigative searches in this Story, conducts additional information gathering on Windows endpoints, and takes a response action to shut down the affected endpoint. 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/4.1/playbook/excessive-account-lockouts-enrichment-and-response/`).\ - -annotations = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["PR.IP"]} -known_false_positives = It's possible that a widely used system, such as a kiosk, could cause a large number of account lockouts. -providing_technologies = none - -[savedsearch://ESCU - Detect Excessive User Account Lockouts - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search detects user accounts that have been locked out a relatively high number of times in a short period. -how_to_implement = ou must ingest your Windows security event logs in the `Change` datamodel under the nodename is `Account_Management`, for this search to execute successfully. Please consider updating the cron schedule and the count of lockouts you want to monitor, according to your environment. -annotations = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["PR.IP"]} -known_false_positives = It is possible that a legitimate user is experiencing an issue causing multiple account login failures leading to lockouts. -providing_technologies = none - -[savedsearch://ESCU - Detect Large Outbound ICMP Packets - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -how_to_implement = In order to run this search effectively, we highly recommend that you leverage the Assets and Identity framework. It is important that you have a good understanding of how your network segments are designed and that you are able to distinguish internal from external address space. Add a category named `internal` to the CIDRs that host the company's assets in the `assets_by_cidr.csv` lookup file, which is located in `$SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/`. More information on updating this lookup can be found here: https://docs.splunk.com/Documentation/ES/5.0.0/Admin/Addassetandidentitydata. This search also requires you to be ingesting your network traffic and populating the Network_Traffic data model -annotations = {"cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1095"], "nist": ["DE.AE"]} -known_false_positives = ICMP packets are used in a variety of ways to help troubleshoot networking issues and ensure the proper flow of traffic. As such, it is possible that a large ICMP packet could be perfectly legitimate. If large ICMP packets are associated with command and control traffic, there will typically be a large number of these packets observed over time. If the search is providing a large number of false positives, you can modify the search to adjust the byte threshold or whitelist specific IP addresses, as necessary. -providing_technologies = none - -[savedsearch://ESCU - Detect Long DNS TXT Record Response - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -how_to_implement = To successfully implement this search you need to ingest data from your DNS logs, or monitor DNS traffic using Stream, Bro or something similar. Specifically, this query requires that the DNS data model is populated with information regarding the DNS record type that is being returned as well as the data in the answer section of the protocol. -annotations = {"cis20": ["CIS 8", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1043"], "nist": ["PR.DS", "PR.PT", "DE.AE", "DE.CM"]} -known_false_positives = It's possible that legitimate TXT record responses can be long enough to trigger this search. You can modify the packet threshold for this search to help mitigate false positives. -providing_technologies = none - -[savedsearch://ESCU - Detect Mimikatz Using Loaded Images - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for reading loaded Images unique to credential dumping with Mimikatz. -how_to_implement = This search needs Sysmon Logs and a sysmon configuration, which includes EventCode 7 with powershell.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon 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. -annotations = {"cis20": ["CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.AE", "DE.CM"]} -known_false_positives = Other tools can import the same DLLs. These tools should be part of a whtelist. -providing_technologies = none - -[savedsearch://ESCU - Detect Mimikatz Via PowerShell And EventCode 4703 - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for PowerShell requesting privileges consistent with credential dumping. -how_to_implement = You must be ingesting Windows Security logs. You must also enable the account change auditing here: http://docs.splunk.com/Documentation/Splunk/7.0.2/Data/MonitorWindowseventlogdata. Additionally, this search requires you to enable your Group Management Audit Logs in your Local Windows Security Policy and to be ingesting those logs. More information on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/. Finally, please make sure that the local administrator group name is "Administrators" to be able to look for the right group membership changes. -annotations = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["PR.IP", "PR.AC", "DE.CM"]} -known_false_positives = The activity may be legitimate. PowerShell is often used by administrators to perform various tasks, and it's possible this event could be generated in those cases. In these cases, false positives should be fairly obvious and you may need to tweak the search to eliminate noise. -providing_technologies = none - -[savedsearch://ESCU - Detect New Local Admin account - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for newly created accounts that have been elevated to local administrators. -how_to_implement = You must be ingesting Windows Security logs. You must also enable the account change auditing here:http://docs.splunk.com/Documentation/Splunk/7.0.2/Data/MonitorWindowseventlogdata. Additionally, this search requires you to enable your Group Management Audit Logs in your Local Windows Security Policy and to be ingesting those logs. More information on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/. Finally, please make sure that the local administrator group name is "Administrators" to be able to look for the right group membership changes.\ -This search produces fields (`Security_ID`,`Group_Name`,`Message`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** Security ID, **Field:** Security_ID\ -1. \ -1. **Label:** Group Name, **Field:** Group_Name\ -1. \ -1. **Label:** Message, **Field:** Message\ -Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -annotations = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1078"], "nist": ["PR.AC", "DE.CM"]} -known_false_positives = The activity may be legitimate. For this reason, it's best to verify the account with an administrator and ask whether there was a valid service request for the account creation. If your local administrator group name is not "Administrators", this search may generate an excessive number of false positives -providing_technologies = none - -[savedsearch://ESCU - Detect New Login Attempts to Routers - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -how_to_implement = To successfully implement this search, you must ensure the network router devices are categorized as "router" in the Assets and identity table. You must also populate the Authentication data model with logs related to users authenticating to routing infrastructure. -annotations = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "PR.AC", "PR.IP"]} -known_false_positives = Legitimate router connections may appear as new connections -providing_technologies = none - -[savedsearch://ESCU - Detect New Open S3 buckets - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for CloudTrail events where a user has created an open/public S3 bucket. -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), and then configure your CloudTrail inputs. The threshold value should be tuned to your environment. -annotations = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS", "PR.AC", "DE.CM"]} -known_false_positives = While this search has no known false positives, it is possible that an AWS admin has legitimately created a public bucket for a specific purpose. That said, AWS strongly advises against granting full control to the "All Users" group. -providing_technologies = none - -[savedsearch://ESCU - Detect Oulook exe writing a zip file - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for execution of process `outlook.exe` where the process is writing a `.zip` file to the disk. -how_to_implement = You must be ingesting data that records filesystem and process activity from your hosts to populate the Endpoint data model. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. -annotations = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1193"], "nist": ["ID.AM", "PR.DS"]} -known_false_positives = It is not uncommon for outlook to write legitimate zip files to the disk. -providing_technologies = none - -[savedsearch://ESCU - Detect Outbound SMB Traffic - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -how_to_implement = In order to run this search effectively, we highly recommend that you leverage the Assets and Identity framework. It is important that you have good understanding of how your network segments are designed, and be able to distinguish internal from external address space. Add a category named `internal` to the CIDRs that host the company's assets in `assets_by_cidr.csv` lookup file, which is located in `$SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/`. More information on updating this lookup can be found here: https://docs.splunk.com/Documentation/ES/5.0.0/Admin/Addassetandidentitydata. This search also requires you to be ingesting your network traffic and populating the Network_Traffic data model -annotations = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -known_false_positives = It is likely that the outbound Server Message Block (SMB) traffic is legitimate, if the company's internal networks are not well-defined in the Assets and Identity Framework. Categorize the internal CIDR blocks as `internal` in the lookup file to avoid creating notable events for traffic destined to those CIDR blocks. Any other network connection that is going out to the Internet should be investigated and blocked. Best practices suggest preventing external communications of all SMB versions and related protocols at the network boundary. -providing_technologies = none - -[savedsearch://ESCU - Detect Path Interception By Creation Of program exe - Rule] -type = detection -asset_type = -confidence = medium -explanation = The search is looking for the creation of program.exe in the C: drive. The creation of this file in that location may be driven by a motive to perform path interception. -how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file system reads and writes. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} -known_false_positives = It is unlikely that a normal user may create and place this file in the C: drive. Confirm with the user. -providing_technologies = none - -[savedsearch://ESCU - Detect Prohibited Applications Spawning cmd exe - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -how_to_implement = You must be ingesting data that records process activity from your hosts and populates the Endpoint data model with the resultant dataset. This search includes a lookup file, `prohibited_apps_launching_cmd.csv`, that contains a list of processes that should not be spawning cmd.exe. You can modify this lookup to better suit your environment. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} -known_false_positives = There are circumstances where an application may legitimately execute and interact with the Windows command-line interface. Investigate and modify the lookup file, as appropriate. -providing_technologies = none - -[savedsearch://ESCU - Detect PsExec With accepteula Flag - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} -known_false_positives = Administrators can leverage PsExec for accessing remote systems and might pass `accepteula` as an argument if they are running this tool for the first time. However, it is not likely that you'd see multiple occurrences of this event on a machine -providing_technologies = none - -[savedsearch://ESCU - Detect Rare Executables - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search will return a table of rare processes, the names of the systems running them, and the users who initiated each process. -how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts and populating the endpoint data model with the resultant dataset. The macro `filter_rare_process_whitelist` searches two lookup files to whitelist your processes. These consist of `rare_process_whitelist_default.csv` and `rare_process_whitelist_local.csv`. To add your own processes to the whitelist, add them to `rare_process_whitelist_local.csv`. If you wish to remove an entry from the default lookup file, you will have to modify the macro itself to set the whitelist value for that process to false. You can modify the limit parameter and search scheduling to better suit your environment. -annotations = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.PT", "PR.DS", "DE.CM"]} -known_false_positives = Some legitimate processes may be only rarely executed in your environment. As these are identified, update `rare_process_whitelist_local.csv` to filter them out of your search results. -providing_technologies = none - -[savedsearch://ESCU - Detect S3 access from a new IP - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks at S3 bucket-access logs and detects new or previously unseen remote IP addresses that have successfully accessed an S3 bucket. -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. This search works best when you run the "Previously Seen S3 Bucket Access by Remote IP" support search once to create a history of previously seen remote IPs and bucket names. -annotations = {"cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS", "PR.AC", "DE.CM"]} -known_false_positives = S3 buckets can be accessed from any IP, as long as it can make a successful connection. This will be a false postive, since the search is looking for a new IP within the past hour -providing_technologies = none - -[savedsearch://ESCU - Detect Spike in AWS API Activity - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -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. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike.\ -This search produces fields (`eventName`,`numberOfApiCalls`,`uniqueApisCalled`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** AWS Event Name, **Field:** eventName\ -1. \ -1. **Label:** Number of API Calls, **Field:** numberOfApiCalls\ -1. \ -1. **Label:** Unique API Calls, **Field:** uniqueApisCalled\ -Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -annotations = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC"]} -known_false_positives = -providing_technologies = none - -[savedsearch://ESCU - Detect Spike in Network ACL Activity - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search will detect users creating spikes in API activity related to network access-control lists (ACLs)in your AWS environment. -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. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike. This search works best when you run the "Baseline of Network ACL Activity by ARN" support search once to create a lookup file of previously seen Network ACL Activity. To add or remove API event names related to network ACLs, edit the macro `network_acl_events`. -annotations = {"cis20": ["CIS 12", "CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC"]} -known_false_positives = The false-positive rate may vary based on the values of`dataPointThreshold` and `deviationThreshold`. Please modify this according the your environment. -providing_technologies = none - -[savedsearch://ESCU - Detect Spike in S3 Bucket deletion - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -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. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike. This search works best when you run the "Baseline of S3 Bucket deletion activity by ARN" support search once to create a baseline of previously seen S3 bucket-deletion activity. -annotations = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC"]} -known_false_positives = Based on the values of`dataPointThreshold` and `deviationThreshold`, the false positive rate may vary. Please modify this according the your environment. -providing_technologies = none - -[savedsearch://ESCU - Detect Spike in Security Group Activity - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -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. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike.This search works best when you run the "Baseline of Security Group Activity by ARN" support search once to create a history of previously seen Security Group Activity. To add or remove API event names for security groups, edit the macro `security_group_api_calls`. -annotations = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC"]} -known_false_positives = Based on the values of`dataPointThreshold` and `deviationThreshold`, the false positive rate may vary. Please modify this according the your environment. -providing_technologies = none - -[savedsearch://ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -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. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the number of data points required to meet the definition of "spike." The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike. This search works best when you run the "Baseline of Blocked Outbound Connection" support search once to create a history of previously seen blocked outbound connections. -annotations = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "nist": ["DE.AE", "DE.CM", "PR.AC"]} -known_false_positives = The false-positive rate may vary based on the values of`dataPointThreshold` and `deviationThreshold`. Additionally, false positives may result when AWS administrators roll out policies enforcing network blocks, causing sudden increases in the number of blocked outbound connections. -providing_technologies = none - -[savedsearch://ESCU - Detect USB device insertion - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -how_to_implement = To successfully implement this search, you must ingest Windows Security Event logs and track event code 4663 and 4656. Ensure that the field from the event logs is being mapped to the result_id field in the Change_Analysis data model. To minimize the alert volume, this search leverages the Assets and Identity framework to filter out events from those assets not marked high priority in the Enterprise Security Assets and Identity Framework. -annotations = {"cis20": ["CIS 13"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "nist": ["PR.PT", "PR.DS"]} -known_false_positives = Legitimate USB activity will also be detected. Please verify and investigate as appropriate. -providing_technologies = none - -[savedsearch://ESCU - Detect Unauthorized Assets by MAC address - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -how_to_implement = This search uses the Network_Sessions data model shipped with Enterprise Security. It leverages the Assets and Identity framework to populate the assets_by_str.csv file located in SA-IdentityManagement, which will contain a list of known authorized organizational assets including their MAC addresses. Ensure that all inventoried systems have their MAC address populated. -annotations = {"cis20": ["CIS 1"], "kill_chain_phases": ["Reconnaissance", "Delivery", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"]} -known_false_positives = This search might be prone to high false positives. Please consider this when conducting analysis or investigations. Authorized devices may be detected as unauthorized. If this is the case, verify the MAC address of the system responsible for the false positive and add it to the Assets and Identity framework with the proper information. -providing_technologies = none - -[savedsearch://ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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 -how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} -known_false_positives = Some legitimate applications may exhibit this behavior. -providing_technologies = none - -[savedsearch://ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -how_to_implement = You must be ingesting data from the web server or network traffic that contains web specific information, and populating the Web data model. -annotations = {"kill_chain_phases": ["Reconnaissance"], "mitre_attack": ["T1082"]} -known_false_positives = It's possible for legitimate HTTP requests to be made to URLs containing the suspicious paths. -providing_technologies = none - -[savedsearch://ESCU - Detect hosts connecting to dynamic domain providers - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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, blacklists 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. -how_to_implement = First, you'll need to ingest data from your DNS operations. This can be done by ingesting logs from your server or data, collected passively by Splunk Stream or a similar solution. Specifically, data that contains the domain that is being queried and the IP of the host originating the request must be populating the `Network_Resolution` data model. This search also leverages a lookup file, `dynamic_dns_providers_default.csv`, which contains a non-exhaustive list of Dynamic DNS providers. Please consider updating the local lookup periodically by adding new domains to the list of `dynamic_dns_providers_local.csv`.\ -This search produces fields (query, answer, isDynDNS) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable event. To see the additional metadata, add the following fields, if not already present, to Incident Review. Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** DNS Query, **Field:** query\ -1. \ -1. **Label:** DNS Answer, **Field:** answer\ -1. \ -1. **Label:** IsDynamicDNS, **Field:** isDynDNS\ -Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -annotations = {"cis20": ["CIS 8", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "nist": ["PR.DS", "PR.PT", "DE.AE", "DE.CM"]} -known_false_positives = Some users and applications may leverage Dynamic DNS to reach out to some domains on the Internet since dynamic DNS by itself is not malicious, however this activity must be verified. -providing_technologies = none - -[savedsearch://ESCU - Detect malicious requests to exploit JBoss servers - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -how_to_implement = You must ingest data from the web server or capture network data that contains web specific information with solutions such as Bro or Splunk Stream, and populating the Web data model -annotations = {"cis20": ["CIS 12", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "PR.PT", "PR.IP", "DE.AE", "PR.MA", "DE.CM"]} -known_false_positives = No known false positives for this detection. -providing_technologies = none - -[savedsearch://ESCU - Detect mshta exe running scripts in command-line arguments - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for the execution of "mshta.exe" with command-line arguments that launch a script. 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. -how_to_implement = To successfully implement this search, you need to be ingesting logs with the process name, parent process, and command-line executions from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} -known_false_positives = Although unlikely, some legitimate applications may exhibit this behavior, triggering a false positive. -providing_technologies = none - -[savedsearch://ESCU - Detect new API calls from user roles - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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`. -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. This search works best when you run the "Previously seen API call per user roles in CloudTrail" support search once to create a history of previously seen user roles. -annotations = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -known_false_positives = It is possible that there are legitimate user roles making new or infrequently used API calls in your infrastructure, causing the search to trigger. -providing_technologies = none - -[savedsearch://ESCU - Detect new user AWS Console Login - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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 -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. Run the "Previously seen users in CloudTrail" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run "Update previously seen users in CloudTrail" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines. -annotations = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} -known_false_positives = When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate. -providing_technologies = none - -[savedsearch://ESCU - Detect processes used for System Network Configuration Discovery - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for fast execution of processes used for system network configuration discovery on the endpoint. -how_to_implement = You must be ingesting data that records registry activity from your hosts to populate the Endpoint data model in the processes node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. The data used for this search is usually generated via logs that report reads and writes to the registry or that are populated via Windows event logs, after enabling process tracking in your Windows audit settings. -annotations = {"cis20": ["CIS 2"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"]} -known_false_positives = It is uncommon for normal users to execute a series of commands used for network discovery. System administrators often use scripts to execute these commands. These can generate false positives. -providing_technologies = none - -[savedsearch://ESCU - Detect web traffic to dynamic domain providers - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for web connections to dynamic DNS providers. -how_to_implement = This search requires you to be ingesting web-traffic logs. You can obtain these logs from indexing data from a web proxy or by using a network-traffic-analysis tool, such as Bro or Splunk Stream. The web data model must contain the URL being requested, the IP address of the host initiating the request, and the destination IP. This search also leverages a lookup file, `dynamic_dns_providers_default.csv`, which contains a non-exhaustive list of dynamic DNS providers. Consider periodically updating this local lookup file with new domains.\ -This search produces fields (`isDynDNS`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** IsDynamicDNS, **Field:** isDynDNS\ -Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -annotations = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1102", "T1041"], "nist": ["PR.IP", "DE.DP"]} -known_false_positives = It is possible that list of dynamic DNS providers is outdated and/or that the URL being requested is legitimate. -providing_technologies = none - -[savedsearch://ESCU - Detection of DNS Tunnels - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -how_to_implement = To successfully implement this search, we must ensure that DNS data is being ingested and mapped to the appropriate fields in the Network_Resolution data model. Fields like src_category are automatically provided by the Assets and Identity Framework shipped with Splunk Enterprise Security. You will need to ensure you are using the Assets and Identity Framework and populating the src_category field. You will also need to enable the `cim_corporate_web_domain_search()` macro which will essentially filter out the DNS queries made to the corporate web domains to reduce alert fatigue. -annotations = {"cis20": ["CIS 13"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1043"], "nist": ["PR.PT", "PR.DS"]} -known_false_positives = It's possible that normal DNS traffic will exhibit this behavior. If an alert is generated, please investigate and validate as appropriate. The threshold can also be modified to better suit your environment. -providing_technologies = none - -[savedsearch://ESCU - Detection of tools built by NirSoft - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -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. -annotations = {"cis20": ["CIS 3"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1072", "T1087"], "nist": ["PR.IP"]} -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 = none - -[savedsearch://ESCU - Disabling Remote User Account Control - Rule] -type = detection -asset_type = -confidence = medium -explanation = The search looks for modifications to registry keys that control the enforcement of Windows User Account Control (UAC). -how_to_implement = To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report registry modifications. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1112"], "nist": ["PR.PT", "DE.CM"]} -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 = none - -[savedsearch://ESCU - Dump LSASS via comsvcs DLL - Rule] -type = detection -asset_type = -confidence = medium -explanation = Detect the usage of comsvcs.dll for dumping the lsass process. -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. -annotations = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} -known_false_positives = None identified. -providing_technologies = none - -[savedsearch://ESCU - EC2 Instance Modified With Previously Unseen User - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for EC2 instances being modified by users who have not previously modified them. -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. This search works best when you run the "Previously Seen EC2 Launches By User" support search once to create a history of previously seen ARNs. To add or remove APIs that modify an EC2 instance, edit the macro `ec2_modification_api_calls`. -annotations = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -known_false_positives = It's possible that a new user will start to modify EC2 instances when they haven't before for any number of reasons. Verify with the user that is modifying instances that this is the intended behavior. -providing_technologies = none - -[savedsearch://ESCU - EC2 Instance Started In Previously Unseen Region - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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 -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. Run the "Previously seen AWS Regions" support search only once to create of baseline of previously seen regions. -annotations = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} -known_false_positives = It's possible that a user has unknowingly started an instance in a new region. Please verify that this activity is legitimate. -providing_technologies = none - -[savedsearch://ESCU - EC2 Instance Started With Previously Unseen AMI - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for EC2 instances being created with previously unseen AMIs. -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. This search works best when you run the "Previously Seen EC2 AMIs" support search once to create a history of previously seen AMIs. -annotations = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -known_false_positives = After a new AMI is created, the first systems created with that AMI will cause this alert to fire. Verify that the AMI being used was created by a legitimate user. -providing_technologies = none - -[savedsearch://ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for EC2 instances being created with previously unseen 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. This search works best when you run the "Previously Seen EC2 Instance Types" support search once to create a history of previously seen instance types. -annotations = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -known_false_positives = It is possible that an admin will create a new system using a new instance type never used before. Verify with the creator that they intended to create the system with the new instance type. -providing_technologies = none - -[savedsearch://ESCU - EC2 Instance Started With Previously Unseen User - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for EC2 instances being created by users who have not created them before. -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. This search works best when you run the "Previously Seen EC2 Launches By User" support search once to create a history of previously seen ARNs. -annotations = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -known_false_positives = It's possible that a user will start to create EC2 instances when they haven't before for any number of reasons. Verify with the user that is launching instances that this is the intended behavior. -providing_technologies = none - -[savedsearch://ESCU - Email Attachments With Lots Of Spaces - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -how_to_implement = You need to ingest data from emails. Specifically, the sender's address and the file names of any attachments must be mapped to the Email data model. The threshold ratio is set to 10%, but this value can be configured to suit each environment. \ - **Splunk Phantom Playbook Integration**\ -If Splunk Phantom is also configured in your environment, a playbook called "Suspicious Email Attachment Investigate and Delete" can be configured to run when any results are found by this detection search. To use this integration, install the Phantom App for Splunk `https://splunkbase.splunk.com/app/3411/` and add the correct hostname to the "Phantom Instance" field in the Adaptive Response Actions when configuring this detection search. The notable event will be sent to Phantom and the playbook will gather further information about the file attachment and its network behaviors. If Phantom finds malicious behavior and an analyst approves of the results, the email will be deleted from the user's inbox. -annotations = {"cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"]} -known_false_positives = None at this time -providing_technologies = none - -[savedsearch://ESCU - Email files written outside of the Outlook directory - Rule] -type = detection -asset_type = -confidence = medium -explanation = The search looks at the change-analysis data model and detects email files created outside the normal Outlook directory. -how_to_implement = To successfully implement this search, you must be ingesting data that records the file-system activity from your hosts to populate the Endpoint.Filesystem data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or by other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file-system reads and writes. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1114"]} -known_false_positives = Administrators and users sometimes prefer backing up their email data by moving the email files into a different folder. These attempts will be detected by the search. -providing_technologies = none - -[savedsearch://ESCU - Email servers sending high volume traffic to hosts - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -how_to_implement = This search requires you to be ingesting your network traffic and populating the Network_Traffic data model. Your email servers must be categorized as "email_server" for the search to work, as well. You may need to adjust the deviation_threshold and minimum_data_samples values based on the network traffic in your environment. The "deviation_threshold" field is a multiplying factor to control how much variation you're willing to tolerate. The "minimum_data_samples" field is the minimum number of connections of data samples required for the statistic to be valid. -annotations = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1114", "T1043"], "nist": ["PR.PT", "DE.CM", "DE.AE"]} -known_false_positives = The false-positive rate will vary based on how you set the deviation_threshold and data_samples values. Our recommendation is to adjust these values based on your network traffic to and from your email servers. -providing_technologies = none - -[savedsearch://ESCU - Excessive DNS Failures - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -how_to_implement = To successfully implement this search you must ensure that DNS data is populating the Network_Resolution data model. -annotations = {"cis20": ["CIS 8", "CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048", "T1043"], "nist": ["PR.PT", "DE.AE", "DE.CM"]} -known_false_positives = It is possible legitimate traffic can trigger this rule. Please investigate as appropriate. The threshold for generating an event can also be customized to better suit your environment. -providing_technologies = none - -[savedsearch://ESCU - Execution of File With Spaces Before Extension - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. -annotations = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.PT", "PR.IP"]} -known_false_positives = None identified. -providing_technologies = none - -[savedsearch://ESCU - Execution of File with Multiple Extensions - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. -annotations = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.PT", "PR.IP"]} -known_false_positives = None identified. -providing_technologies = none - -[savedsearch://ESCU - Extended Period Without Successful Netbackup Backups - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search returns a list of hosts that have not successfully completed a backup in over a week. -how_to_implement = To successfully implement this search you need to first obtain data from your backup solution, either from the backup logs on your hosts, or from a central server responsible for performing the backups. If you do not use Netbackup, you can modify this search for your backup solution. Depending on how often you backup your systems, you may want to modify how far in the past to look for a successful backup, other than the default of seven days. -annotations = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} -known_false_positives = None identified -providing_technologies = none - -[savedsearch://ESCU - File with Samsam Extension - Rule] -type = detection -asset_type = -confidence = medium -explanation = The search looks for file writes with extensions consistent with a SamSam ransomware attack. -how_to_implement = You must be ingesting data that records file-system 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 = {"cis20": ["CIS 8"], "kill_chain_phases": ["Installation"], "nist": ["PR.PT", "DE.CM"]} -known_false_positives = Because these extensions are not typically used in normal operations, you should investigate all results. -providing_technologies = none - -[savedsearch://ESCU - First Time Seen Running Windows Service - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for the first time a Windows service is seen running in your environment. -how_to_implement = While this search does not require you to adhere to Splunk CIM, you must be ingesting your Windows security-event logs in order for this search to execute successfully. The support search, `Previously Seen Running Windows Services`, should be run before this search to create the baseline of known Windows services. Please ensure that the Splunk Add-on for Microsoft Windows is version 5.0.0 or above. -annotations = {"cis20": ["CIS 2", "CIS 9"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1050"], "nist": ["ID.AM", "PR.DS", "PR.AC", "DE.AE"]} -known_false_positives = A previously unseen service is not necessarily malicious. Verify that the service is legitimate and that was installed by a legitimate process. -providing_technologies = none - -[savedsearch://ESCU - First time seen command line argument - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for command-line arguments that use a `/c` parameter to execute a command that has not previously been seen. -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. Please make sure you run the support search "Previously seen command line arguments,"—which creates a lookup file called `previously_seen_cmd_line_arguments.csv`—a historical baseline of all command-line arguments. You must also validate this list. For the search to do accurate calculation, ensure the search scheduling is the same value as the `relative_time` evaluation function. -annotations = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1064", "T1059"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -known_false_positives = Legitimate programs can also use command-line arguments to execute. Please verify the command-line arguments to check what command/program is being executed. We recommend customizing the `first_time_seen_cmd_line_filter` macro to exclude legitimate parent_process_name -providing_technologies = none - -[savedsearch://ESCU - GCP GCR container uploaded - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search show information on uploaded containers including source user, account, action, bucket name event name, http user agent, message and destination path. -how_to_implement = You must install the GCP App for Splunk (version 2.0.0 or later), then configure stackdriver and set a subpub subscription to be imported to Splunk. You must also install Cloud Infrastructure data model. Please also customize the `container_implant_gcp_detection_filter` macro to filter out the false positives. -annotations = {} -known_false_positives = Uploading container is a normal behavior from developers or users with access to container registry. GCP GCR registers container upload as a Storage event, this search must be considered under the context of CONTAINER upload creation which automatically generates a bucket entry for destination path. -providing_technologies = none - -[savedsearch://ESCU - GCP Kubernetes cluster scan detection - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster -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. -annotations = {"kill_chain_phases": ["Reconnaissance"]} -known_false_positives = Not all unauthenticated requests are malicious, but frequency, User Agent and source IPs will provide context. -providing_technologies = none - -[savedsearch://ESCU - Hiding Files And Directories With Attrib exe - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM"]} -known_false_positives = Some applications and users may legitimately use attrib.exe to interact with the files. -providing_technologies = none - -[savedsearch://ESCU - Hosts receiving high volume of network traffic from email server - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -how_to_implement = This search requires you to be ingesting your network traffic and populating the Network_Traffic data model. Your email servers must be categorized as "email_server" for the search to work, as well. You may need to adjust the deviation_threshold and minimum_data_samples values based on the network traffic in your environment. The "deviation_threshold" field is a multiplying factor to control how much variation you're willing to tolerate. The "minimum_data_samples" field is the minimum number of connections of data samples required for the statistic to be valid. -annotations = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043"], "nist": ["PR.PT", "DE.CM", "DE.AE"]} -known_false_positives = The false-positive rate will vary based on how you set the deviation_threshold and data_samples values. Our recommendation is to adjust these values based on your network traffic to and from your email servers. -providing_technologies = none - -[savedsearch://ESCU - Identify New User Accounts - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -how_to_implement = To successfully implement this search, you need to be populating the Enterprise Security Identity_Management data model in the assets and identity framework. -annotations = {"cis20": ["CIS 16"], "mitre_attack": ["T1136"], "nist": ["PR.IP"]} -known_false_positives = If the Identity_Management data model is not updated regularly, this search could give you false positive alerts. Please consider this and investigate appropriately. -providing_technologies = none - -[savedsearch://ESCU - Kubernetes Azure detect RBAC authorization by account - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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 -how_to_implement = You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics -annotations = {"kill_chain_phases": ["Lateral Movement"]} -known_false_positives = Not all RBAC Authorications are malicious. RBAC authorizations can uncover malicious activity specially if sensitive Roles have been granted. -providing_technologies = none - -[savedsearch://ESCU - Kubernetes Azure detect most active service accounts by pod namespace - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search provides information on Kubernetes service accounts,accessing pods and namespaces by IP address and verb -how_to_implement = You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics -annotations = {"kill_chain_phases": ["Lateral Movement"]} -known_false_positives = Not all service accounts interactions are malicious. Analyst must consider IP and verb context when trying to detect maliciousness. -providing_technologies = none - -[savedsearch://ESCU - Kubernetes Azure detect sensitive object access - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search provides information on Kubernetes accounts accessing sensitve objects such as configmpas or secrets -how_to_implement = You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics -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 = none - -[savedsearch://ESCU - Kubernetes Azure detect sensitive role access - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search provides information on Kubernetes accounts accessing sensitve objects such as configmpas or secrets -how_to_implement = You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics -annotations = {"kill_chain_phases": ["Lateral Movement"]} -known_false_positives = Sensitive role resource access is necessary for cluster operation, however source IP, namespace and user group may indicate possible malicious use. -providing_technologies = none - -[savedsearch://ESCU - Kubernetes Azure detect service accounts forbidden failure access - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search provides information on Kubernetes service accounts with failure or forbidden access status -how_to_implement = You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics -annotations = {"kill_chain_phases": ["Lateral Movement"]} -known_false_positives = This search can give false positives as there might be inherent issues with authentications and permissions at cluster. -providing_technologies = none - -[savedsearch://ESCU - Kubernetes Azure detect suspicious kubectl calls - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search provides information on Kubectl calls with IP, verb namespace and object access context -how_to_implement = You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics -annotations = {"kill_chain_phases": ["Lateral Movement"]} -known_false_positives = Kubectl calls are not malicious by nature. However source IP, verb and Object can reveal potential malicious activity, specially suspicious IPs and sensitive objects such as configmaps or secrets -providing_technologies = none - -[savedsearch://ESCU - Kubernetes Azure pod scan fingerprint - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search provides information of unauthenticated requests via source IP user agent, request URI and response status data against Kubernetes cluster pod in Azure -how_to_implement = You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics -annotations = {"kill_chain_phases": ["Reconnaissance"]} -known_false_positives = Not all unauthenticated requests are malicious, but source IPs, userAgent, verb, request URI and response status will provide context. -providing_technologies = none - -[savedsearch://ESCU - Kubernetes Azure scan fingerprint - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search provides information of unauthenticated requests via source IP user agent, request URI and response status data against Kubernetes cluster in Azure -how_to_implement = You must install the Add-on for Microsoft Cloud Services and Configure Kube-Audit data diagnostics -annotations = {"kill_chain_phases": ["Reconnaissance"]} -known_false_positives = Not all unauthenticated requests are malicious, but source IPs, userAgent, verb, request URI and response status will provide context. -providing_technologies = none - -[savedsearch://ESCU - Large Volume of DNS ANY Queries - Rule] -type = detection -asset_type = -confidence = medium -explanation = The search is used to identify attempts to use your DNS Infrastructure for DDoS purposes via a DNS amplification attack leveraging ANY queries. -how_to_implement = To successfully implement this search you must ensure that DNS data is populating the Network_Resolution data model. -annotations = {"cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.AE", "PR.IP"]} -known_false_positives = Legitimate ANY requests may trigger this search, however it is unusual to see a large volume of them under typical circumstances. You may modify the threshold in the search to better suit your environment. -providing_technologies = none - -[savedsearch://ESCU - MacOS - Re-opened Applications - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for processes referencing the plist files that determine which applications are re-opened when a user reboots their machine. -how_to_implement = In order to properly run this search, Splunk needs to ingest process data from your osquery deployed agents with the [splunk.conf](https://github.com/splunk/TA-osquery/blob/master/config/splunk.conf) pack enabled. Also the [TA-OSquery](https://github.com/splunk/TA-osquery) must be deployed across your indexers and universal forwarders in order to have the data populate the Endpoint data model. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Installation", "Command and Control"], "nist": ["DE.DP", "DE.CM"]} -known_false_positives = At this stage, there are no known false positives. During testing, no process events refering the com.apple.loginwindow.plist files were observed during normal operation of re-opening applications on reboot. Therefore, it can be asumed that any occurences of this in the process events would be worth investigating. In the event that the legitimate modification by the system of these files is in fact logged to the process log, then the process_name of that process can be whitelisted. -providing_technologies = none - -[savedsearch://ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -known_false_positives = Legitimate process can have this combination of command-line options, but it's not common. -providing_technologies = none - -[savedsearch://ESCU - Malicious PowerShell Process - Encoded Command - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -known_false_positives = System administrators may use this option, but it's not common. -providing_technologies = none - -[savedsearch://ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -known_false_positives = There may be legitimate reasons to bypass the PowerShell execution policy. The PowerShell script being run with this parameter should be validated to ensure that it is legitimate. -providing_technologies = none - -[savedsearch://ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -known_false_positives = Legitimate process can have this combination of command-line options, but it's not common. -providing_technologies = none - -[savedsearch://ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for PowerShell processes launched with arguments that have characters indicative of obfuscation on the command-line. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -known_false_positives = These characters might be legitimately on the command-line, but it is not common. -providing_technologies = none - -[savedsearch://ESCU - Monitor DNS For Brand Abuse - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for DNS requests for faux domains similar to the domains that you want to have monitored for abuse. -how_to_implement = You need to ingest data from your DNS logs. Specifically you must ingest the domain that is being queried and the IP of the host originating the request. Ideally, you should also be ingesting the answer to the query and the query type. This approach allows you to also create your own localized passive DNS capability which can aid you in future investigations. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for. -annotations = {"kill_chain_phases": ["Delivery", "Actions on Objectives"]} -known_false_positives = None at this time -providing_technologies = none - -[savedsearch://ESCU - Monitor Email For Brand Abuse - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for emails claiming to be sent from a domain similar to one that you want to have monitored for abuse. -how_to_implement = You need to ingest email header data. Specifically the sender's address (src_user) must be populated. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for. -annotations = {"cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"]} -known_false_positives = None at this time -providing_technologies = none - -[savedsearch://ESCU - Monitor Registry Keys for Print Monitors - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -how_to_implement = To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report registry modifications. -annotations = {"cis20": ["CIS 8", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM", "PR.AC"]} -known_false_positives = You will encounter noise from legitimate print-monitor registry entries. -providing_technologies = none - -[savedsearch://ESCU - Monitor Web Traffic For Brand Abuse - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for Web requests to faux domains similar to the one that you want to have monitored for abuse. -how_to_implement = You need to ingest data from your web traffic. This can be accomplished by indexing data from a web proxy, or using a network traffic analysis tool, such as Bro or Splunk Stream. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for. -annotations = {"cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"]} -known_false_positives = None at this time -providing_technologies = none - -[savedsearch://ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search detects Okta login failures due to bad credentials for multiple users originating from the same ip address. -how_to_implement = This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment. -annotations = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} -known_false_positives = A single public IP address servicing multiple legitmate users may trigger this search. In addition, the threshold of 5 distinct users may be too low for your needs. You may modify the included filter macro XXXXXXXXXXXXX to raise the threshold or except specific IP adresses from triggering this search. -providing_technologies = none - -[savedsearch://ESCU - New container uploaded to AWS ECR - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -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. You must also install Cloud Infrastructure data model. Please also customize the `container_implant_aws_detection_filter` macro to filter out the false positives. -annotations = {} -known_false_positives = Uploading container is a normal behavior from developers or users with access to container registry. -providing_technologies = none - -[savedsearch://ESCU - No Windows Updates in a time frame - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -how_to_implement = To successfully implement this search, it requires that the 'Update' data model is being populated. This can be accomplished by ingesting Windows events or the Windows Update log via a universal forwarder on the Windows endpoints you wish to monitor. The Windows add-on should be also be installed and configured to properly parse Windows events in Splunk. There may be other data sources which can populate this data model, including vulnerability management systems. -annotations = {"cis20": ["CIS 18"], "nist": ["PR.PT", "PR.MA"]} -known_false_positives = None identified -providing_technologies = none - -[savedsearch://ESCU - Okta Account Lockout Events - Rule] -type = detection -asset_type = -confidence = medium -explanation = Detect Okta user lockout events -how_to_implement = This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment. -annotations = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} -known_false_positives = None. Account lockouts should be followed up on to determine if the actual user was the one who caused the lockout, or if it was an unauthorized actor. -providing_technologies = none - -[savedsearch://ESCU - Okta Failed SSO Attempts - Rule] -type = detection -asset_type = -confidence = medium -explanation = Detect failed Okta SSO events -how_to_implement = This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment. -annotations = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} -known_false_positives = There may be a faulty config preventing legitmate users from accessing apps they should have access to. -providing_technologies = none - -[savedsearch://ESCU - Okta User Logins From Multiple Cities - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search detects logins from the same user from different states in a 24 hour period. -how_to_implement = This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment. -annotations = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} -known_false_positives = Users in your enviornment may legitmately be travelling and loggin in from different locations. This search is useful for those users that should *not* be travelling for some reason, such as the COVID-19 pandemic. The search also relies on the geographical information being populated in the Okta logs. It is also possible that a connection from another region may be attributed to a login from a remote VPN endpoint. -providing_technologies = none - -[savedsearch://ESCU - Open Redirect in Splunk Web - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search allows you to look for evidence of exploitation for CVE-2016-4859, the Splunk Open Redirect Vulnerability. -how_to_implement = No extra steps needed to implement this search. -annotations = {"cis20": ["CIS 3", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "RS.MI", "PR.PT", "PR.AC", "PR.IP", "DE.CM"]} -known_false_positives = None identified -providing_technologies = none - -[savedsearch://ESCU - Osquery pack - ColdRoot detection - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for ColdRoot events from the osx-attacks osquery pack. -how_to_implement = In order to properly run this search, Splunk needs to ingest data from your osquery deployed agents with the [osx-attacks.conf](https://github.com/facebook/osquery/blob/experimental/packs/osx-attacks.conf#L599) pack enabled. Also the [TA-OSquery](https://github.com/d1vious/TA-osquery) must be deployed across your indexers and universal forwarders in order to have the osquery data populate the Alerts data model -annotations = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Installation", "Command and Control"], "nist": ["DE.DP", "DE.CM", "PR.PT"]} -known_false_positives = There are no known false positives. -providing_technologies = none - -[savedsearch://ESCU - Overwriting Accessibility Binaries - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -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 = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015"], "nist": ["PR.PT", "DE.CM"]} -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 = none - -[savedsearch://ESCU - Process Execution via WMI - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for processes launched via WMI. -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. -annotations = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} -known_false_positives = Although unlikely, administrators may use wmi to execute commands for legitimate purposes. -providing_technologies = none - -[savedsearch://ESCU - Processes Tapping Keyboard Events - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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 -how_to_implement = In order to properly run this search, Splunk needs to ingest data from your osquery deployed agents with the [osx-attacks.conf](https://github.com/facebook/osquery/blob/experimental/packs/osx-attacks.conf#L599) pack enabled. Also the [TA-OSquery](https://github.com/d1vious/TA-osquery) must be deployed across your indexers and universal forwarders in order to have the osquery data populate the Alerts data model. -annotations = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Command and Control"], "nist": ["DE.DP"]} -known_false_positives = There might be some false positives as keyboard event taps are used by processes like Siri and Zoom video chat, for some good examples of processes to exclude please see [this](https://github.com/facebook/osquery/pull/5345#issuecomment-454639161) comment. -providing_technologies = none - -[savedsearch://ESCU - Processes created by netsh - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -how_to_implement = To successfully implement this search, you must be ingesting logs with the process name, command-line arguments, and parent processes from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} -known_false_positives = It is unusual for netsh.exe to have any child processes in most environments. It makes sense to investigate the child process and verify whether the process spawned is legitimate. -providing_technologies = none - -[savedsearch://ESCU - Processes launching netsh - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059", "T1089"], "nist": ["PR.PT", "DE.CM"]} -known_false_positives = Some VPN applications are known to launch netsh.exe. Outside of these instances, it is unusual for an executable to launch netsh.exe and run commands. -providing_technologies = none - -[savedsearch://ESCU - Prohibited Network Traffic Allowed - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -how_to_implement = In order to properly run this search, Splunk needs to ingest data from firewalls or other network control devices that mediate the traffic allowed into an environment. This is necessary so that the search can identify an 'action' taken on the traffic of interest. The search requires the Network_Traffic data model be populated. -annotations = {"cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Delivery", "Command and Control"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "PR.AC"]} -known_false_positives = None identified -providing_technologies = none - -[savedsearch://ESCU - Prohibited Software On Endpoint - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for applications on the endpoint that you have marked as prohibited. -how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. This is typically populated via endpoint detection-and-response products, such as Carbon Black or endpoint data sources, such as Sysmon. The data used for this search is usually generated via logs that report process tracking in your Windows audit settings. In addition, you must also have only the `process_name` (not the entire process path) marked as "prohibited" in the Enterprise Security `interesting processes` table. To include the process names marked as "prohibited", which is included with ES Content Updates, run the included search Add Prohibited Processes to Enterprise Security. -annotations = {"cis20": ["CIS 2"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"]} -known_false_positives = None identified -providing_technologies = none - -[savedsearch://ESCU - Protocol or Port Mismatch - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -how_to_implement = Running this search properly requires a technology that can inspect network traffic and identify common protocols. Technologies such as Bro and Palo Alto Networks firewalls are two examples that will identify protocols via inspection, and not just assume a specific protocol based on the transport protocol and ports. -annotations = {"cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE", "PR.AC"]} -known_false_positives = None identified -providing_technologies = none - -[savedsearch://ESCU - Protocols passing authentication in cleartext - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -how_to_implement = This search requires you to be ingesting your network traffic, and populating the Network_Traffic data model. -annotations = {"cis20": ["CIS 9", "CIS 14"], "kill_chain_phases": ["Reconnaissance", "Actions on Objectives"], "nist": ["PR.PT", "DE.AE", "PR.AC", "PR.DS"]} -known_false_positives = Some networks may use kerberized FTP or telnet servers, however, this is rare. -providing_technologies = none - -[savedsearch://ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule] -type = detection -asset_type = -confidence = medium -explanation = The search looks for reg.exe modifying registry keys that define Windows services and their configurations. -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. -annotations = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack": ["T1050", "T1031", "T1089"], "nist": ["PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.CM"]} -known_false_positives = It is unusual for a service to be created or modified by directly manipulating the registry. However, there may be legitimate instances of this behavior. It is important to validate and investigate, as appropriate. -providing_technologies = none - -[savedsearch://ESCU - Reg exe used to hide files directories via registry keys - Rule] -type = detection -asset_type = -confidence = medium -explanation = The search looks for command-line arguments used to hide a file or directory using the reg add command. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM"]} -known_false_positives = None at the moment -providing_technologies = none - -[savedsearch://ESCU - Registry Keys Used For Persistence - Rule] -type = detection -asset_type = -confidence = medium -explanation = The search looks for modifications to registry keys that can be used to launch an application or service at system startup. -how_to_implement = To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, 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. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1103", "T1131"], "nist": ["PR.PT", "DE.CM", "DE.AE"]} -known_false_positives = There are many legitimate applications that must execute on system startup and will use these registry keys to accomplish that task. -providing_technologies = none - -[savedsearch://ESCU - Registry Keys Used For Privilege Escalation - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -how_to_implement = To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, 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. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015"], "nist": ["PR.PT", "DE.CM"]} -known_false_positives = There are many legitimate applications that must execute upon system startup and will use these registry keys to accomplish that task. -providing_technologies = none - -[savedsearch://ESCU - Registry Keys for Creating SHIM Databases - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for registry activity associated with application compatibility shims, which can be leveraged by attackers for various nefarious purposes. -how_to_implement = To successfully implement this search, you must populate the Change_Analysis data model. This is typically populated via endpoint detection and response products, such as Carbon Black or other 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. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1138"], "nist": ["PR.PT", "DE.CM"]} -known_false_positives = There are many legitimate applications that leverage shim databases for compatibility purposes for legacy applications -providing_technologies = none - -[savedsearch://ESCU - Remote Desktop Network Bruteforce - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -how_to_implement = You must ensure that your network traffic data is populating the Network_Traffic data model. -annotations = {"cis20": ["CIS 12", "CIS 9", "CIS 16"], "kill_chain_phases": ["Reconnaissance", "Delivery"], "mitre_attack": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -known_false_positives = RDP gateways may have unusually high amounts of traffic from all other hosts' RDP applications in the network. -providing_technologies = none - -[savedsearch://ESCU - Remote Desktop Network Traffic - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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 allows for whitelisting both source and destination hosts to remove them from the output of the search so you can focus on the uncommon uses of remote desktop on your network. -how_to_implement = To successfully implement this search you need to identify systems that commonly originate remote desktop traffic and that commonly receive remote desktop traffic. You can use the included support search "Identify Systems Creating Remote Desktop Traffic" to identify systems that originate the traffic and the search "Identify Systems Receiving Remote Desktop Traffic" to identify systems that receive a lot of remote desktop traffic. After identifying these systems, you will need to add the "common_rdp_source" or "common_rdp_destination" category to that system depending on the usage, using the Enterprise Security Assets and Identities framework. This can be done by adding an entry in the assets.csv file located in SA-IdentityManagement/lookups. -annotations = {"cis20": ["CIS 3", "CIS 9", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -known_false_positives = Remote Desktop may be used legitimately by users on the network. -providing_technologies = none - -[savedsearch://ESCU - Remote Desktop Process Running On System - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. The search requires you to identify systems that do not commonly use remote desktop. You can use the included support search "Identify Systems Using Remote Desktop" to identify these systems. After identifying them, you will need to add the "common_rdp_source" category to that system using the Enterprise Security Assets and Identities framework. This can be done by adding an entry in the assets.csv file located in `SA-IdentityManagement/lookups`. -annotations = {"cis20": ["CIS 3", "CIS 9", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -known_false_positives = Remote Desktop may be used legitimately by users on the network. -providing_technologies = none - -[savedsearch://ESCU - Remote Process Instantiation via WMI - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for wmic.exe being launched with parameters to spawn a process on a remote system. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} -known_false_positives = The wmic.exe utility is a benign Windows application. It may be used legitimately by Administrators with these parameters for remote system administration, but it's relatively uncommon. -providing_technologies = none - -[savedsearch://ESCU - Remote Registry Key modifications - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search monitors for remote modifications to registry keys. -how_to_implement = To successfully implement this search, you must populate the `Endpoint` data model. This is typically populated via endpoint detection-and-response products, 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. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} -known_false_positives = This technique may be legitimately used by administrators to modify remote registries, so it's important to filter these events out. -providing_technologies = none - -[savedsearch://ESCU - Remote WMI Command Attempt - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for wmic.exe being launched with parameters to operate on remote systems. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} -known_false_positives = Administrators may use this legitimately to gather info from remote systems. -providing_technologies = none - -[savedsearch://ESCU - RunDLL Loading DLL By Ordinal - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for DLLs under %AppData% being loaded by rundll32.exe that are calling the exported function at ordinal 2. Calling exported functions by ordinal is not as common as calling by exported name. There was a bug fixed in IDAPro on 2016-08-08 that would not display functions without names. Calling functions by ordinal would overcome the lack of name and make it harder for analyst to reverse engineer. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack": ["T1085"], "nist": ["PR.PT", "DE.CM"]} -known_false_positives = While not common, loading a DLL under %AppData% and calling a function by ordinal is possible by a legitimate process -providing_technologies = none - -[savedsearch://ESCU - SMB Traffic Spike - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for spikes in the number of Server Message Block (SMB) traffic connections. -how_to_implement = This search requires you to be ingesting your network traffic logs and populating the `Network_Traffic` data model. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -known_false_positives = A file server may experience high-demand loads that could cause this analytic to trigger. -providing_technologies = none - -[savedsearch://ESCU - SMB Traffic Spike - MLTK - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search uses the Machine Learning Toolkit (MLTK) to identify spikes in the number of Server Message Block (SMB) connections. -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, the Machine Learning Toolkit (MLTK) version 4.2 or greater must be installed on your search heads, along with any required dependencies. Finally, the support search "Baseline of SMB Traffic - MLTK" must be executed before this detection search, because it builds a machine-learning (ML) model over the historical data used by this search. It is important that this search is run in the same app context as the associated support search, so that the model created by the support search is available for use. You should periodically re-run the support search to rebuild the model with the latest data available in your environment.\ -This search produces a field (Number of events,count) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. This field contributes additional context to the notable. To see the additional metadata, add the following field, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry): \ -1. **Label:** Number of events, **Field:** count\ -Detailed documentation on how to create a new field within Incident Review is found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -known_false_positives = If you are seeing more results than desired, you may consider reducing the value of the threshold in the search. You should also periodically re-run the support search to re-build the ML model on the latest data. Please update the `smb_traffic_spike_mltk_filter` macro to filter out false positive results -providing_technologies = none - -[savedsearch://ESCU - SQL Injection with Long URLs - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for long URLs that have several SQL commands visible within them. -how_to_implement = To successfully implement this search, you need to be monitoring network communications to your web servers or ingesting your HTTP logs and populating the Web data model. You must also identify your web servers in the Enterprise Security assets table. -annotations = {"cis20": ["CIS 4", "CIS 13", "CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1043"], "nist": ["PR.DS", "ID.RA", "PR.PT", "PR.IP", "DE.CM"]} -known_false_positives = It's possible that legitimate traffic will have long URLs or long user agent strings and that common SQL commands may be found within the URL. Please investigate as appropriate. -providing_technologies = none - -[savedsearch://ESCU - Samsam Test File Write - Rule] -type = detection -asset_type = -confidence = medium -explanation = The search looks for a file named "test.txt" written to the windows system directory tree, which is consistent with Samsam propagation. -how_to_implement = You must be ingesting data that records the file-system 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 = {"cis20": ["CIS 8"], "kill_chain_phases": ["Delivery"], "nist": ["PR.PT", "DE.CM"]} -known_false_positives = No false positives have been identified. -providing_technologies = none - -[savedsearch://ESCU - Sc exe Manipulating Windows Services - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for arguments to sc.exe indicating the creation or modification of a Windows service. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack": ["T1050", "T1031", "T1089"], "nist": ["PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.CM"]} -known_false_positives = Using sc.exe to manipulate Windows services is uncommon. However, there may be legitimate instances of this behavior. It is important to validate and investigate as appropriate. -providing_technologies = none - -[savedsearch://ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for flags passed to schtasks.exe on the command-line that indicate a task name associated with the Dragonfly threat actor was created or deleted. -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. -annotations = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053"], "nist": ["PR.IP"]} -known_false_positives = No known false positives -providing_technologies = none - -[savedsearch://ESCU - Scheduled tasks used in BadRabbit ransomware - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053"], "nist": ["PR.IP"]} -known_false_positives = No known false positives -providing_technologies = none - -[savedsearch://ESCU - Schtasks scheduling job on remote system - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for flags passed to schtasks.exe on the command-line that indicate a job is being scheduled on a remote system. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053"], "nist": ["PR.IP"]} -known_false_positives = Administrators may create jobs on remote systems, but this activity is usually limited to a small set of hosts or users. It is important to validate and investigate as appropriate. -providing_technologies = none - -[savedsearch://ESCU - Schtasks used for forcing a reboot - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for flags passed to schtasks.exe on the command-line that indicate that a forced reboot of system is scheduled. -how_to_implement = To successfully implement this search 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. -annotations = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053"], "nist": ["PR.IP"]} -known_false_positives = Administrators may create jobs on systems forcing reboots to perform updates, maintenance, etc. -providing_technologies = none - -[savedsearch://ESCU - Script Execution via WMI - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for scripts launched via WMI. -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. -annotations = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} -known_false_positives = Although unlikely, administrators may use wmi to launch scripts for legitimate purposes. -providing_technologies = none - -[savedsearch://ESCU - Shim Database File Creation - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -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 = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1138"], "nist": ["DE.CM"]} -known_false_positives = Because legitimate shim files are created and used all the time, this event, in itself, is not suspicious. However, if there are other correlating events, it may warrant further investigation. -providing_technologies = none - -[savedsearch://ESCU - Shim Database Installation With Suspicious Parameters - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1138"], "nist": ["DE.CM"]} -known_false_positives = None identified -providing_technologies = none - -[savedsearch://ESCU - Short Lived Windows Accounts - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search detects accounts that were created and deleted in a short time period. -how_to_implement = This search requires you to have enabled your Group Management Audit Logs in your Local Windows Security Policy and be ingesting those logs. More information on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/ -annotations = {"cis20": ["CIS 16"], "mitre_attack": ["T1136"], "nist": ["PR.IP"]} -known_false_positives = It is possible that an administrator created and deleted an account in a short time period. Verifying activity with an administrator is advised. -providing_technologies = none - -[savedsearch://ESCU - Single Letter Process On Endpoint - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for process names that consist only of a single letter. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["ID.AM", "PR.DS"]} -known_false_positives = Single-letter executables are not always malicious. Investigate this activity with your normal incident-response process. -providing_technologies = none - -[savedsearch://ESCU - Spectre and Meltdown Vulnerable Systems - Rule] -type = detection -asset_type = -confidence = medium -explanation = The search is used to detect systems that are still vulnerable to the Spectre and Meltdown vulnerabilities. -how_to_implement = The search requires that you are ingesting your vulnerability-scanner data and that it reports the CVE of the vulnerability identified. -annotations = {"cis20": ["CIS 4"], "nist": ["ID.RA", "RS.MI", "PR.IP", "DE.CM"]} -known_false_positives = It is possible that your vulnerability scanner is not detecting that the patches have been applied. -providing_technologies = none - -[savedsearch://ESCU - Spike in File Writes - Rule] -type = detection -asset_type = -confidence = medium -explanation = The search looks for a sharp increase in the number of files written to a particular host -how_to_implement = In order to implement this search, you must populate the Endpoint file-system data model node. This is typically populated via endpoint detection and response products, 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 file system. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM"]} -known_false_positives = It is important to understand that if you happen to install any new applications on your hosts or are copying a large number of files, you can expect to see a large increase of file modifications. -providing_technologies = none - -[savedsearch://ESCU - Splunk Enterprise Information Disclosure - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search allows you to look for evidence of exploitation for CVE-2018-11409, a Splunk Enterprise Information Disclosure Bug. -how_to_implement = The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Whitelisting your Splunk systems will reduce false positives. -annotations = {"cis20": ["CIS 3", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "RS.MI", "PR.PT", "PR.AC", "PR.IP", "DE.CM"]} -known_false_positives = Retrieving server information may be a legitimate API request. Verify that the attempt is a valid request for information. -providing_technologies = none - -[savedsearch://ESCU - Suspicious Changes to File Associations - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -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. -annotations = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.PT", "PR.IP"]} -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. -providing_technologies = none - -[savedsearch://ESCU - Suspicious Email - UBA Anomaly - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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). -how_to_implement = You must be ingesting data from email logs and have Splunk integrated with UBA. This anomaly is raised by a UBA detection model called "SuspiciousEmailDetectionModel." Ensure that this model is enabled on your UBA instance. -annotations = {"cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"]} -known_false_positives = This detection model will alert on any sender domain that is seen for the first time. This could be a potential false positive. The next step is to investigate and whitelist the URL if you determine that it is a legitimate sender. -providing_technologies = none - -[savedsearch://ESCU - Suspicious Email Attachment Extensions - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for emails that have attachments with suspicious file extensions. -how_to_implement = You need to ingest data from emails. Specifically, the sender's address and the file names of any attachments must be mapped to the Email data model. \ - **Splunk Phantom Playbook Integration**\ -If Splunk Phantom is also configured in your environment, a Playbook called "Suspicious Email Attachment Investigate and Delete" can be configured to run when any results are found by this detection search. To use this integration, install the Phantom App for Splunk `https://splunkbase.splunk.com/app/3411/`, and add the correct hostname to the "Phantom Instance" field in the Adaptive Response Actions when configuring this detection search. The notable event will be sent to Phantom and the playbook will gather further information about the file attachment and its network behaviors. If Phantom finds malicious behavior and an analyst approves of the results, the email will be deleted from the user's inbox. -annotations = {"cis20": ["CIS 3", "CIS 7", "CIS 12"], "kill_chain_phases": ["Delivery"], "nist": ["DE.AE", "PR.IP"]} -known_false_positives = None identified -providing_technologies = none - -[savedsearch://ESCU - Suspicious File Write - Rule] -type = detection -asset_type = -confidence = medium -explanation = The search looks for files created with names that have been linked to malicious activity. -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. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file system reads and writes. In addition, this search leverages an included lookup file that contains the names of the files to watch for, as well as a note to communicate why that file name is being monitored. This lookup file can be edited to add or remove file the file names you want to monitor. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} -known_false_positives = It's possible for a legitimate file to be created with the same name as one noted in the lookup file. Filenames listed in the lookup file should be unique enough that collisions are rare. Looking at the location of the file and the process responsible for the activity can help determine whether or not the activity is legitimate. -providing_technologies = none - -[savedsearch://ESCU - Suspicious Java Classes - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for suspicious Java classes that are often used to exploit remote command execution in common Java frameworks, such as Apache Struts. -how_to_implement = In order to properly run this search, Splunk needs to ingest data from your web-traffic appliances that serve or sit in the path of your Struts application servers. This can be accomplished by indexing data from a web proxy, or by using network traffic-analysis tools, such as Splunk Stream or Bro. -annotations = {"cis20": ["CIS 7", "CIS 12"], "kill_chain_phases": ["Exploitation"], "nist": ["DE.AE"]} -known_false_positives = There are no known false positives. -providing_technologies = none - -[savedsearch://ESCU - Suspicious LNK file launching a process - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for a ``*.lnk` file under `C:\User*` or `*\Local\Temp\*` executing a process. This is common behavior used by various spear phishing tools. -how_to_implement = You must be ingesting data that records filesystem and process activity from your hosts to populate the Endpoint data model. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. -annotations = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1193"], "nist": ["ID.AM", "PR.DS"]} -known_false_positives = This detection should yield little or no false positive results. It is uncommon for LNK files to execute process from temporary or user directories. -providing_technologies = none - -[savedsearch://ESCU - Suspicious Reg exe Process - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1112", "T1089"], "nist": ["DE.CM"]} -known_false_positives = It's possible for system administrators to write scripts that exhibit this behavior. If this is the case, the search will need to be modified to filter them out. -providing_technologies = none - -[savedsearch://ESCU - Suspicious wevtutil Usage - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 3", "CIS 5", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.DP", "PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.AE"]} -known_false_positives = The wevtutil.exe application is a legitimate Windows event log utility. Administrators may use it to manage Windows event logs. -providing_technologies = none - -[savedsearch://ESCU - Suspicious writes to System Volume Information - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search detects writes to the 'System Volume Information' folder by something other than the System process. -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. -annotations = {"cis20": ["CIS 8"], "mitre_attack": ["T1074"], "nist": ["DE.CM"]} -known_false_positives = It is possible that other utilities or system processes may legitimately write to this folder. Investigate and modify the search to include exceptions as appropriate. -providing_technologies = none - -[savedsearch://ESCU - Suspicious writes to windows Recycle Bin - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search detects writes to the recycle bin by a process other than explorer.exe. -how_to_implement = To successfully implement this search you need to be ingesting information on filesystem and process logs responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` and `Filesystem` nodes. -annotations = {"cis20": ["CIS 8"], "mitre_attack": ["T1074"], "nist": ["DE.CM"]} -known_false_positives = Because the Recycle Bin is a hidden folder in modern versions of Windows, it would be unusual for a process other than explorer.exe to write to it. Incidents should be investigated as appropriate. -providing_technologies = none - -[savedsearch://ESCU - System Processes Run From Unexpected Locations - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -how_to_implement = To successfully implement this search you need to ingest details about process execution from your hosts. Specifically, this search requires the process name and the full path to the process executable. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1036"], "nist": ["PR.PT", "DE.CM"]} -known_false_positives = None identified -providing_technologies = none - -[savedsearch://ESCU - TOR Traffic - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -how_to_implement = In order to properly run this search, Splunk needs to ingest data from firewalls or other network control devices that mediate the traffic allowed into an environment. This is necessary so that the search can identify an 'action' taken on the traffic of interest. The search requires the Network_Traffic data model be populated. -annotations = {"cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE"]} -known_false_positives = None at this time -providing_technologies = none - -[savedsearch://ESCU - USN Journal Deletion - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"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"]} -known_false_positives = None identified -providing_technologies = none - -[savedsearch://ESCU - Uncommon Processes On Endpoint - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for applications on the endpoint that you have marked as uncommon. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. This search uses a lookup file `uncommon_processes_default.csv` to track various features of process names that are usually uncommon in most environments. Please consider updating `uncommon_processes_local.csv` to hunt for processes that are uncommon in your environment. -annotations = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015"], "nist": ["ID.AM", "PR.DS"]} -known_false_positives = None identified -providing_technologies = none - -[savedsearch://ESCU - Unload Sysmon Filter Driver - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. This search is also shipped with `unload_sysmon_filter_driver_filter` macro, update this macro to filter out false positives. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1089"], "nist": ["DE.CM"]} -known_false_positives = -providing_technologies = none - -[savedsearch://ESCU - Unsigned Image Loaded by LSASS - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search detects loading of unsigned images by LSASS. -how_to_implement = This search needs Sysmon Logs with a sysmon configuration, which includes EventCode 7 with lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon 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. -annotations = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} -known_false_positives = Other tools could load images into LSASS for legitimate reason. But enterprise tools should always use signed DLLs. -providing_technologies = none - -[savedsearch://ESCU - Unsuccessful Netbackup backups - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search gives you the hosts where a backup was attempted and then failed. -how_to_implement = To successfully implement this search you need to obtain data from your backup solution, either from the backup logs on your endpoints or from a central server responsible for performing the backups. If you do not use Netbackup, you can modify this search for your specific backup solution. -annotations = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} -known_false_positives = None identified -providing_technologies = none - -[savedsearch://ESCU - Unusually Long Command Line - Rule] -type = detection -asset_type = -confidence = medium -explanation = Command lines that are extremely long may be indicative of malicious activity on your hosts. -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. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} -known_false_positives = Some legitimate applications start with long command lines. -providing_technologies = none - -[savedsearch://ESCU - Unusually Long Command Line - MLTK - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -how_to_implement = You must be ingesting endpoint data that monitors command lines and populates the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. In addition, MLTK version >= 4.2 must be installed on your search heads, along with any required dependencies. Finally, the support search "Baseline of Command Line Length - MLTK" must be executed before this detection search, as it builds an ML model over the historical data used by this search. It is important that this search is run in the same app context as the associated support search, so that the model created by the support search is available for use. You should periodically re-run the support search to rebuild the model with the latest data available in your environment. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} -known_false_positives = Some legitimate applications use long command lines for installs or updates. You should review identified command lines for legitimacy. You may modify the first part of the search to omit legitimate command lines from consideration. If you are seeing more results than desired, you may consider changing the value of threshold in the search to a smaller value. You should also periodically re-run the support search to re-build the ML model on the latest data. You may get unexpected results if the user identified in the results is not present in the data used to build the associated model. -providing_technologies = none - -[savedsearch://ESCU - Unusually Long Content-Type Length - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for unusually long strings in the Content-Type http header that the client sends the server. -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. -annotations = {"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"]} -known_false_positives = Very few legitimate Content-Type fields will have a length greater than 100 characters. -providing_technologies = none - -[savedsearch://ESCU - WMI Permanent Event Subscription - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for the creation of WMI permanent event subscriptions. -how_to_implement = To successfully implement this search, you must be ingesting the Windows WMI activity logs. This can be done by adding a stanza to inputs.conf on the system generating logs with a title of [WinEventLog://Microsoft-Windows-WMI-Activity/Operational]. -annotations = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1084"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} -known_false_positives = Although unlikely, administrators may use event subscriptions for legitimate purposes. -providing_technologies = none - -[savedsearch://ESCU - WMI Permanent Event Subscription - Sysmon - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for the creation of WMI permanent event subscriptions. -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 alerts for WMI activity. In addition, you must have at least version 6.0.4 of the Sysmon TA installed to properly parse the fields. -annotations = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1084"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} -known_false_positives = Although unlikely, administrators may use event subscriptions for legitimate purposes. -providing_technologies = none - -[savedsearch://ESCU - WMI Temporary Event Subscription - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for the creation of WMI temporary event subscriptions. -how_to_implement = To successfully implement this search, you must be ingesting the Windows WMI activity logs. This can be done by adding a stanza to inputs.conf on the system generating logs with a title of [WinEventLog://Microsoft-Windows-WMI-Activity/Operational]. -annotations = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1084"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} -known_false_positives = Some software may create WMI temporary event subscriptions for various purposes. The included search contains an exception for two of these that occur by default on Windows 10 systems. You may need to modify the search to create exceptions for other legitimate events. -providing_technologies = none - -[savedsearch://ESCU - Web Fraud - Account Harvesting - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search is used to identify the creation of multiple user accounts using the same email domain name. -how_to_implement = We start with a dataset that provides visibility into the email address used for the account creation. In this example, we are narrowing our search down to the single web page that hosts the Magento2 e-commerce platform (via URI) used for account creation, the single http content-type to grab only the user's clicks, and the http field that provides the username (form_data), for performance reasons. After we have the username and email domain, we look for numerous account creations per email domain. Common data sources used for this detection are customized Apache logs or Splunk Stream. -annotations = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1136"], "nist": ["DE.CM", "DE.DP"]} -known_false_positives = As is common with many fraud-related searches, we are usually looking to attribute risk or synthesize relevant context with loosely written detections that simply detect anamolous behavior. This search will need to be customized to fit your environment—improving its fidelity by counting based on something much more specific, such as a device ID that may be present in your dataset. Consideration for whether the large number of registrations are occuring from a first-time seen domain may also be important. Extending the search window to look further back in time, or even calculating the average per hour/day for each email domain to look for an anomalous spikes, will improve this search. You can also use Shannon entropy or Levenshtein Distance (both courtesy of URL Toolbox) to consider the randomness or similarity of the email name or email domain, as the names are often machine-generated. -providing_technologies = none - -[savedsearch://ESCU - Web Fraud - Anomalous User Clickspeed - Rule] -type = detection -asset_type = -confidence = medium -explanation = 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. -how_to_implement = Start with a dataset that allows you to see clickstream data for each user click on the website. That data must have a time stamp and must contain a reference to the session identifier being used by the website. This ties the clicks together into clickstreams. This value is usually found in the http cookie. With a bit of tuning, a version of this search could be used in high-volume scenarios, such as scraping, crawling, application DDOS, credit-card testing, account takeover, etc. Common data sources used for this detection are customized Apache logs, customized IIS, and Splunk Stream. -annotations = {"cis20": ["CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078"], "nist": ["DE.AE", "DE.CM"]} -known_false_positives = As is common with many fraud-related searches, we are usually looking to attribute risk or synthesize relevant context with loosly written detections that simply detect anamoluous behavior. -providing_technologies = none - -[savedsearch://ESCU - Web Fraud - Password Sharing Across Accounts - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search is used to identify user accounts that share a common password. -how_to_implement = We need to start with a dataset that allows us to see the values of usernames and passwords that users are submitting to the website hosting the Magento2 e-commerce platform (commonly found in the HTTP form_data field). A tokenized or hashed value of a password is acceptable and certainly preferable to a clear-text password. Common data sources used for this detection are customized Apache logs, customized IIS, and Splunk Stream. -annotations = {"cis20": ["CIS 16"], "nist": ["DE.DP"]} -known_false_positives = As is common with many fraud-related searches, we are usually looking to attribute risk or synthesize relevant context with loosely written detections that simply detect anamoluous behavior. -providing_technologies = none - -[savedsearch://ESCU - Web Servers Executing Suspicious Processes - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for suspicious processes on all systems labeled as web servers. -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 also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. In addition, web servers will need to be identified in the Assets and Identity Framework of Enterprise Security. -annotations = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1082"], "nist": ["PR.IP"]} -known_false_positives = Some of these processes may be used legitimately on web servers during maintenance or other administrative tasks. -providing_technologies = none - -[savedsearch://ESCU - Windows Event Log Cleared - Rule] -type = detection -asset_type = -confidence = medium -explanation = This search looks for Windows events that indicate one of the Windows event logs has been purged. -how_to_implement = To successfully implement this search, you need to be ingesting Windows event logs from your hosts. -annotations = {"cis20": ["CIS 3", "CIS 5", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.DP", "PR.IP", "PR.AC", "PR.AT", "DE.AE"]} -known_false_positives = It is possible that these logs may be legitimately cleared by Administrators. -providing_technologies = none - -[savedsearch://ESCU - Windows hosts file modification - Rule] -type = detection -asset_type = -confidence = medium -explanation = The search looks for modifications to the hosts file on all Windows endpoints across your environment. -how_to_implement = To successfully implement this search, you must be ingesting data that records the file-system activity from your hosts to populate the Endpoint.Filesystem data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or by other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file-system reads and writes. -annotations = {"cis20": ["CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "nist": ["PR.IP", "PR.PT", "PR.AC", "DE.AE", "DE.CM"]} -known_false_positives = There may be legitimate reasons for system administrators to add entries to this file. -providing_technologies = none - -### END DETECTIONS ### - -### RESPONSE TASKS ### - -[savedsearch://ESCU - AWS Investigate User Activities By ARN] -type = investigation -explanation = none -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 -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - AWS Investigate User Activities By AccessKeyId] -type = investigation -explanation = none -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 -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - AWS Investigate User Activities By Source User] -type = investigation -explanation = none -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 -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - AWS Network ACL Details from ID] -type = investigation -explanation = none -how_to_implement = In order to implement this search, 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) and configure your AWS description inputs. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - AWS Network Interface details via resourceId] -type = investigation -explanation = none -how_to_implement = In order to implement this search, 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) and configure your AWS configuration inputs -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - AWS S3 Bucket details via bucketName] -type = investigation -explanation = none -how_to_implement = To implement this search, 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) and configure your AWS inputs. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - All backup logs for host] -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] -type = investigation -explanation = none -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 Cloud Watch EKS inputs. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Analyze Malicious File] -type = investigation -explanation = none -how_to_implement = none -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - DNS Hijack Enrichment] -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] -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] -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] -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] -type = investigation -explanation = none -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 -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Get All AWS Activity From Country] -type = investigation -explanation = none -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 -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Get All AWS Activity From IP Address] -type = investigation -explanation = none -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 -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Get All AWS Activity From Region] -type = investigation -explanation = none -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 -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Get Authentication Logs For Endpoint] -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 - Get Backup Logs For Endpoint] -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] -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] -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] -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] -type = investigation -explanation = none -how_to_implement = In order to implement this search, 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) and configure your AWS description inputs. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Get EC2 Launch Details] -type = investigation -explanation = none -how_to_implement = In order to implement this search, 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) and configure your AWS description inputs. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Get Email Info] -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] -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] -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] -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] -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] -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] -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 Notable Info] -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] -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] -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] -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] -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] -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 Registry Activity] -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 Responsible For The DNS Traffic] -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 Registry Activities] -type = investigation -explanation = none -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. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Get Risk Modifiers For Endpoint] -type = investigation -explanation = none -how_to_implement = Enable the correlation searches included in Splunk Enterprise Security that include Risk Analysis alert actions by leveraging the Risk Analysis Framework -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Get Risk Modifiers For User] -type = investigation -explanation = none -how_to_implement = Enable the correlation searches included in Splunk Enterprise Security that include Risk Analysis alert actions by leveraging the Risk Analysis Framework -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Get Sysmon WMI Activity for Host] -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 Update Logs For Endpoint] -type = investigation -explanation = none -how_to_implement = You need to be ingesting the update logs from your various systems. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Get User Information from Identity Table] -type = investigation -explanation = none -how_to_implement = To successfully implement this search you must have populated the identity table with information about your users. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Get Vulnerability Logs For Endpoint] -type = investigation -explanation = none -how_to_implement = You need to be ingesting the logs from your vulnerability scanner. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Get Web Session Information via session id] -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 ECR container listing activity] -type = investigation -explanation = none -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.You must also install Cloud Infrastructure Data Model. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Investigate AWS User Activities by user field] -type = investigation -explanation = none -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 -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Investigate AWS activities via region name] -type = investigation -explanation = none -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 -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Investigate Cloud Compute Instance Activities] -type = investigation -explanation = none -how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Investigate Failed Logins for Multiple Destinations] -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] -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] -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] -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] -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] -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] -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] -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] -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 All Cloud Regions] -type = investigation -explanation = none -how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Investigate User Activities In Okta] -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 User Activities In Single Cloud Region] -type = investigation -explanation = none -how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Investigate Web Activity From Host] -type = investigation -explanation = none -how_to_implement = To successfully implement this search you must be ingesting your web traffic and populating the Web data model. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Investigate Web Activity From src ip] -type = investigation -explanation = none -how_to_implement = To successfully implement this search, you must be ingesting your web traffic and populating the web data model. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Investigate Web POSTs From src] -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 - Malware Hunt and Contain] -type = investigation -explanation = none -how_to_implement = none -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Process Chain Analysis] -type = investigation -explanation = none -how_to_implement = none -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Quarantaine Infected Host] -type = investigation -explanation = none -how_to_implement = none -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -[savedsearch://ESCU - Suspicious Email Attachment Investigate and Delete] -type = investigation -explanation = none -how_to_implement = Synchronize the community playbook repository in Phantom, then open the playbook and follow the deployment notes to configure it for your environment. -known_false_positives = not defined -earliest_time_offset = 14400 -latest_time_offset = 0 - -### END RESPONSE TASKS ### - -### BASELINES ### -[savedsearch://ESCU - Add Prohibited Processes to Enterprise Security] -type = support -explanation = This search takes the existing interesting process table from ES, filters out any existing additions added by ESCU and then updates the table with processes identified by ESCU that should be prohibited on your endpoints. -how_to_implement = This search should be run on each new install of ESCU. -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 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 Compute Creations By User] -type = support -explanation = This search builds a table of previously seen users that have launched a cloud compute instance. -how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Previously Seen Cloud Compute Images] -type = support -explanation = This search builds a table of previously seen images used to launch cloud compute instances -how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Previously Seen Cloud Compute Instance Types] -type = support -explanation = This search builds a table of previously seen cloud compute instance types -how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. -known_false_positives = not defined -providing_technologies = none - -[savedsearch://ESCU - Previously Seen Cloud Regions] -type = support -explanation = 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 -how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. -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] -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 5.0.0 or above. -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. -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.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 - 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. -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.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 - 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