Roles

Elastic #

• Direct Interactive Kubernetes API Request by Unusual Utilities source low: This rule leverages a combination of Defend for Containers and Kubernetes audit logs to detect the execution of direct interactive Kubernetes API requests via unusual utilities. An adversary may need to execute direct interactive Kubernetes API requests to gain access to the Kubernetes API server or other resources within the cluster. These requests are often used to enumerate the Kubernetes API server or other resources within the cluster, and may indicate an attempt to move laterally within the cluster.T1059, T1059.004, T1069, T1087, T1609, T1610↳ also matches list-roles: list roles, watch-roles: watch roles, create-roles: create roles, update-roles: update roles, patch-roles: patch roles
  Investigation guide

  Triage and analysis#

  Disclaimer: This investigation guide was created using generative AI technology and has been reviewed to improve its accuracy and relevance. While every effort has been made to ensure its quality, we recommend validating the content and adapting it to suit your specific environment and operational needs.

  Investigating Direct Interactive Kubernetes API Request by Unusual Utilities#

  This rule detects interactive commands executed inside containers that use atypical utilities to hit the Kubernetes API, paired with near-simultaneous API activity on pods, secrets, service accounts, roles/bindings, or pod exec/attach/log/portforward. It surfaces hands-on-keyboard discovery and lateral movement using custom scripts that evade common tool allowlists; for example, an intruder opens a shell in a pod, uses Python to query the in-cluster API to list secrets, then triggers pods/exec to pivot into another workload.

  Possible investigation steps#

  • Identify the implicated pod, container image, and executing service account, then quickly review its RBAC bindings and effective permissions to determine blast radius.
  • Inspect the container’s interactive session context by pulling recent command lines, shell history, environment variables, and mounted service account tokens, and look for custom scripts or binaries issuing HTTP requests.
  • Correlate nearby Kubernetes audit entries tied to the same principal and pod to map accessed resources and verbs, noting any exec/attach/portforward or sensitive object interactions across namespaces.
  • Review network activity from the pod to the API server and any in-pod proxies, including DNS lookups and outbound connections, to spot nonstandard clients or tunneling behavior.
  • If suspicious, isolate the pod or node, capture runtime artifacts (e.g., process memory or HTTP client traffic), revoke and rotate the service account credentials, and verify image provenance and integrity.

  False positive analysis#

  • An operator interactively attaches to a pod and uses a Python REPL or bash with /dev/tcp to call the in-cluster API for routine troubleshooting (e.g., list pods, read ConfigMaps, or run selfsubjectaccessreviews), producing normal audit entries that match the rule signature.
  • A correlation artifact arises when two namespaces have pods with the same name: one pod starts an interactive shell while another independently performs get/list/watch calls, and the 1-second sequence keyed only on pod-name links the unrelated events.

  Response and remediation#

  • Immediately isolate the implicated pod that issued direct API calls using a nonstandard utility by applying a deny-all egress NetworkPolicy in its namespace (including to kubernetes.default.svc:443), terminating the interactive session, and scaling its owning Deployment/Job/StatefulSet to zero replicas.
  • Before teardown, capture a runtime snapshot of the container and node including the binary or script used to query the API (e.g., files under /tmp or /dev/tcp usage), shell history, environment, and the mounted service account token and CA bundle at /var/run/secrets/kubernetes.io/serviceaccount/.
  • Revoke access by removing the service account’s RoleBindings/ClusterRoleBindings, deleting all pods that mount that service account to force token rotation, rotating any Secrets and ConfigMaps that were read or created during the window, and deleting any unauthorized Jobs, CronJobs, or Deployments created by the same principal.
  • Restore workloads from a known-good image digest, re-enable the Deployment only after image scan and integrity checks pass, and monitor subsequent Kubernetes audit logs for pods/exec, portforward, and access to secrets across the affected namespaces.
  • Escalate to incident response leadership and consider cluster-wide containment if audit logs show create/patch of ClusterRoleBindings, access to secrets outside the workload’s namespace, or use of pods/exec to pivot into other nodes or system namespaces such as kube-system.
  • Harden access by enforcing least-privilege RBAC that denies pods/exec and attach for application service accounts, setting automountServiceAccountToken: false on workloads that do not need it, restricting egress to the API server with NetworkPolicies, and requiring just-in-time break-glass roles for interactive access.
• GKE Multi-Resource Discovery source medium: Adversaries who land credentials in a GKE cluster—or abuse an over-privileged token, often map the environment before exfiltration or privilege escalation. A practical first pass is to learn where workloads run, how the cluster is partitioned, and what RBAC exists at namespace vs cluster scope. Rapid get/list traffic across many distinct API resource kinds that answer those questions (namespaces, workloads, roles, cluster-wide roles) is a common setup and orientation pattern for both interactive attackers and automated recon scripts. This rule highlights that cross-resource burst from a single client fingerprint within a one-minute bucket when both cluster-layout and RBAC resource kinds are touched, so analysts can separate routine automation from potential discovery ahead of follow-on actions.T1613↳ also matches list-roles: list roles
  Investigation guide

  Triage and analysis#

  Investigating GKE Multi-Resource Discovery#

  The rule groups GKE audit get/list events on namespaces, nodes, pods, configmaps, serviceaccounts, roles, rolebindings, clusterroles, and clusterrolebindings into one-minute windows per client.user.email, source.ip, and user_agent.original. It alerts when five or more distinct resource kinds appear and the burst includes both cluster-layout kinds (namespaces, pods, or nodes) and RBAC kinds. Allowed and denied authorizations are both included: failures still signal probing.

  Possible investigation steps#

  • Review Esql.enumerated_resources, Esql.enumerated_namespaces, and Esql.enumerated_resource_names for ordering and targeted APIs.
  • Confirm whether source.ip and user_agent.original match expected admin or automation clients.
  • Correlate with follow-on secret reads, RoleBinding changes, pod exec, or unusual user agents from the same actor.

  False positive analysis#

  • Documented platform sync jobs that read layout and RBAC together; exclude known service accounts after validation.
  • Upgrade or install windows that briefly query many resource kinds; correlate with change records.

  Response and remediation#

  • If malicious, revoke or rotate the implicated credentials, tighten RBAC, and inspect for data access or persistence established after the burst.

Elastic #

• Direct Interactive Kubernetes API Request by Unusual Utilities source low: This rule leverages a combination of Defend for Containers and Kubernetes audit logs to detect the execution of direct interactive Kubernetes API requests via unusual utilities. An adversary may need to execute direct interactive Kubernetes API requests to gain access to the Kubernetes API server or other resources within the cluster. These requests are often used to enumerate the Kubernetes API server or other resources within the cluster, and may indicate an attempt to move laterally within the cluster.T1059, T1059.004, T1069, T1087, T1609, T1610↳ also matches get-roles: get roles, watch-roles: watch roles, create-roles: create roles, update-roles: update roles, patch-roles: patch roles
  Investigation guide

  Triage and analysis#

  Disclaimer: This investigation guide was created using generative AI technology and has been reviewed to improve its accuracy and relevance. While every effort has been made to ensure its quality, we recommend validating the content and adapting it to suit your specific environment and operational needs.

  Investigating Direct Interactive Kubernetes API Request by Unusual Utilities#

  This rule detects interactive commands executed inside containers that use atypical utilities to hit the Kubernetes API, paired with near-simultaneous API activity on pods, secrets, service accounts, roles/bindings, or pod exec/attach/log/portforward. It surfaces hands-on-keyboard discovery and lateral movement using custom scripts that evade common tool allowlists; for example, an intruder opens a shell in a pod, uses Python to query the in-cluster API to list secrets, then triggers pods/exec to pivot into another workload.

  Possible investigation steps#

  • Identify the implicated pod, container image, and executing service account, then quickly review its RBAC bindings and effective permissions to determine blast radius.
  • Inspect the container’s interactive session context by pulling recent command lines, shell history, environment variables, and mounted service account tokens, and look for custom scripts or binaries issuing HTTP requests.
  • Correlate nearby Kubernetes audit entries tied to the same principal and pod to map accessed resources and verbs, noting any exec/attach/portforward or sensitive object interactions across namespaces.
  • Review network activity from the pod to the API server and any in-pod proxies, including DNS lookups and outbound connections, to spot nonstandard clients or tunneling behavior.
  • If suspicious, isolate the pod or node, capture runtime artifacts (e.g., process memory or HTTP client traffic), revoke and rotate the service account credentials, and verify image provenance and integrity.

  False positive analysis#

  • An operator interactively attaches to a pod and uses a Python REPL or bash with /dev/tcp to call the in-cluster API for routine troubleshooting (e.g., list pods, read ConfigMaps, or run selfsubjectaccessreviews), producing normal audit entries that match the rule signature.
  • A correlation artifact arises when two namespaces have pods with the same name: one pod starts an interactive shell while another independently performs get/list/watch calls, and the 1-second sequence keyed only on pod-name links the unrelated events.

  Response and remediation#

  • Immediately isolate the implicated pod that issued direct API calls using a nonstandard utility by applying a deny-all egress NetworkPolicy in its namespace (including to kubernetes.default.svc:443), terminating the interactive session, and scaling its owning Deployment/Job/StatefulSet to zero replicas.
  • Before teardown, capture a runtime snapshot of the container and node including the binary or script used to query the API (e.g., files under /tmp or /dev/tcp usage), shell history, environment, and the mounted service account token and CA bundle at /var/run/secrets/kubernetes.io/serviceaccount/.
  • Revoke access by removing the service account’s RoleBindings/ClusterRoleBindings, deleting all pods that mount that service account to force token rotation, rotating any Secrets and ConfigMaps that were read or created during the window, and deleting any unauthorized Jobs, CronJobs, or Deployments created by the same principal.
  • Restore workloads from a known-good image digest, re-enable the Deployment only after image scan and integrity checks pass, and monitor subsequent Kubernetes audit logs for pods/exec, portforward, and access to secrets across the affected namespaces.
  • Escalate to incident response leadership and consider cluster-wide containment if audit logs show create/patch of ClusterRoleBindings, access to secrets outside the workload’s namespace, or use of pods/exec to pivot into other nodes or system namespaces such as kube-system.
  • Harden access by enforcing least-privilege RBAC that denies pods/exec and attach for application service accounts, setting automountServiceAccountToken: false on workloads that do not need it, restricting egress to the API server with NetworkPolicies, and requiring just-in-time break-glass roles for interactive access.
• GKE Multi-Resource Discovery source medium: Adversaries who land credentials in a GKE cluster—or abuse an over-privileged token, often map the environment before exfiltration or privilege escalation. A practical first pass is to learn where workloads run, how the cluster is partitioned, and what RBAC exists at namespace vs cluster scope. Rapid get/list traffic across many distinct API resource kinds that answer those questions (namespaces, workloads, roles, cluster-wide roles) is a common setup and orientation pattern for both interactive attackers and automated recon scripts. This rule highlights that cross-resource burst from a single client fingerprint within a one-minute bucket when both cluster-layout and RBAC resource kinds are touched, so analysts can separate routine automation from potential discovery ahead of follow-on actions.T1613↳ also matches get-roles: get roles
  Investigation guide

  Triage and analysis#

  Investigating GKE Multi-Resource Discovery#

  The rule groups GKE audit get/list events on namespaces, nodes, pods, configmaps, serviceaccounts, roles, rolebindings, clusterroles, and clusterrolebindings into one-minute windows per client.user.email, source.ip, and user_agent.original. It alerts when five or more distinct resource kinds appear and the burst includes both cluster-layout kinds (namespaces, pods, or nodes) and RBAC kinds. Allowed and denied authorizations are both included: failures still signal probing.

  Possible investigation steps#

  • Review Esql.enumerated_resources, Esql.enumerated_namespaces, and Esql.enumerated_resource_names for ordering and targeted APIs.
  • Confirm whether source.ip and user_agent.original match expected admin or automation clients.
  • Correlate with follow-on secret reads, RoleBinding changes, pod exec, or unusual user agents from the same actor.

  False positive analysis#

  • Documented platform sync jobs that read layout and RBAC together; exclude known service accounts after validation.
  • Upgrade or install windows that briefly query many resource kinds; correlate with change records.

  Response and remediation#

  • If malicious, revoke or rotate the implicated credentials, tighten RBAC, and inspect for data access or persistence established after the burst.

Elastic #

• Direct Interactive Kubernetes API Request by Unusual Utilities source low: This rule leverages a combination of Defend for Containers and Kubernetes audit logs to detect the execution of direct interactive Kubernetes API requests via unusual utilities. An adversary may need to execute direct interactive Kubernetes API requests to gain access to the Kubernetes API server or other resources within the cluster. These requests are often used to enumerate the Kubernetes API server or other resources within the cluster, and may indicate an attempt to move laterally within the cluster.T1059, T1059.004, T1069, T1087, T1609, T1610↳ also matches get-roles: get roles, list-roles: list roles, create-roles: create roles, update-roles: update roles, patch-roles: patch roles
  Investigation guide

  Triage and analysis#

  Disclaimer: This investigation guide was created using generative AI technology and has been reviewed to improve its accuracy and relevance. While every effort has been made to ensure its quality, we recommend validating the content and adapting it to suit your specific environment and operational needs.

  Investigating Direct Interactive Kubernetes API Request by Unusual Utilities#

  This rule detects interactive commands executed inside containers that use atypical utilities to hit the Kubernetes API, paired with near-simultaneous API activity on pods, secrets, service accounts, roles/bindings, or pod exec/attach/log/portforward. It surfaces hands-on-keyboard discovery and lateral movement using custom scripts that evade common tool allowlists; for example, an intruder opens a shell in a pod, uses Python to query the in-cluster API to list secrets, then triggers pods/exec to pivot into another workload.

  Possible investigation steps#

  • Identify the implicated pod, container image, and executing service account, then quickly review its RBAC bindings and effective permissions to determine blast radius.
  • Inspect the container’s interactive session context by pulling recent command lines, shell history, environment variables, and mounted service account tokens, and look for custom scripts or binaries issuing HTTP requests.
  • Correlate nearby Kubernetes audit entries tied to the same principal and pod to map accessed resources and verbs, noting any exec/attach/portforward or sensitive object interactions across namespaces.
  • Review network activity from the pod to the API server and any in-pod proxies, including DNS lookups and outbound connections, to spot nonstandard clients or tunneling behavior.
  • If suspicious, isolate the pod or node, capture runtime artifacts (e.g., process memory or HTTP client traffic), revoke and rotate the service account credentials, and verify image provenance and integrity.

  False positive analysis#

  • An operator interactively attaches to a pod and uses a Python REPL or bash with /dev/tcp to call the in-cluster API for routine troubleshooting (e.g., list pods, read ConfigMaps, or run selfsubjectaccessreviews), producing normal audit entries that match the rule signature.
  • A correlation artifact arises when two namespaces have pods with the same name: one pod starts an interactive shell while another independently performs get/list/watch calls, and the 1-second sequence keyed only on pod-name links the unrelated events.

  Response and remediation#

  • Immediately isolate the implicated pod that issued direct API calls using a nonstandard utility by applying a deny-all egress NetworkPolicy in its namespace (including to kubernetes.default.svc:443), terminating the interactive session, and scaling its owning Deployment/Job/StatefulSet to zero replicas.
  • Before teardown, capture a runtime snapshot of the container and node including the binary or script used to query the API (e.g., files under /tmp or /dev/tcp usage), shell history, environment, and the mounted service account token and CA bundle at /var/run/secrets/kubernetes.io/serviceaccount/.
  • Revoke access by removing the service account’s RoleBindings/ClusterRoleBindings, deleting all pods that mount that service account to force token rotation, rotating any Secrets and ConfigMaps that were read or created during the window, and deleting any unauthorized Jobs, CronJobs, or Deployments created by the same principal.
  • Restore workloads from a known-good image digest, re-enable the Deployment only after image scan and integrity checks pass, and monitor subsequent Kubernetes audit logs for pods/exec, portforward, and access to secrets across the affected namespaces.
  • Escalate to incident response leadership and consider cluster-wide containment if audit logs show create/patch of ClusterRoleBindings, access to secrets outside the workload’s namespace, or use of pods/exec to pivot into other nodes or system namespaces such as kube-system.
  • Harden access by enforcing least-privilege RBAC that denies pods/exec and attach for application service accounts, setting automountServiceAccountToken: false on workloads that do not need it, restricting egress to the API server with NetworkPolicies, and requiring just-in-time break-glass roles for interactive access.

Elastic #

• Direct Interactive Kubernetes API Request by Unusual Utilities source low: This rule leverages a combination of Defend for Containers and Kubernetes audit logs to detect the execution of direct interactive Kubernetes API requests via unusual utilities. An adversary may need to execute direct interactive Kubernetes API requests to gain access to the Kubernetes API server or other resources within the cluster. These requests are often used to enumerate the Kubernetes API server or other resources within the cluster, and may indicate an attempt to move laterally within the cluster.T1059, T1059.004, T1069, T1087, T1609, T1610↳ also matches get-roles: get roles, list-roles: list roles, watch-roles: watch roles, update-roles: update roles, patch-roles: patch roles
  Investigation guide

  Triage and analysis#

  Disclaimer: This investigation guide was created using generative AI technology and has been reviewed to improve its accuracy and relevance. While every effort has been made to ensure its quality, we recommend validating the content and adapting it to suit your specific environment and operational needs.

  Investigating Direct Interactive Kubernetes API Request by Unusual Utilities#

  This rule detects interactive commands executed inside containers that use atypical utilities to hit the Kubernetes API, paired with near-simultaneous API activity on pods, secrets, service accounts, roles/bindings, or pod exec/attach/log/portforward. It surfaces hands-on-keyboard discovery and lateral movement using custom scripts that evade common tool allowlists; for example, an intruder opens a shell in a pod, uses Python to query the in-cluster API to list secrets, then triggers pods/exec to pivot into another workload.

  Possible investigation steps#

  • Identify the implicated pod, container image, and executing service account, then quickly review its RBAC bindings and effective permissions to determine blast radius.
  • Inspect the container’s interactive session context by pulling recent command lines, shell history, environment variables, and mounted service account tokens, and look for custom scripts or binaries issuing HTTP requests.
  • Correlate nearby Kubernetes audit entries tied to the same principal and pod to map accessed resources and verbs, noting any exec/attach/portforward or sensitive object interactions across namespaces.
  • Review network activity from the pod to the API server and any in-pod proxies, including DNS lookups and outbound connections, to spot nonstandard clients or tunneling behavior.
  • If suspicious, isolate the pod or node, capture runtime artifacts (e.g., process memory or HTTP client traffic), revoke and rotate the service account credentials, and verify image provenance and integrity.

  False positive analysis#

  • An operator interactively attaches to a pod and uses a Python REPL or bash with /dev/tcp to call the in-cluster API for routine troubleshooting (e.g., list pods, read ConfigMaps, or run selfsubjectaccessreviews), producing normal audit entries that match the rule signature.
  • A correlation artifact arises when two namespaces have pods with the same name: one pod starts an interactive shell while another independently performs get/list/watch calls, and the 1-second sequence keyed only on pod-name links the unrelated events.

  Response and remediation#

  • Immediately isolate the implicated pod that issued direct API calls using a nonstandard utility by applying a deny-all egress NetworkPolicy in its namespace (including to kubernetes.default.svc:443), terminating the interactive session, and scaling its owning Deployment/Job/StatefulSet to zero replicas.
  • Before teardown, capture a runtime snapshot of the container and node including the binary or script used to query the API (e.g., files under /tmp or /dev/tcp usage), shell history, environment, and the mounted service account token and CA bundle at /var/run/secrets/kubernetes.io/serviceaccount/.
  • Revoke access by removing the service account’s RoleBindings/ClusterRoleBindings, deleting all pods that mount that service account to force token rotation, rotating any Secrets and ConfigMaps that were read or created during the window, and deleting any unauthorized Jobs, CronJobs, or Deployments created by the same principal.
  • Restore workloads from a known-good image digest, re-enable the Deployment only after image scan and integrity checks pass, and monitor subsequent Kubernetes audit logs for pods/exec, portforward, and access to secrets across the affected namespaces.
  • Escalate to incident response leadership and consider cluster-wide containment if audit logs show create/patch of ClusterRoleBindings, access to secrets outside the workload’s namespace, or use of pods/exec to pivot into other nodes or system namespaces such as kube-system.
  • Harden access by enforcing least-privilege RBAC that denies pods/exec and attach for application service accounts, setting automountServiceAccountToken: false on workloads that do not need it, restricting egress to the API server with NetworkPolicies, and requiring just-in-time break-glass roles for interactive access.
• GKE Creation or Modification of Sensitive Role source medium: Detects creation or modification of GKE Roles or ClusterRoles that grant high-risk permissions, such as wildcard access or RBAC escalation verbs (bind, escalate, impersonate), which may enable privilege escalation or unauthorized access within the cluster.T1098, T1098.006↳ also matches update-roles: update roles, patch-roles: patch roles
  Investigation guide

  Triage and analysis#

  Investigating GKE Creation or Modification of Sensitive Role#

  This rule detects allowed create, update, or patch actions on Roles and ClusterRoles that introduce high-risk RBAC permissions, including wildcard access and escalation verbs like bind, escalate, or impersonate.

  Possible investigation steps#

  • Identify client.user.email, source.ip, and user_agent.original.
  • Review gcp.audit.resource_name, event.action, and gcp.audit.request for the changed role.
  • Enumerate RoleBindings or ClusterRoleBindings that reference the role and hunt for follow-on secret or exec activity.

  False positive analysis#

  • GitOps or platform bootstrap may create broad roles during onboarding. system:addon-manager patch reconciliation on built-in Roles and ClusterRoles is excluded.

  Response and remediation#

  • Revert unauthorized roles, remove unexpected bindings, and restrict RBAC change permissions to governed pipelines.
• GKE Sensitive RBAC Change Followed by Workload Modification source medium: Detects when the same GKE identity creates or modifies a Role or ClusterRole with high-risk permissions (wildcard access, RBAC escalation verbs, or access to secrets / privileged APIs) and also creates or patches a DaemonSet, Deployment, or CronJob within five minutes. This correlation is consistent with RBAC-based privilege escalation followed by payload deployment.T1098, T1098.006↳ also matches update-roles: update roles, patch-roles: patch roles
  Investigation guide

  Triage and analysis#

  Investigating GKE Sensitive RBAC Change Followed by Workload Modification#

  This ES|QL rule correlates two successful GKE audit behaviors from the same client.user.email within five minutes:

  1. Role or ClusterRole create/update/patch that grants high-risk permissions (wildcards, escalate / bind / impersonate, secret read, or privileged API resources such as pods/exec and serviceaccounts/token)
  2. DaemonSet, Deployment, or CronJob create or patch after the sensitive RBAC change

  Esql.rbac_to_workload_minutes is the gap from the latest sensitive RBAC event to the earliest workload modification in the lookback window.

  Possible investigation steps#

  • Review Esql.event_action_values and Esql.gcp_audit_resource_name_values for the Role/ClusterRole and workload objects touched.
  • Inspect Esql.user_agent_original_values and Esql.source_ip_values for unexpected clients or networks.
  • Check for RoleBinding or ClusterRoleBinding activity around the same identity and time window.
  • Correlate with secret access, pod exec, or token creation from the same actor.

  False positive analysis#

  • GitOps pipelines that manage both RBAC manifests and workloads in one sync cycle.
  • Platform bootstrap that patches built-in roles and reconciles addon workloads.

  Response and remediation#

  • Roll back unauthorized Role/ClusterRole and workload changes, revoke the actor's credentials, and tighten who can mutate RBAC and sensitive workloads.

Show 4 more (7 total) on the rules page

Panther #

• Kubernetes Role With Node Proxy Permissions Created source high: This detection monitors for Roles or ClusterRoles being created with permissions to access node proxy endpoints (nodes/proxy or nodes/*). These permissions allow users to access the kubelet API through the Kubernetes API server proxy, enabling privilege escalation by executing commands on nodes, accessing container logs and filesystems, and potentially escaping to the underlying host. This technique is documented by Stratus Red Team as a privilege escalation vector.T1078.004, T1562.001
• Kubernetes Role With Pod Exec Permissions Created source high: This detection monitors for Roles or ClusterRoles being created that grant permissions to exec into pods. The pods/exec subresource allows executing arbitrary commands inside containers, which can be abused for lateral movement, credential theft, or container escape. Attackers who gain RBAC modification permissions often create roles with pods/exec to establish backdoor access for executing commands across the cluster.T1021, T1078.004
• Kubernetes Role With Wildcard Permissions Created source high: This detection monitors for Roles or ClusterRoles being created with wildcard (*) permissions in resources or verbs. Wildcard permissions grant overly broad access, such as all operations on all resources, which violates the principle of least privilege. Attackers who gain RBAC modification permissions often create wildcard roles to maximize their access across the cluster without knowing specific resource names or API operations.T1078.004

Show 1 more (4 total) on the rules page

Falco #

• K8s Role Created source INFO: Detect any attempt to create a role
• ClusterRole With Pod Exec Created source WARNING: Detect any attempt to create a Role/ClusterRole that can exec to pods
• ClusterRole With Wildcard Created source WARNING: Detect any attempt to create a Role/ClusterRole with wildcard resources or verbs

Show 2 more (5 total) on the rules page

Elastic #

• Direct Interactive Kubernetes API Request by Unusual Utilities source low: This rule leverages a combination of Defend for Containers and Kubernetes audit logs to detect the execution of direct interactive Kubernetes API requests via unusual utilities. An adversary may need to execute direct interactive Kubernetes API requests to gain access to the Kubernetes API server or other resources within the cluster. These requests are often used to enumerate the Kubernetes API server or other resources within the cluster, and may indicate an attempt to move laterally within the cluster.T1059, T1059.004, T1069, T1087, T1609, T1610↳ also matches get-roles: get roles, list-roles: list roles, watch-roles: watch roles, create-roles: create roles, patch-roles: patch roles
  Investigation guide

  Triage and analysis#

  Disclaimer: This investigation guide was created using generative AI technology and has been reviewed to improve its accuracy and relevance. While every effort has been made to ensure its quality, we recommend validating the content and adapting it to suit your specific environment and operational needs.

  Investigating Direct Interactive Kubernetes API Request by Unusual Utilities#

  This rule detects interactive commands executed inside containers that use atypical utilities to hit the Kubernetes API, paired with near-simultaneous API activity on pods, secrets, service accounts, roles/bindings, or pod exec/attach/log/portforward. It surfaces hands-on-keyboard discovery and lateral movement using custom scripts that evade common tool allowlists; for example, an intruder opens a shell in a pod, uses Python to query the in-cluster API to list secrets, then triggers pods/exec to pivot into another workload.

  Possible investigation steps#

  • Identify the implicated pod, container image, and executing service account, then quickly review its RBAC bindings and effective permissions to determine blast radius.
  • Inspect the container’s interactive session context by pulling recent command lines, shell history, environment variables, and mounted service account tokens, and look for custom scripts or binaries issuing HTTP requests.
  • Correlate nearby Kubernetes audit entries tied to the same principal and pod to map accessed resources and verbs, noting any exec/attach/portforward or sensitive object interactions across namespaces.
  • Review network activity from the pod to the API server and any in-pod proxies, including DNS lookups and outbound connections, to spot nonstandard clients or tunneling behavior.
  • If suspicious, isolate the pod or node, capture runtime artifacts (e.g., process memory or HTTP client traffic), revoke and rotate the service account credentials, and verify image provenance and integrity.

  False positive analysis#

  • An operator interactively attaches to a pod and uses a Python REPL or bash with /dev/tcp to call the in-cluster API for routine troubleshooting (e.g., list pods, read ConfigMaps, or run selfsubjectaccessreviews), producing normal audit entries that match the rule signature.
  • A correlation artifact arises when two namespaces have pods with the same name: one pod starts an interactive shell while another independently performs get/list/watch calls, and the 1-second sequence keyed only on pod-name links the unrelated events.

  Response and remediation#

  • Immediately isolate the implicated pod that issued direct API calls using a nonstandard utility by applying a deny-all egress NetworkPolicy in its namespace (including to kubernetes.default.svc:443), terminating the interactive session, and scaling its owning Deployment/Job/StatefulSet to zero replicas.
  • Before teardown, capture a runtime snapshot of the container and node including the binary or script used to query the API (e.g., files under /tmp or /dev/tcp usage), shell history, environment, and the mounted service account token and CA bundle at /var/run/secrets/kubernetes.io/serviceaccount/.
  • Revoke access by removing the service account’s RoleBindings/ClusterRoleBindings, deleting all pods that mount that service account to force token rotation, rotating any Secrets and ConfigMaps that were read or created during the window, and deleting any unauthorized Jobs, CronJobs, or Deployments created by the same principal.
  • Restore workloads from a known-good image digest, re-enable the Deployment only after image scan and integrity checks pass, and monitor subsequent Kubernetes audit logs for pods/exec, portforward, and access to secrets across the affected namespaces.
  • Escalate to incident response leadership and consider cluster-wide containment if audit logs show create/patch of ClusterRoleBindings, access to secrets outside the workload’s namespace, or use of pods/exec to pivot into other nodes or system namespaces such as kube-system.
  • Harden access by enforcing least-privilege RBAC that denies pods/exec and attach for application service accounts, setting automountServiceAccountToken: false on workloads that do not need it, restricting egress to the API server with NetworkPolicies, and requiring just-in-time break-glass roles for interactive access.
• GKE Creation or Modification of Sensitive Role source medium: Detects creation or modification of GKE Roles or ClusterRoles that grant high-risk permissions, such as wildcard access or RBAC escalation verbs (bind, escalate, impersonate), which may enable privilege escalation or unauthorized access within the cluster.T1098, T1098.006↳ also matches create-roles: create roles, patch-roles: patch roles
  Investigation guide

  Triage and analysis#

  Investigating GKE Creation or Modification of Sensitive Role#

  This rule detects allowed create, update, or patch actions on Roles and ClusterRoles that introduce high-risk RBAC permissions, including wildcard access and escalation verbs like bind, escalate, or impersonate.

  Possible investigation steps#

  • Identify client.user.email, source.ip, and user_agent.original.
  • Review gcp.audit.resource_name, event.action, and gcp.audit.request for the changed role.
  • Enumerate RoleBindings or ClusterRoleBindings that reference the role and hunt for follow-on secret or exec activity.

  False positive analysis#

  • GitOps or platform bootstrap may create broad roles during onboarding. system:addon-manager patch reconciliation on built-in Roles and ClusterRoles is excluded.

  Response and remediation#

  • Revert unauthorized roles, remove unexpected bindings, and restrict RBAC change permissions to governed pipelines.
• GKE RBAC Wildcard Elevation on Existing Role source high: Flags an existing GKE Role or ClusterRole being changed (patch or update) so the effective rules become cluster-admin-like: wildcard on every API resource and wildcard on every verb. That is usually a deliberate privilege expansion, not a typo. GKE audit logs with response body capture are required so the detection reads the merged role after apply; loopback source IPs are ignored.T1098, T1098.006↳ also matches patch-roles: patch roles
  Investigation guide

  Triage and analysis#

  Investigating GKE RBAC Wildcard Elevation on Existing Role#

  Someone patched or updated a Role or ClusterRole so the stored rules grant star verbs and star resources—near cluster-admin breadth on that scope. Confirm the actor (user.email, groups), client, and non-loopback source IP; then see who can bind that role.

  Possible investigation steps#

  • Diff the role YAML before and after; list RoleBindings and ClusterRoleBindings that reference it and which subjects gained the widened access.
  • Review gcp.audit.resource_name, gcp.audit.response.rules.verbs, and gcp.audit.response.rules.resources.
  • In the same window, check secret reads, exec, and further RBAC changes from the same identity.

  False positive analysis#

  • Approved GitOps or vendor upgrades sometimes widen a known ClusterRole; allowlist stable automation when documented.

  Response and remediation#

  • Revert the role, drop unexpected bindings, rotate credentials for the actor, and block future wildcard RBAC outside governed pipelines (policy-as-code, PR-only RBAC).

Show 6 more (9 total) on the rules page

Panther #

• Kubernetes System Role Modified or Deleted source critical: This detection monitors for modifications or deletions of system ClusterRoles/Roles (those starting with "system:"). These are built-in Kubernetes roles for control plane components like kube-scheduler, kube-controller-manager, and system:admin. Tampering with system roles can break cluster functionality, create privilege escalation backdoors, or disable security controls. Legitimate modifications to system roles are extremely rare outside of cluster upgrades.T1078.004, T1098, T1222↳ also matches patch-roles: patch roles, delete-roles: delete roles

Falco #

• System ClusterRole Modified/Deleted source WARNING: Detect any attempt to modify/delete a ClusterRole/Role starting with system↳ also matches create-roles: create roles, patch-roles: patch roles, delete-roles: delete roles

Elastic #

• Direct Interactive Kubernetes API Request by Unusual Utilities source low: This rule leverages a combination of Defend for Containers and Kubernetes audit logs to detect the execution of direct interactive Kubernetes API requests via unusual utilities. An adversary may need to execute direct interactive Kubernetes API requests to gain access to the Kubernetes API server or other resources within the cluster. These requests are often used to enumerate the Kubernetes API server or other resources within the cluster, and may indicate an attempt to move laterally within the cluster.T1059, T1059.004, T1069, T1087, T1609, T1610↳ also matches get-roles: get roles, list-roles: list roles, watch-roles: watch roles, create-roles: create roles, update-roles: update roles
  Investigation guide

  Triage and analysis#

  Disclaimer: This investigation guide was created using generative AI technology and has been reviewed to improve its accuracy and relevance. While every effort has been made to ensure its quality, we recommend validating the content and adapting it to suit your specific environment and operational needs.

  Investigating Direct Interactive Kubernetes API Request by Unusual Utilities#

  This rule detects interactive commands executed inside containers that use atypical utilities to hit the Kubernetes API, paired with near-simultaneous API activity on pods, secrets, service accounts, roles/bindings, or pod exec/attach/log/portforward. It surfaces hands-on-keyboard discovery and lateral movement using custom scripts that evade common tool allowlists; for example, an intruder opens a shell in a pod, uses Python to query the in-cluster API to list secrets, then triggers pods/exec to pivot into another workload.

  Possible investigation steps#

  • Identify the implicated pod, container image, and executing service account, then quickly review its RBAC bindings and effective permissions to determine blast radius.
  • Inspect the container’s interactive session context by pulling recent command lines, shell history, environment variables, and mounted service account tokens, and look for custom scripts or binaries issuing HTTP requests.
  • Correlate nearby Kubernetes audit entries tied to the same principal and pod to map accessed resources and verbs, noting any exec/attach/portforward or sensitive object interactions across namespaces.
  • Review network activity from the pod to the API server and any in-pod proxies, including DNS lookups and outbound connections, to spot nonstandard clients or tunneling behavior.
  • If suspicious, isolate the pod or node, capture runtime artifacts (e.g., process memory or HTTP client traffic), revoke and rotate the service account credentials, and verify image provenance and integrity.

  False positive analysis#

  • An operator interactively attaches to a pod and uses a Python REPL or bash with /dev/tcp to call the in-cluster API for routine troubleshooting (e.g., list pods, read ConfigMaps, or run selfsubjectaccessreviews), producing normal audit entries that match the rule signature.
  • A correlation artifact arises when two namespaces have pods with the same name: one pod starts an interactive shell while another independently performs get/list/watch calls, and the 1-second sequence keyed only on pod-name links the unrelated events.

  Response and remediation#

  • Immediately isolate the implicated pod that issued direct API calls using a nonstandard utility by applying a deny-all egress NetworkPolicy in its namespace (including to kubernetes.default.svc:443), terminating the interactive session, and scaling its owning Deployment/Job/StatefulSet to zero replicas.
  • Before teardown, capture a runtime snapshot of the container and node including the binary or script used to query the API (e.g., files under /tmp or /dev/tcp usage), shell history, environment, and the mounted service account token and CA bundle at /var/run/secrets/kubernetes.io/serviceaccount/.
  • Revoke access by removing the service account’s RoleBindings/ClusterRoleBindings, deleting all pods that mount that service account to force token rotation, rotating any Secrets and ConfigMaps that were read or created during the window, and deleting any unauthorized Jobs, CronJobs, or Deployments created by the same principal.
  • Restore workloads from a known-good image digest, re-enable the Deployment only after image scan and integrity checks pass, and monitor subsequent Kubernetes audit logs for pods/exec, portforward, and access to secrets across the affected namespaces.
  • Escalate to incident response leadership and consider cluster-wide containment if audit logs show create/patch of ClusterRoleBindings, access to secrets outside the workload’s namespace, or use of pods/exec to pivot into other nodes or system namespaces such as kube-system.
  • Harden access by enforcing least-privilege RBAC that denies pods/exec and attach for application service accounts, setting automountServiceAccountToken: false on workloads that do not need it, restricting egress to the API server with NetworkPolicies, and requiring just-in-time break-glass roles for interactive access.
• GKE Creation or Modification of Sensitive Role source medium: Detects creation or modification of GKE Roles or ClusterRoles that grant high-risk permissions, such as wildcard access or RBAC escalation verbs (bind, escalate, impersonate), which may enable privilege escalation or unauthorized access within the cluster.T1098, T1098.006↳ also matches create-roles: create roles, update-roles: update roles
  Investigation guide

  Triage and analysis#

  Investigating GKE Creation or Modification of Sensitive Role#

  This rule detects allowed create, update, or patch actions on Roles and ClusterRoles that introduce high-risk RBAC permissions, including wildcard access and escalation verbs like bind, escalate, or impersonate.

  Possible investigation steps#

  • Identify client.user.email, source.ip, and user_agent.original.
  • Review gcp.audit.resource_name, event.action, and gcp.audit.request for the changed role.
  • Enumerate RoleBindings or ClusterRoleBindings that reference the role and hunt for follow-on secret or exec activity.

  False positive analysis#

  • GitOps or platform bootstrap may create broad roles during onboarding. system:addon-manager patch reconciliation on built-in Roles and ClusterRoles is excluded.

  Response and remediation#

  • Revert unauthorized roles, remove unexpected bindings, and restrict RBAC change permissions to governed pipelines.
• GKE RBAC Wildcard Elevation on Existing Role source high: Flags an existing GKE Role or ClusterRole being changed (patch or update) so the effective rules become cluster-admin-like: wildcard on every API resource and wildcard on every verb. That is usually a deliberate privilege expansion, not a typo. GKE audit logs with response body capture are required so the detection reads the merged role after apply; loopback source IPs are ignored.T1098, T1098.006↳ also matches update-roles: update roles
  Investigation guide

  Triage and analysis#

  Investigating GKE RBAC Wildcard Elevation on Existing Role#

  Someone patched or updated a Role or ClusterRole so the stored rules grant star verbs and star resources—near cluster-admin breadth on that scope. Confirm the actor (user.email, groups), client, and non-loopback source IP; then see who can bind that role.

  Possible investigation steps#

  • Diff the role YAML before and after; list RoleBindings and ClusterRoleBindings that reference it and which subjects gained the widened access.
  • Review gcp.audit.resource_name, gcp.audit.response.rules.verbs, and gcp.audit.response.rules.resources.
  • In the same window, check secret reads, exec, and further RBAC changes from the same identity.

  False positive analysis#

  • Approved GitOps or vendor upgrades sometimes widen a known ClusterRole; allowlist stable automation when documented.

  Response and remediation#

  • Revert the role, drop unexpected bindings, rotate credentials for the actor, and block future wildcard RBAC outside governed pipelines (policy-as-code, PR-only RBAC).

Show 6 more (9 total) on the rules page

Panther #

• Kubernetes System Role Modified or Deleted source critical: This detection monitors for modifications or deletions of system ClusterRoles/Roles (those starting with "system:"). These are built-in Kubernetes roles for control plane components like kube-scheduler, kube-controller-manager, and system:admin. Tampering with system roles can break cluster functionality, create privilege escalation backdoors, or disable security controls. Legitimate modifications to system roles are extremely rare outside of cluster upgrades.T1078.004, T1098, T1222↳ also matches update-roles: update roles, delete-roles: delete roles

Falco #

• System ClusterRole Modified/Deleted source WARNING: Detect any attempt to modify/delete a ClusterRole/Role starting with system↳ also matches create-roles: create roles, update-roles: update roles, delete-roles: delete roles

Elastic #

• GKE Service Account Modified RBAC Objects source medium: Detects write operations performed by GKE service accounts against RBAC resources (Roles, ClusterRoles, RoleBindings, ClusterRoleBindings). Service accounts typically do not manage RBAC directly; this activity may indicate token abuse or unauthorized privilege escalation.T1098, T1098.006↳ also matches create-roles: create roles, update-roles: update roles, patch-roles: patch roles
  Investigation guide

  Triage and analysis#

  Investigating GKE Service Account Modified RBAC Objects#

  This rule detects service accounts performing allowed write actions on RBAC resources. Stolen or over-privileged service account tokens can silently alter authorization to gain or retain elevated access.

  Possible investigation steps#

  • Review client.user.email, event.action, and gcp.audit.resource_name.
  • Trace the acting service account to its owning workload and inspect recent image changes or exec activity.
  • Correlate with change tickets or GitOps commits for the same RBAC object.

  False positive analysis#

  • Platform operators and GitOps controllers running in-cluster commonly create or patch RBAC objects.

  Response and remediation#

  • Revert unauthorized RBAC changes, rotate the service account credentials, and tighten RBAC for the workload.
• Kubernetes Service Account Modified RBAC Objects source medium: Detects write operations performed by Kubernetes service accounts against RBAC resources (Roles, ClusterRoles, RoleBindings, ClusterRoleBindings). Service accounts typically do not manage RBAC directly; this activity may indicate token abuse, misconfigured permissions, or unauthorized privilege escalation.T1098, T1098.006↳ also matches create-roles: create roles, update-roles: update roles, patch-roles: patch roles
  Investigation guide

  Triage and analysis#

  Disclaimer: This investigation guide was created using generative AI technology and has been reviewed to improve its accuracy and relevance. While every effort has been made to ensure its quality, we recommend validating the content and adapting it to suit your specific environment and operational needs.

  Investigating Kubernetes Service Account Modified RBAC Objects#

  This rule detects Kubernetes service accounts performing allowed write actions on RBAC resources such as Roles and RoleBindings, which is atypical because service accounts rarely administer permissions. It matters because stolen or over-privileged service account tokens can silently alter authorization to gain or retain elevated access across the cluster. An attacker commonly uses a compromised workload’s token to create or patch a binding that grants cluster-admin privileges to their service account for persistent control.

  Possible investigation steps#

  • Retrieve the full audit event and diff the before/after RBAC object to identify newly granted subjects, verbs, resources, and cluster-admin or wildcard permissions.
  • Trace the acting service account to its owning workload (Deployment/Pod) and node, then review recent image changes, restarts, exec sessions, and container logs around the event time for compromise indicators.
  • Determine whether the change is attributable to an expected controller or GitOps/CI automation by correlating with change tickets, pipeline runs, and repository commits for RBAC manifests.
  • Validate whether the service account token may be abused by checking for unusual API access patterns, source IPs/user agents, and cross-namespace activity compared to its baseline behavior.
  • Contain if suspicious by reverting the RBAC change, rotating the service account token (and any mounted secrets), and tightening the service account’s Role/ClusterRole to least privilege.

  False positive analysis#

  • A platform automation running in-cluster (e.g., a controller or CI job using a service account) legitimately applies RBAC manifests during routine deployment, upgrades, or namespace onboarding, resulting in create/patch/update of Roles or RoleBindings.
  • A Kubernetes operator or housekeeping workflow running under a service account intentionally adjusts RBAC as part of maintenance (e.g., rotating access, reconciling drift, or cleaning up obsolete bindings) and triggers allowed delete or update actions on RBAC resources.

  Response and remediation#

  • Immediately remove or quarantine the offending service account by deleting its RoleBindings/ClusterRoleBindings and restarting or scaling down the owning workload to stop further RBAC writes.
  • Revert the unauthorized RBAC object changes by restoring the last known-good Roles/Bindings from GitOps/manifests (or kubectl rollout undo where applicable) and verify no new subjects gained wildcard or cluster-admin-equivalent access.
  • Rotate credentials by recreating the service account or triggering token re-issuance, deleting any mounted legacy token secrets, and redeploying workloads to ensure old tokens cannot be reused.
  • Hunt and eradicate persistence by searching for additional recently modified RBAC objects and newly created service accounts in the same namespaces, then remove unauthorized accounts/bindings and scan the implicated container images for backdoors.
  • Escalate to incident response and cluster administrators immediately if any change grants cluster-admin, introduces * verbs/resources, or binds a service account to privileged ClusterRoles across namespaces.
  • Harden going forward by enforcing least-privilege RBAC, enabling admission controls to restrict RBAC modifications to approved identities/namespaces, and using short-lived projected service account tokens with workload identity constraints.

Panther #

• Kubernetes System Role Modified or Deleted source critical: This detection monitors for modifications or deletions of system ClusterRoles/Roles (those starting with "system:"). These are built-in Kubernetes roles for control plane components like kube-scheduler, kube-controller-manager, and system:admin. Tampering with system roles can break cluster functionality, create privilege escalation backdoors, or disable security controls. Legitimate modifications to system roles are extremely rare outside of cluster upgrades.T1078.004, T1098, T1222↳ also matches update-roles: update roles, patch-roles: patch roles

Falco #

• K8s Role Deleted source INFO: Detect any attempt to delete a role
• System ClusterRole Modified/Deleted source WARNING: Detect any attempt to modify/delete a ClusterRole/Role starting with system↳ also matches create-roles: create roles, update-roles: update roles, patch-roles: patch roles

Elastic #

• Kubernetes Multi-Resource Discovery source medium: Adversaries who land credentials in a cluster—or abuse an over-privileged token—often map the environment before exfiltration or privilege escalation. A practical first pass is to learn where workloads run, how the cluster is partitioned, and what RBAC exists at namespace vs cluster scope. Rapid get/list traffic across distinct API resource kinds that answer those questions (namespaces, workloads, roles, cluster-wide roles) is a common setup and orientation pattern for both interactive attackers and automated recon scripts. It is less typical for steady-state controllers, which usually touch a narrow set of resources repeatedly. This rule highlights that cross-resource burst from a single client fingerprint within a one-minute bucket so analysts can separate routine automation from potential discovery and permission reconnaissance ahead of follow-on actions.T1613