Detects a sequence where a principal creates or modifies a Role/ClusterRole to include high-risk permissions (e.g., wildcard access or escalation verbs) and then creates or patches a workload resource (DaemonSet, Deployment, or CronJob) shortly after, which may indicate RBAC-based privilege escalation followed by payload deployment. This pattern is often used by adversaries to gain unauthorized access to sensitive resources and deploy malicious payloads.

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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.

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This rule detects a request to attach a controller service account to an existing or new pod running in the kube-system namespace. By default, controllers running as part of the API Server utilize admin-equivalent service accounts hosted in the kube-system namespace. Controller service accounts aren't normally assigned to running pods and could indicate adversary behavior within the cluster. An attacker that can create or modify pods or pod controllers in the kube-system namespace, can assign one of these admin-equivalent service accounts to a pod and abuse their powerful token to escalate privileges and gain complete cluster control.

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Detects the creation or modification of several sensitive workloads, such as DaemonSets, Deployments, or CronJobs, by an unusual user agent, source IP and username, which may indicate privilege escalation or unauthorized access within the cluster.

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Detects Kubernetes API requests where a user is impersonating a privileged cluster identity such as system:kube-controller-manager, system:admin, system:anonymous, or a member of the system:masters group. These identities have broad cluster-wide permissions including unrestricted access to all secrets, the ability to create tokens for any service account, schedule pods on any node, and modify RBAC policies. An attacker impersonating system:masters gains full cluster-admin equivalent access, while impersonating system:kube-controller-manager grants access to every secret in every namespace and the ability to mint service account tokens for lateral movement.

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Detects non-system identities using the Kubernetes nodes/proxy API to proxy requests through the API server directly to a node's Kubelet. The nodes/proxy subresource allows any principal with this RBAC permission to reach the Kubelet API on any worker node without needing direct network access or Kubelet TLS certificates. Through this proxy path, an attacker can list all pod specifications including environment variable secrets, read Kubelet configuration and PKI material, retrieve container logs, and access running pod metadata across all workloads on the target node. Monitoring and health check endpoints such as /metrics, /healthz, and /stats are excluded to reduce noise from legitimate observability tooling.

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This rule detects a container deployed with one or more dangerously permissive Linux capabilities. An attacker with the ability to deploy a container with added capabilities could use this for further execution, lateral movement, or privilege escalation within a cluster. The capabilities detected in this rule have been used in container escapes to the host machine.

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Detects allowed updates to the pods/ephemeralcontainers subresource by a non-system identity. Ephemeral containers are commonly used for debugging (kubectl debug) but can also be abused to inject tooling into a running pod, access mounted secrets, and execute commands in the target pod context. Attackers with sufficient RBAC may use ephemeral containers to escalate privileges, move laterally, or establish persistence without deploying a new workload.

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This rule detects when a pod is created with a sensitive volume of type hostPath. A hostPath volume type mounts a sensitive file or folder from the node to the container. If the container gets compromised, the attacker can use this mount for gaining access to the node. There are many ways a container with unrestricted access to the host filesystem can escalate privileges, including reading data from other containers, and accessing tokens of more privileged pods.

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This rule detects an attempt to create or modify a pod using the host IPC namespace. This gives access to data used by any pod that also use the hosts IPC namespace. If any process on the host or any processes in a pod uses the hosts inter-process communication mechanisms (shared memory, semaphore arrays, message queues, etc.), an attacker can read/write to those same mechanisms. They may look for files in /dev/shm or use ipcs to check for any IPC facilities being used.

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This rules detects an attempt to create or modify a pod attached to the host network. HostNetwork allows a pod to use the node network namespace. Doing so gives the pod access to any service running on localhost of the host. An attacker could use this access to snoop on network activity of other pods on the same node or bypass restrictive network policies applied to its given namespace.

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This rule detects an attempt to create or modify a pod attached to the host PID namespace. HostPID allows a pod to access all the processes running on the host and could allow an attacker to take malicious action. When paired with ptrace this can be used to escalate privileges outside of the container. When paired with a privileged container, the pod can see all of the processes on the host. An attacker can enter the init system (PID 1) on the host. From there, they could execute a shell and continue to escalate privileges to root.

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This rule detects when a user creates a pod/container running in privileged mode. A highly privileged container has access to the node's resources and breaks the isolation between containers. If compromised, an attacker can use the privileged container to gain access to the underlying host. Gaining access to the host may provide the adversary with the opportunity to achieve follow-on objectives, such as establishing persistence, moving laterally within the environment, or setting up a command and control channel on the host.

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Flags an existing Role or ClusterRole being changed (patch or update) to a wildcard on every API resource and verb. This may be indicative of a deliberate privilege expansion but may also be a nefarious attempt at privilege escalation.

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Detects creation, modification, or deletion of Kubernetes MutatingWebhookConfigurations or ValidatingWebhookConfigurations by non-system identities. Admission webhooks intercept every API request matching their rules before persistence, giving an attacker powerful capabilities: injecting malicious sidecars into every new pod via a mutating webhook, blocking security tooling deployments via a validating webhook, or silently exfiltrating pod specifications to an external server. Webhook manipulation is a stealthy persistence and defense evasion technique because the webhook configuration itself looks benign in kubectl output while actively modifying or intercepting all matching Kubernetes API traffic.

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This rule detects when an unauthenticated user request is authorized within the cluster via an unusual user agent. Attackers may attempt to use anonymous accounts to gain initial access to the cluster or to avoid attribution of their activities within the cluster. This rule excludes the /healthz, /livez, /version and /.well-known/oauth-authorization-server endpoints which are commonly accessed anonymously.

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Detects modifications to the aws-auth ConfigMap in Amazon EKS clusters. The aws-auth ConfigMap maps AWS IAM roles and users to Kubernetes RBAC groups, an attacker who modifies it can grant any IAM role cluster-admin access by adding a mapping to the system:masters group. This is a well-documented persistence technique that survives pod restarts, node replacements, and RBAC changes because the authentication mapping exists outside of normal Kubernetes Role objects. Modifications to aws-auth are rare in normal operations, the ConfigMap is typically set during cluster provisioning and updated only during node group or access configuration changes.

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Detects creation or approval of a Kubernetes CertificateSigningRequest (CSR) by a non-system identity. Attackers who have gained cluster access can submit a CSR with a privileged Common Name such as system:kube-controller-manager or system:masters, then approve it themselves to obtain a long-lived client certificate. Unlike service account tokens which expire in hours, client certificates persist until they expire or the cluster CA is rotated, providing durable access that survives pod termination, token revocation, and RBAC changes. On non-EKS clusters, the signed certificate allows the attacker to authenticate as the privileged identity from anywhere without needing cluster network access, making it one of the most persistent backdoor mechanisms available in Kubernetes.

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This rule detects the creation of a RoleBinding or ClusterRoleBinding that grants the cluster-admin ClusterRole, which provides unrestricted access to all Kubernetes resources and represents a high-risk privilege escalation or misconfiguration.

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Detects modifications to the CoreDNS or kube-dns ConfigMap in the kube-system namespace. These ConfigMaps control cluster DNS resolution for all pods. An attacker who modifies the CoreDNS Corefile can redirect internal service DNS names to attacker-controlled IP addresses, enabling man-in-the-middle attacks against the Kubernetes API server, database services, and other internal endpoints. Pods that resolve service names via cluster DNS will transparently connect to the attacker instead of the legitimate service, allowing interception of service account tokens, database credentials, and API traffic. DNS poisoning at the cluster level is particularly dangerous because it affects every pod in every namespace simultaneously and does not require any modification to the victim workloads. CoreDNS configuration changes are rare in normal operations and any unexpected modification should be investigated immediately.

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This rule detects the creation of RoleBindings or ClusterRoleBindings that reference a ServiceAccount, which may indicate privilege delegation or potential RBAC misconfiguration leading to elevated access.

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Detects the creation or modification of Kubernetes Roles or ClusterRoles that grant high-risk permissions, such as wildcard access or RBAC escalation verbs (e.g., bind, escalate, impersonate), which may enable privilege escalation or unauthorized access within the cluster.

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This rule detects an attempt to create or modify a service as type NodePort. The NodePort service allows a user to externally expose a set of labeled pods to the internet. This creates an open port on every worker node in the cluster that has a pod for that service. When external traffic is received on that open port, it directs it to the specific pod through the service representing it. A malicious user can configure a service as type Nodeport in order to intercept traffic from other pods or nodes, bypassing firewalls and other network security measures configured for load balancers within a cluster. This creates a direct method of communication between the cluster and the outside world, which could be used for more malicious behavior and certainly widens the attack surface of your cluster.

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This rule detects a user attempt to establish a shell session into a pod using the 'exec' command. Using the 'exec' command in a pod allows a user to establish a temporary shell session and execute any process/commands in the pod. An adversary may call bash to gain a persistent interactive shell which will allow access to any data the pod has permissions to, including secrets.

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This rule detects attempts to create, update, or patch pods by an anonymous user. An anonymous user is a user that is not authenticated or authorized to access the Kubernetes API server. Creating, updating, or patching pods is a common activity for attackers to gain access to the cluster and execute commands.

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This rule detects attempts to create resources in Kubernetes clusters that are forbidden by the authorization policy. It specifically looks for creation requests that are denied with a "forbid" decision, indicating that the user or service account does not have the necessary permissions to perform the action. This activity is commonly associated with adversaries attempting to create resources in a Kubernetes environment without proper authorization, which can lead to unauthorized access, manipulation of cluster resources, lateral movement and/or privilege escalation.

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This rule detects when a forbidden request is made from an unusual user agent in a Kubernetes environment. Adversary tooling may use non-standard or unexpected user agents to interact with the Kubernetes API, which can indicate an attempt to evade detection or blend in with legitimate traffic. In combination with a forbidden request, this behavior can suggest an adversary is attempting to exploit vulnerabilities or misconfigurations in the Kubernetes cluster.

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Adversaries who land credentials in a cluster or abuse an over-privileged token, often map the environment before exfiltration or privilege escalation. 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. This rule detects cross-resource bursts from a single client fingerprint within a one-minute bucket which may represent reconnaissance.

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Flags exec into a pod when the URL-decoded command payload resembles reverse-shell or bind-shell one-liners invocation patterns. Legitimate debug sessions sometimes use similar building blocks, but together these patterns align with post-exploitation interactive access and command-and-control.

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Detects pod or attach exec API calls where the decoded request query implies "curl" or "wget" fetching an "https" URL. Attackers with permission to exec into workloads often run one-liners to stage tooling, pull scripts or binaries, or exfiltrate data over HTTPS—activity that should be rare compared to shells, debuggers, or expected health checks. The rule decodes the audit requestURI, reconstructs a readable command string from repeated command parameters, and applies noise filters for common cluster health and OIDC/JWKS endpoints so benign automation is less likely to alert.

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This rule detects potential endpoint enumeration attempts by an anonymous user. An anonymous user is a user that is not authenticated or authorized to access the Kubernetes API server. By looking for a series of failed API requests, on multiple endpoints, and a limited number of documents, this rule can detect automated permission enumeration attempts. This behavior is uncommon for regular Kubernetes clusters.

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This rule detects potential endpoint enumeration attempts by a single user and source IP address. By looking for a combination of failed/successful API requests across multiple endpoints and a limited number of documents, this rule can detect automated permission enumeration attempts. This behavior is uncommon for regular Kubernetes clusters.

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This rule detects when a service account or node attempts to enumerate their own permissions via the selfsubjectaccessreview or selfsubjectrulesreview APIs via an unusual user agent. This is highly unusual behavior for non-human identities like service accounts and nodes. An adversary may have gained access to credentials/tokens and this could be an attempt to determine what privileges they have to facilitate further movement or execution within the cluster.

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This rule detects unusual request responses in Kubernetes audit logs through the use of the "new_terms" rule type. In production environments, default API requests are typically made by system components or trusted users, who are expected to have a consistent user agent and allowed response annotations. By monitoring for anomalies in the username and response annotations, this rule helps identify potential unauthorized access or misconfigurations in the Kubernetes environment.

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This rule detects the deletion of Kubernetes events, which can indicate an attempt to cover up malicious activity or misconfigurations. Adversaries may delete events to remove traces of their actions, making it harder for defenders to investigate and respond to incidents.

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Detects Kubernetes pod exec sessions whose decoded command line references cloud instance metadata endpoints or equivalent hostnames and paths. Workloads that reach the link-local metadata IP, AWS IMDS paths, GCP computeMetadata, Azure IMDS token routes, or encoded variants are often attempting to harvest role credentials, tokens, or instance attributes from the underlying node or hypervisor boundary. That behavior is high risk in multi-tenant and regulated environments because it can expose short-lived cloud credentials to code running inside a container. The rule classifies a coarse cloud target label and whether the string looks like credential retrieval versus lighter reconnaissance.

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Detects Kubernetes pod exec sessions whose decoded command line references high-value host or in-cluster paths and material types: mounted service account or platform tokens, kubelet and control-plane configuration areas, host identity stores, root dot-directories for cloud and kubeconfig material, common private-key and keystore extensions, process environment dumps, and configuration filenames suggestive of embedded secrets. The intent is to catch interactive or scripted access that often precedes lateral movement, privilege escalation, or credential theft from the node or workload boundary. A narrow exclusion ignores benign reads of resolv.conf. The query also labels an access_type bucket to speed triage without altering the detection predicates you validated.

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This rule detects an unusual volume of Kubernetes API get requests against multiple distinct Secret objects from the same client fingerprint (user, source IP, and user agent) within a defined lookback window. This can indicate credential access or in-cluster reconnaissance, where a user or token is used to enumerate and retrieve sensitive data such as service account tokens, registry credentials, TLS material, or application configuration. Failed get requests are also included, as they may reveal RBAC boundaries, confirm the existence of targeted secrets, or reflect automated probing activity.

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Kubernetes audit identities for kubelet (system:node:) and workloads (system:serviceaccount:) are meant to operate with tight, predictable API usage. Direct get or list on the Secrets API from those principals is often a sign of credential access. Attackers who stole a pod service-account token or node credentials sweep Secret objects for tokens, registry credentials, TLS keys, or application configuration. Even denied attempts still reveal intent to reach sensitive material. Legitimate controllers do read secrets they mount or manage, so this signal is most valuable when paired with triage (namespace scope, user agent, RBAC, and whether the identity should touch those secret names at all).

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Detects read access to Kubernetes Secrets (get/list) with a user agent matching a curated set of non-standard or attacker-leaning clients, for example minimal HTTP tooling, common scripting stacks, default library fingerprints, or distribution-tagged strings associated with offensive-security Linux images. Legitimate in-cluster automation usually presents stable, purpose-specific user agents (for example controller or client-go variants used by known components).

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Detects list operations on Kubernetes Secrets from a non-loopback client when the request URI targets cluster-wide secrets or list operations under kube-system or default. Useful for spotting broad secret enumeration from remote clients.

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Detects the creation of a Kubernetes service account token through the TokenRequest API by a non-system identity. The TokenRequest API allows users and workloads to programmatically generate short-lived tokens for any service account they have create permissions on, without accessing the filesystem or the mounted projected token. Attackers who have gained initial access to a cluster can abuse this API to mint tokens for more privileged service accounts, pivot to cloud provider resources via IRSA/workload identity, or generate long-lived tokens that persist beyond pod termination. Unlike mounted service account tokens which are detectable through file access monitoring, tokens created via the TokenRequest API leave no filesystem footprint, they are only visible in Kubernetes audit logs as a create verb on the serviceaccounts/token subresource. This rule excludes legitimate system components such as the kubelet, kube-controller-manager, EKS managed identities, and the Calico/Tigera operator that routinely create tokens for pod lifecycle management.

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Detects Kubernetes pod exec sessions whose decoded command line references cloud instance metadata endpoints or equivalent hostnames and paths. Workloads that reach the link-local metadata IP, AWS IMDS paths, GCP computeMetadata, Azure IMDS token routes, or encoded variants are often attempting to harvest role credentials, tokens, or instance attributes from the underlying node or hypervisor boundary. That behavior is high risk in multi-tenant and regulated environments because it can expose short-lived cloud credentials to code running inside a container. The rule classifies a coarse cloud target label and whether the string looks like credential retrieval versus lighter reconnaissance.

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Flags exec into a pod when the URL-decoded command payload resembles reverse-shell or bind-shell one-liners invocation patterns. Legitimate debug sessions sometimes use similar building blocks, but together these patterns align with post-exploitation interactive access and command-and-control.

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Detects Kubernetes pod exec sessions whose decoded command line references high-value host or in-cluster paths and material types: mounted service account or platform tokens, kubelet and control-plane configuration areas, host identity stores, root dot-directories for cloud and kubeconfig material, common private-key and keystore extensions, process environment dumps, and configuration filenames suggestive of embedded secrets. The intent is to catch interactive or scripted access that often precedes lateral movement, privilege escalation, or credential theft from the node or workload boundary. A narrow exclusion ignores benign reads of resolv.conf. The query also labels an access_type bucket to speed triage without altering the detection predicates you validated.

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Detects pod or attach exec API calls where the decoded request query implies curl or wget fetching an https URL. Attackers with permission to exec into workloads often run one-liners to stage tooling, pull scripts or binaries, or exfiltrate data over HTTPS—activity that should be rare compared to shells, debuggers, or expected health checks. The rule decodes the audit requestURI, reconstructs a readable command string from repeated command parameters, and applies noise filters for common cluster health and OIDC/JWKS endpoints so benign automation is less likely to alert.

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Kubernetes audit identities for kubelet (system:node:) and workloads (system:serviceaccount:) are meant to operate with tight, predictable API usage. Direct get or list on the Secrets API from those principals is often a sign of credential access. Attackers who stole a pod service-account token or node credentials sweep Secret objects for tokens, registry credentials, TLS keys, or application configuration. Even denied attempts still reveal intent to reach sensitive material. Legitimate controllers do read secrets they mount or manage, so this signal is most valuable when paired with triage (namespace scope, user agent, RBAC, and whether the identity should touch those secret names at all).

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Detects read access to Kubernetes Secrets (get/list) with a user agent matching a curated set of non-standard or attacker-leaning clients, for example minimal HTTP tooling, common scripting stacks, default library fingerprints, or distribution-tagged strings associated with offensive-security Linux images. Legitimate in-cluster automation usually presents stable, purpose-specific user agents (for example controller or client-go variants used by known components).

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Detects when secrets or configmaps are accessed, created, modified, or deleted in a Kubernetes cluster by the Azure Arc AAD proxy service account. When operations are routed through the Azure Arc Cluster Connect proxy, the Kubernetes audit log records the acting user as system:serviceaccount:azure-arc:azure-arc-kube-aad-proxy-sa with the actual caller identity in the impersonatedUser field. This pattern indicates that someone is accessing the cluster through the Azure ARM API rather than directly via kubectl against the API server. While legitimate for Arc-managed workflows, adversaries with stolen service principal credentials can abuse Arc Cluster Connect to read, exfiltrate, or modify secrets and configmaps while appearing as the Arc proxy service account in K8s audit logs. This rule uses a 5-day new-terms history window keyed on the impersonated identity and alerts the first time that Azure AD principal performs this activity.

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Detects a sequence where a principal creates or modifies a Role/ClusterRole to include high-risk permissions (e.g., wildcard access or escalation verbs) and then creates or patches a workload resource (DaemonSet, Deployment, or CronJob) shortly after, which may indicate RBAC-based privilege escalation followed by payload deployment. This pattern is often used by adversaries to gain unauthorized access to sensitive resources and deploy malicious payloads.

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