[New] Kubernetes Service Account Token Created via TokenRequest API

[Samirbous]

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, and cloud provider managed identities (EKS, AKS, GKE) that routinely create tokens for pod lifecycle management.

[github-actions]

Rule: New - Guidelines

These guidelines serve as a reminder set of considerations when proposing a new rule.

Documentation and Context

• Detailed description of the rule.
• List any new fields required in ECS/data sources.
• Link related issues or PRs.
• Include references.

Rule Metadata Checks

• creation_date matches the date of creation PR initially merged.
• min_stack_version should support the widest stack versions.
• name and description should be descriptive and not include typos.
• query should be inclusive, not overly exclusive, considering performance for diverse environments. Non ecs fields should be added to non-ecs-schema.json if not available in an integration.
• min_stack_comments and min_stack_version should be included if the rule is only compatible starting from a specific stack version.
• index pattern should be neither too specific nor too vague, ensuring it accurately matches the relevant data stream (e.g., use logs-endpoint.process-* for process data).
• integration should align with the index. If the integration is newly introduced, ensure the manifest, schemas, and new_rule.yaml template are updated.
• setup should include the necessary steps to configure the integration.
• note should include any additional information (e.g. Triage and analysis investigation guides, timeline templates).
• tags should be relevant to the threat and align/added to the EXPECTED_RULE_TAGS in the definitions.py file.
• threat, techniques, and subtechniques should map to ATT&CK always if possible.

New BBR Rules

• building_block_type should be included if the rule is a building block and the rule should be located in the rules_building_block folder.
• bypass_bbr_timing should be included if adding custom lookback timing to the rule.

Testing and Validation

• Provide evidence of testing and detecting the expected threat.
• Check for existence of coverage to prevent duplication.

[Aegrah]

LGTM, ran the query across my lab telemetry and 0 hits.