AI Cyber Defense / Cloud, Kubernetes and software supply chain
AI Cyber Defense: Monitor secret-manager access as a privileged data event
Scope secrets to workload purpose and alert on unusual retrieval combinations. Rotate affected secrets according to dependent-service needs when access is confirmed unauthorized.
Environment and inputs: Cloud control planes, workload identity, Kubernetes clusters, CI/CD pipelines and immutable deployment artifacts; provider support varies.
Scenario and goal
An attacker may retrieve legitimate secrets through authorized APIs after compromising an overprivileged workload.
Why it matters
For this scenario, an attacker can automate permitted API operations after gaining a workload or pipeline identity. Review who can change trust, who can assume the resulting identity and what resources it can reach. Keep source review, build provenance, deployment authorization and runtime permissions as distinct checks. A configuration object or successful deployment does not prove the intended runtime boundary is enforced.
Evidence to collect
Collect secret identifier, requesting principal, version, access time and subsequent target-service authentication without logging the secret value.
Validate with an authorized exercise
Use test secrets to compare expected workload access with an unrelated identity request; confirm denials and that rotation updates the authorized consumer without leaking values.
Rollout and checks
Evaluate effective permissions and runtime behavior in a disposable account or namespace before production rollout. Retain the approved source revision, resulting artifact and independent audit trail. Plan recovery if identity, policy or admission dependencies fail. Reconcile running assets after the change because resources created outside the normal pipeline can otherwise remain outside its checks.
Scope and limits
This guide proposes a defensive test; it is not a tested production design. Check platform support and local requirements. References explain the mechanisms but do not certify the design. Behavior alone does not prove AI involvement.