AI Cyber Defense / Cloud, Kubernetes and software supply chain
AI Cyber Defense: Investigate serverless events across asynchronous boundaries
Restrict event producers and validate authorization again before sensitive downstream actions. Use idempotent processing for events that can be delivered repeatedly.
Environment and inputs: Cloud control planes, workload identity, Kubernetes clusters, CI/CD pipelines and immutable deployment artifacts; provider support varies.
Scenario and goal
An intruder can trigger downstream work through a queue or event bus without a direct application request.
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
Join producer identity, message identifier, queue policy, function invocation and resource action with replay and retry context.
Validate with an authorized exercise
Send a harmless event twice in staging and verify one business effect; confirm an unauthorized producer cannot publish to the protected input and each decision is traceable.
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.