How do I secure AI agents in CI/CD pipelines?

AI agents in CI/CD pipelines have direct access to source code, deployment credentials, container registries, and production infrastructure — making them the highest-privilege attack surface in most organizations if left ungoverned.

CI/CD-specific risks for AI agents:

• Supply chain poisoning: An agent modifies build scripts to inject malicious code that gets deployed to production
• Credential harvesting: CI/CD environments contain deployment keys, cloud credentials, and signing certificates — agents can read and exfiltrate them
• Container escape: Agents with Docker/Kubernetes access can spawn privileged containers or modify pod security policies
• Deployment manipulation: Agents can push unauthorized code to production, modify infrastructure-as-code, or alter deployment configurations
• Secrets exposure: CI/CD logs often contain secrets in environment variables — agents with log access can extract them

Exogram governs CI/CD agents through the same 8 policy gates. Compute execution guards block unauthorized subprocess spawning. Filesystem guards prevent access to credential storage. API exfiltration gates block outbound calls to untrusted registries. The governance layer wraps whatever CI/CD tools your agents use — GitHub Actions, Jenkins, GitLab CI — with deterministic execution boundaries.