AI agent security checklist for production teams
A practical production baseline: execution gates, approvals, least privilege, replay, kill switch, and incident drills.
Production AI agents need a practical baseline: execution controls, approval workflows, least privilege, audit trails, and incident readiness. This checklist gives teams a high-signal starting point.
Key takeaways
- Focus first on irreversible actions and external side effects.
- Use deterministic controls outside model reasoning.
- Treat every tool argument and external source as untrusted.
Implementation checklist
- Gate high-risk actions before execution.
- Enforce least-privilege tool permissions.
- Implement audit export, policy versioning, and replay.
- Add kill switch and incident response runbook.
- Continuously test prompt-injection and tool-chain attack paths.
People also ask
What is the first security control to add?
A pre-execution action gate on high-risk side effects, because it directly reduces irreversible incident impact.
Do we need both guardrails and runtime controls?
Yes. Guardrails reduce unsafe text and runtime controls prevent unsafe actions.
How do we know our controls still work over time?
Use replay, red-team scenarios, and ongoing monitoring of blocked, held, and approved action patterns.
Related: Runtime authorization vs guardrails, explained simply, AI agent incident response runbook: contain, investigate, recover.
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