How do I implement an AI agent incident response plan?

An AI agent incident response plan defines how your organization detects, contains, investigates, and recovers from AI agent security incidents — and the window between detection and containment must be seconds, not hours, because agents can execute hundreds of actions per minute.

AI agent incident response phases:

1. Detection (seconds): Automated alerts from policy violations, anomalous behavior patterns, or rate threshold breaches
2. Containment (seconds): Kill switch activation — freeze the agent's namespace to prevent further actions while preserving state for investigation
3. Investigation (minutes-hours): Forensic analysis of the Trust Ledger to trace the exact sequence of actions, identify root cause, and determine blast radius
4. Eradication (hours): Fix the vulnerability — update policy rules, patch the agent code, rotate compromised credentials
5. Recovery (hours-days): Restore from the last known good state (SHA-256 verified), re-enable the agent with updated policies
6. Lessons learned: Update governance policies and red team procedures based on the incident

Exogram accelerates every phase. Detection: Real-time policy violation alerts. Containment: One-click namespace kill switch. Investigation: Complete Trust Ledger with every action, state hash, and policy evaluation. Recovery: State verification via SHA-256 ensures you're restoring to uncompromised state.