AI Incident Response: A Complete Playbook

When an AI agent is compromised or behaves unexpectedly, traditional incident response playbooks may not apply. AI systems require specialized detection, containment, and recovery procedures. This playbook provides a framework for handling AI-related security incidents.

AI Incident Categories

Not all AI incidents are the same. Understanding the category helps determine response priorities:

Category	Description	Severity	Response Time
Active Exploitation	Attacker actively using compromised agent	Critical	Immediate
Data Breach	Sensitive data exposed through agent	Critical	< 1 hour
Safety Bypass	Agent producing harmful outputs	High	< 4 hours
Anomalous Behavior	Unexpected but not clearly malicious	Medium	< 24 hours
Performance Degradation	Quality or reliability issues	Low	< 72 hours

Detection Signals

High-Confidence Indicators

These signals warrant immediate investigation:

Definite Compromise:

• Agent accessing resources outside normal scope
• Unusual tool call patterns (frequency, parameters)
• Data exfiltration attempts detected
• Known attack patterns in logs

Probable Compromise:

• Multiple failed attempts followed by success
• Sudden behavior changes
• Requests for credentials or sensitive data
• Attempts to escalate privileges

Low-Confidence Indicators

These may indicate issues but require context:

Possible Issues:

• Increased error rates
• Latency spikes
• User complaints about responses
• Unusual topic patterns

Response Phases

Phase 1: Detection & Triage

Immediate Actions (0-15 minutes):

1. Verify the Alert

   • Confirm the incident is real (not false positive)
   • Review raw logs and evidence
   • Identify affected systems/users

2. Initial Classification

   • Determine incident category
   • Assess potential impact scope
   • Identify affected data types

3. Notify Stakeholders

   • Alert incident response team
   • Notify management if high severity
   • Prepare for potential escalation

Phase 2: Containment

Goal: Stop the bleeding without destroying evidence.

Containment Options by Severity:

Severity	Primary Action	Secondary Action
Critical	Kill switch - disable agent entirely	Isolate affected systems
High	Restrict to read-only operations	Enable enhanced logging
Medium	Rate limit operations	Increase monitoring
Low	Flag for review	Document behavior

Containment Checklist:

• Affected agent identified
• Containment action selected
• Containment implemented
• Verification that containment is effective
• Evidence preservation initiated
• Timeline documentation started

Phase 3: Investigation

Evidence Collection:

Gather and preserve:

• Complete conversation logs
• Tool invocation history
• Input/output pairs
• System metrics and telemetry
• User reports and complaints
• Configuration snapshots

Analysis Framework:

1. Timeline Construction

   • When did anomalous behavior start?
   • What was the first indicator?
   • What actions occurred in sequence?

2. Attack Vector Identification

   • How did the attacker gain access?
   • What prompt or input triggered the issue?
   • Was this direct or indirect injection?

3. Impact Assessment

   • What data was exposed?
   • What actions were taken?
   • Who was affected?

Phase 4: Eradication

Remove the Threat:

1. Identify Root Cause

   • Document the specific vulnerability
   • Understand how it was exploited
   • Identify any persistence mechanisms

2. Remediate

   • Patch the vulnerability
   • Update guardrails and filters
   • Strengthen relevant controls

3. Verify Fix

   • Test with known attack patterns
   • Confirm vulnerability is addressed
   • Review related areas for similar issues

Phase 5: Recovery

Restore Normal Operations:

Staged Recovery:

1. Enhanced monitoring mode
2. Limited operation (reduced permissions)
3. Gradual permission restoration
4. Full operation with monitoring

Validation Checklist:

• Vulnerability confirmed fixed
• Agent behavior tested
• Monitoring in place
• Rollback plan ready
• Stakeholders notified

Phase 6: Post-Incident

Learn and Improve:

Post-Incident Review:

• What happened?
• How was it detected?
• What worked well in response?
• What could be improved?
• What systemic changes are needed?

Documentation:

• Incident report
• Timeline of events
• Actions taken
• Lessons learned
• Recommendations

Communication Templates

Internal Alert (Critical)

CRITICAL AI INCIDENT - [Agent Name]

Time Detected: [Timestamp]
Category: [Active Exploitation / Data Breach / etc.]
Status: [Investigating / Contained / Resolved]

Summary: [Brief description]

Immediate Actions Taken:
- [Action 1]
- [Action 2]

Next Update: [Time]
Incident Lead: [Name]

Stakeholder Update

AI Security Incident Update

Incident ID: [Number]
Status: [Status]
Impact: [Description of impact]

What Happened:
[Brief, non-technical summary]

Current Status:
[What's happening now]

Next Steps:
[What will happen next]

Questions: Contact [Name] at [Contact]

Preparation Checklist

Before incidents happen, ensure you have:

Technical Readiness:

• Kill switch mechanism tested
• Logging and monitoring in place
• Evidence collection procedures
• Backup and recovery tested

Process Readiness:

• Incident response playbook documented
• On-call rotation established
• Escalation paths defined
• Communication templates ready

Team Readiness:

• Team trained on AI-specific incidents
• Tabletop exercises conducted
• Roles and responsibilities clear
• Contact information current

Key Takeaways

1. Prepare before incidents - Have playbooks, tools, and training ready
2. Detect early - Invest in monitoring and alerting
3. Contain quickly - Speed matters, but preserve evidence
4. Investigate thoroughly - Understand root cause before declaring victory
5. Learn continuously - Every incident is an opportunity to improve

AI incident response is different from traditional IR. Prepare accordingly.

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