AI Security Incident Response Plan: Prepare for Prompt Injection, Data Leakage, and Model Abuse

Traditional incident response runbooks are not enough for AI systems. You must account for model-specific vulnerabilities, data pipelines, and third-party dependencies. Use this plan to adapt your security operations center (SOC) for generative AI threats and comply with emerging regulations such as the EU AI Act and NIS2.

1. Prepare: Roles, Inventories, and Detection Coverage

Document AI assets—models, datasets, prompts, vector databases, APIs, and third-party services. Map ownership across data engineering, ML, security, and product teams. Establish incident severity tiers and align with legal obligations for breach notification timelines (e.g., GDPR’s 72-hour rule). Ensure logging covers model inputs/outputs, administrative actions, and data access.

2. Identify: AI-Specific Threat Detection

Monitor for prompt injection attempts, abnormal token usage, mass export of embeddings, or sudden shifts in model behavior. Use anomaly detection to flag suspicious API usage. Leverage guidance from the CISA Secure AI Guidelines to map detection logic to known threat vectors.

3. Contain and Eradicate: Response Actions

Develop playbooks for isolating compromised components: disable affected prompts, rotate keys, revoke API tokens, or revert to safe model versions. For data exposure, initiate legal and compliance workflows immediately. For compromised third-party models, coordinate with vendors to apply fixes and verify remediation.

4. Recover: Validation, Rollback, and Communication

Validate restored systems with regression tests, synthetic transactions, and manual QA. Communicate transparently with stakeholders—internal leadership, customers, regulators—following pre-approved templates. Document impacted data subjects and maintain evidence for forensic analysis.

5. Post-Incident Review and Improvement

Run blameless postmortems. Capture root causes, detection gaps, and remediation timelines. Update guardrails—prompt filters, access controls, rate limits—and share learnings with product and legal teams. Practice incidents via tabletop exercises at least twice per year.

Frameworks and Reporting References

Ikalos AI provides incident simulation scripts, communication templates, and detection integrations to help teams operationalize this playbook.

AI Security Incident Response Plan - ikalos.ai