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AI Incident-Response Plan and Runbook
Operational incident response plan and crisis runbook governing AI-specific emergencies: massive hallucination outbreaks, prompt injection compromises, toxic output generation, training data poisoning, unauthorized agentic tool execution, and statutory regulatory breach notifications under EU AI Act Article 73.
Crisis response runbook for containment, isolation, rollback, and regulatory reporting of AI security and hallucination incidents.
Important Tech Document Template & Operational Notice
TinyCTO.tv Tech Document Template Notice: This template is a general educational and operational starting point. It is not legal, tax, accounting, investment, procurement, regulatory, security or certification advice. Requirements vary by jurisdiction, organization, contract and risk. Review and adapt it with qualified professionals before relying on it.
Problem Solved
Traditional IT incident response playbooks assume deterministic code bugs or server hardware crashes, leaving organizations entirely unprepared when a live LLM hallucinates defamatory content, leaks customer PII, or executes rogue automated agent workflows.
When to Use
- •Managing live AI production crises (hallucination cascades, toxic outputs, intellectual property leakage)
- •Responding to successful adversarial attacks, prompt injections, or data poisoning breaches
- •Executing mandatory regulatory notifications under EU AI Act Article 73 for serious incidents within 72 hours
When NOT to Use
- •For standard network DDoS attacks and web infrastructure outages (use TPL-OPS-007)
- •For routine code defect triage and minor UI cosmetic bug fixes (use TPL-DEL-005)
5 Template Sections & Structural Outline
Categorizing incidents: Critical Sev-1 (severe hallucination with financial/legal harm, data exfiltration, rogue agent financial commits), Sev-2 (degraded accuracy, guardrail bypass without harm), and Sev-3 (minor drift).
Executing emergency containment playbooks: activating traffic diversion to static fallback models, clearing compromised vector store caches, revoking agentic API keys, and triggering inference kill-switches.
Diagnosing root causes: token-level prompt payload analysis, embedding drift detection, vector retrieval poisoning audits, and foundation model provider regression checks.
Executing rollback to known safe checkpoints: reverting system prompts, restoring clean vector database snapshots, redeploying previous fine-tuned weights, and running red-team regression suites.
Drafting comprehensive postmortem documentation, updating AI System Cards, executing EU AI Act Article 73 notification within 72 hours, and hardening guardrail rules.
Completion Instructions
Independent Review Checklist
- All mandatory sections completed
- No secrets or passwords included
- Executive sponsor sign-off obtained
AI Incident-Response Plan and Runbook - Worked Case Study
Fictional Entity: Global Financial Robo-Advisory AI Engine
Real-world production case study demonstrating complete operational adoption for Global Financial Robo-Advisory AI Engine.
- •Activated incident response protocols within 4 minutes of a high-risk RAG hallucination involving speculative stock advice
- •Executed instant traffic diversion to conservative deterministic rule models, preventing customer financial losses
- •Completed comprehensive root-cause forensics identifying poisoned financial forum embeddings, and filed Article 73 notification within 48 hours
Frequently Asked Questions
What triggers a mandatory regulatory notification under EU AI Act Article 73?
Article 73 requires providers of High-Risk AI systems to immediately report any serious incident to the relevant market surveillance authority. A serious incident includes any malfunction that leads to death or serious damage to health, disruption of critical infrastructure, breach of fundamental rights, or severe property/environmental damage. Reports must be filed within 72 hours of becoming aware.
How does containment differ between traditional software crashes and AI incidents?
Traditional software containment involves restarting crashed servers or reverting microservice code. AI incident containment requires severing agentic tool execution permissions, purging poisoned vector embeddings from RAG caches, diverting model routing to deterministic fallbacks, or freezing system prompts while underlying model inference continues safely.
What role does the AI Incident Commander play during an active hallucination outbreak?
The AI Incident Commander holds single-point operational authority to declare severity tiers, authorize emergency model kill-switches, coordinate with Legal and PR liaisons, direct engineering on rollback targets, and mandate the execution of red-team verification tests prior to service restoration.
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Authoritative Sources
- EU Artificial Intelligence Act: Article 73 Reporting of Serious IncidentsEuropean Commission • OFFICIAL REQUIREMENT
- ISO/IEC 42001:2023 Information Technology — Artificial Intelligence — Management SystemInternational Organization for Standardization • OFFICIAL REQUIREMENT
- NIST SP 800-61 Rev. 2: Computer Security Incident Handling GuideNational Institute of Standards and Technology • OFFICIAL REQUIREMENT