AI Incident Detection and Response
Related Templates
What This Requires
Extend the organization's incident response plan with AI-specific playbooks addressing prompt injection, RAG poisoning, model manipulation, data exfiltration through AI channels, and agentic system failures. Playbooks must define detection criteria, containment procedures, forensic preservation steps, and communication templates tailored to AI incidents.
Why It Matters
Traditional incident response playbooks assume network- or host-based attack vectors and lack the procedures needed to contain AI-specific threats such as persistent prompt injection, poisoned retrieval contexts, or autonomous agent misbehavior. Without AI-tailored response plans, security teams lose critical time during incidents attempting to improvise containment for unfamiliar attack patterns. Pre-built playbooks reduce mean-time-to-contain and ensure forensic evidence is preserved correctly for AI-specific artifacts.
How To Implement
Develop AI Incident Taxonomy
Create a classification scheme for AI-specific incidents covering prompt injection (direct and indirect), training and retrieval data poisoning, model theft or extraction, unauthorized autonomous actions by agentic systems, bias or safety incidents, and supply chain compromises of AI components. Map each category to severity levels using the organization's existing incident classification framework.
Build Response Playbooks
For each incident category, document step-by-step procedures covering initial detection indicators, immediate containment actions (disable model endpoint, revoke API keys, isolate RAG data store), evidence preservation (capture prompt logs, model state snapshots, retrieval context dumps), analysis procedures, and recovery steps. Include communication templates for internal stakeholders, affected users, and regulators where applicable.
Conduct Tabletop Exercises
Run at least two AI-focused tabletop exercises per year, simulating scenarios such as a prompt injection campaign exfiltrating customer data or a poisoned RAG knowledge base generating harmful advice. Include participants from security operations, AI engineering, legal, and communications. Document lessons learned and update playbooks accordingly.
Integrate with Security Operations
Ensure AI incident playbooks are loaded into the organization's SOAR platform or incident management system. Train SOC analysts on AI-specific indicators of compromise and triage procedures. Establish clear handoff procedures between L1 SOC and AI security specialists for escalated incidents.
Evidence & Audit
- AI incident taxonomy document with severity mapping
- Response playbooks for each incident category with step-by-step procedures
- Tabletop exercise reports with participant lists, scenarios, and lessons learned
- SOAR platform configuration showing AI playbook integration
- SOC analyst training records for AI-specific incident triage
- Post-incident reports from actual AI incidents (if any) demonstrating playbook usage
- Communication templates for AI incident notifications