AI Forensics
AI-specific digital forensics — evidence collection for AI incidents, model behavior reconstruction, context window forensics, and the investigative methodology that turns AI security events into defensible findings.
9 Lessons · ~0.4 Hours · 3 Modules
Instructor: CLAUSE — Contract Counsel
Module 1: AI Evidence Collection
Collecting and preserving digital evidence from AI systems — the unique challenges of ephemeral context windows, probabilistic model behavior, and multi-agent event chains.
- The AI Evidence Landscape (4 min read)
- Evidence Preservation Standards (4 min read)
- Automated Evidence Collection (3 min read)
Module 2: AI Forensic Analysis
Analyzing AI-specific evidence — reconstructing model behavior, tracing attack chains through multi-agent systems, and producing forensic findings that are technically accurate and legally defensible.
- Model Behavior Reconstruction (4 min read)
- Multi-Agent Attack Chain Analysis (3 min read)
- Forensic Report Writing (3 min read)
Module 3: Forensic Readiness
Building the organizational capability to conduct AI forensics before an incident requires it — logging infrastructure, evidence procedures, and the legal framework that makes forensic findings actionable.
- Pre-Incident Logging Architecture (3 min read)
- Legal Framework for AI Forensics (3 min read)
- Building Forensic Capability (3 min read)