DevSecOps Forensics & Incident Response
Evidence Architecture, Investigation Playbooks, and AI Agent Forensics
Most DevSecOps teams can deploy fast. Few can answer 'what happened?' when something goes wrong — because they never built the evidence architecture required for that answer. This volume solves that problem at the infrastructure level, before incidents occur.
The evidence architecture chapter is the book's foundation: structured logging requirements for CI/CD systems (build events, deployment events, access events), artifact provenance chains, immutable audit trails, and the Evidence Architecture Pipeline pattern that automatically collects and preserves forensic artifacts as a side effect of normal pipeline operations. By the time you're done, every deployment will generate a chain of custody record you can use in a legal proceeding.
18 investigation playbooks across six domains — Pipeline Compromise, Supply Chain Breach, Container Escape, Credential Theft, Insider Threat, and AI Agent Misbehavior — each structured as a decision tree: start here, pivot based on what you find, document as you go. Each playbook includes the specific log queries, forensic commands, and artifact preservation steps for the most common cloud platforms (AWS, GCP, Azure) and CI systems (GitHub Actions, GitLab CI, Jenkins).
The AI agent forensics chapter introduces the Five Questions Framework: What did the agent intend? What tools did it call? What data did it access? What did it output? Was it manipulated? With the implementation guide for building agent session recording, action log schema, and the reconstruction pipeline that answers those questions from raw logs.
Four concrete capabilities you will have
Build the Evidence Architecture Pipeline: automatic forensic artifact collection and immutable chain-of-custody records as a side effect of your normal CI/CD process
Run 18 structured investigation playbooks across six domains — from pipeline compromise to AI agent misbehavior — with platform-specific log queries and artifact preservation steps
Implement the Forensics Readiness Score (FRS) maturity model: assess your current evidence posture and generate a gap analysis against FRS Level 3
Apply the Five Questions Framework to AI agent incidents: build the session recording and action log infrastructure that makes post-incident reconstruction possible
The idea behind Volume VI
5 parts · 20 chapters
Part I — Evidence Architecture
Forensic evidence requirements for CI/CD systems, the Evidence Architecture Pipeline pattern, structured logging schema for build and deployment events, artifact provenance chains, immutable audit trail implementation (AWS CloudTrail, GCP Audit Logs, Sigstore Rekor), and chain of custody documentation.
Part II — Investigation Playbooks: Pipeline and Supply Chain
Seven playbooks covering CI/CD pipeline compromise (credential theft, runner hijack, cache poisoning) and supply chain breach (malicious package, compromised build tool, insider-modified artifact). Each playbook includes detection queries, timeline reconstruction, and evidence preservation commands.
Part III — Investigation Playbooks: Infrastructure and Identity
Six playbooks covering container escape, cloud credential abuse, lateral movement, and privilege escalation. Includes the cloud forensics toolkit for AWS, GCP, and Azure: disk imaging from snapshots, memory acquisition from running containers, and network flow log reconstruction.
Part IV — AI Agent Forensics
Agent session recording architecture, the action log schema for LLM tool calls, the Five Questions Framework implementation, reconstruction pipeline from raw logs, and five case studies of AI agent incidents with full investigation walkthroughs.
Part V — Forensics Readiness and Governance
The Forensics Readiness Score (FRS) maturity model across five levels, FRS assessment rubric and gap analysis template, legal hold automation, law enforcement liaison protocols, and integrating forensics readiness into your existing DevSecOps maturity program.
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