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AI Agent Forensic Audit
Last updated: 2026-09-24
Short answer: An AI agent forensic audit reconstructs an incident from preserved receipt chains, session records, tool results, and independent evidence. It should explain what was requested, what ran, what changed, and which parts cannot be established from the available record.
Last reviewed: 2026-09-23. This page describes a reviewable evidence pattern and does not claim an outside result without upstream confirmation.
Preserve the chain
Keep receipt IDs, timestamps, session context, canonical bytes, hashes, and verifier responses in their original form.
Reconstruct the session
Order calls and separate plans, executions, failures, retries, and confirmations.
Test the boundary
Check whether a claimed external effect has a real callback, read-back, settlement reference, or comparable upstream record.
State unknowns
A missing record or unavailable provider is an audit finding, not permission to fill the gap with a model summary.
Open a public execution receipt or call its verifier. The example reports verification_status: verified for the stored record. It is not proof of an unobserved external outcome.
Frequently asked questions
AI agent forensic audit
An AI agent forensic audit reconstructs an incident from preserved receipt chains, session records, tool results, and independent evidence. It should explain what was requested, what ran, what changed, and which parts cannot be established from the available record.
What can a verifiable receipt prove?
It can show what the execution layer recorded and what its integrity checks verify. It cannot prove an unobserved outside outcome.
How can another reviewer check the record?
Open the public receipt, compare the tool, time, result, and status, then call the verifier. Keep outside confirmations separate from the execution record.