ClearGlass Long Read · AI Forensics

Shadow AI incidents become unprovable faster than most teams realize.

The real risk is not only unauthorized AI use. It is discovering the incident after the evidence needed to reconstruct it has already rolled over, disappeared, or never been collected.

Published August 7, 2026·9-minute read·Free source
Selected interview

Shadow AI incident response begins with logs that may already be gone

Publisher
Help Net Security
Published
July 28, 2026
Format
Interview with Brandy Wityak, VP of Complex Matters at LevelBlue
Access
Free
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The useful idea

The strongest point is brutally practical: the evidence window starts closing immediately. Firewall logs can roll over, endpoint memory can be overwritten, and organizations often discover that the logs they assumed existed were never retained at all.

ClearGlass assessment

You cannot investigate what you never recorded. AI governance without forensic readiness is policy theater.

The evidence window is a countdown

T+0
Secure the endpoint.

Preserve the user device and volatile evidence before normal activity destroys context.

T+MIN
Freeze relevant logs.

Preserve firewall, proxy, DNS, identity, endpoint, DLP, browser, API gateway, and SaaS audit events before retention policies erase them.

T+HRS
Reconstruct data movement.

Determine what left the organization, through which AI service, under whose identity, and from which system.

T+DAYS
Build the defensibility record.

Document what controls existed, what failed, what compensating controls were used, and why decisions were made.

Four controls that make AI incidents investigable

RetentionKeep security and AI-access logs long enough to survive delayed discovery.
IdentityBind users and agents to attributable identities across AI workflows.
TelemetryCapture destination, time, data path, prompt context where lawful, and resulting actions.
PreservationPredefine legal-hold and incident-preservation procedures before an event occurs.

The goal is not maximal surveillance. The goal is evidence proportional to risk, with clear retention, access controls, and privacy boundaries.

Regulators care whether controls actually function

A policy page in a wiki does not prove governance. What matters is whether the organization took reasonable technical and organizational measures, documented why controls existed or did not exist, and can show that decisions were followed through.

Operational test

If a known AI risk was documented but never remediated, that record can become evidence of neglect. The answer is not less documentation. It is stronger governance that converts documented risk into owned, time-bound action.

ClearGlass implementation moves

  • Define an AI evidence schema: identity, endpoint, destination, model/service, timestamp, data classification, action, and outcome.
  • Set retention by risk: critical AI-access and egress logs should not disappear before realistic incident discovery windows.
  • Automate preservation: trigger log export and endpoint isolation when shadow-AI indicators cross defined thresholds.
  • Track governance debt: every deferred control needs an owner, compensating measure, deadline, and review date.
  • Test the process: run tabletop exercises where responders must prove what happened using only retained evidence.