Architecture in Practice / AI Governance

A Validation Gate for AI-Discovered Findings

A practical five-check architecture worksheet for ai governance, covering trust boundaries, ownership, evidence and exception decisions.

This practitioner worksheet translates a security architecture concern into a short, repeatable decision process. It is deliberately vendor-neutral and should be adapted to local operational constraints.

Purpose and scope

Use this review when deciding whether a control protects the boundary between Read-only repository and Human-approved remediation. The goal is a documented, testable decision rather than a checklist completed for its own sake. Confirm asset ownership and process impact before changing a production environment.

Conceptual architecture · Trust-boundary design
Exposure: Unverified agent conclusion crosses change boundary
Conceptual architecture, not an incident reconstruction. Flow moves from source through a controlled trust boundary to a destination. Trade-off: Discovery breadth versus validation capacity. No client environment or sensitive topology is depicted.

Five decision checks

  1. Require a minimal reproducer and affected version before declaring confirmation.
  2. Separate reproduced exploitability from hypothetical impact and environmental assumptions.
  3. Assign one of Confirmed, Disproven or Rejected with an evidence trail.
  4. Keep analysis tooling read-only by default; prohibit unreviewed merges or deploys.
  5. Link every accepted finding to a reviewer, owner, remediation plan and retest result.

Evidence to retain

Keep an inventory entry, a named business or technical owner, a documented authorization decision, and a record of test results. Capture evidence for Human disposition and least-privilege agent scope and demonstrate that unverified agent conclusion crosses change boundary is either prevented, detected or constrained. If a system cannot be tested safely, note that limitation and obtain an operational risk decision rather than treating absence of evidence as success.

Escalation and exception rule

Escalate when the chosen control could interrupt critical services, expose sensitive data or depend on unverified assumptions. A valid exception specifies affected assets, compensating monitoring, owner, expiry and the action that closes it. The principal trade-off is discovery breadth versus validation capacity; neither side should be treated as automatically dominant.

Suggested review cadence

At implementation, capture the baseline and the intended authorization boundary. At the first operational checkpoint, verify access logs and unexpected denials. At the next change window, re-evaluate exceptions and re-run the negative test. These are review prompts rather than universal intervals or service-level guarantees.

Sources and confidence

Primary source: Google Threat Intelligence Group, Agentic Source Code Review. These sources support the attributed signal. All architecture controls, comparisons and proposed review timelines are independent analytical recommendations, not claims that the cited organization implemented them.

Practical architecture worksheet; it is not a claim of measured outcomes, an incident advisory or a substitute for local engineering validation.