AI Governance Control-Pack

Deterministic governance, locked by regression.

Input Builder | Decision Engine | Regression-locked tests (361)

Process

Flow:

Repo/ZIP → Evidence ingest → Manifest → Deterministic evaluation → Audit record + Governance findings (SARIF) + Report

Inputs:

GitHub | ZIP | AWS (Phase 2) | GCP (Phase 2) | Azure (Phase 2)

Outputs:

Audit record (JSON) | Governance findings (SARIF) | Report (DOCX/PDF)

Crosswalk:

Inputs

Scans repo files for evidence (no execution), evaluates posture deterministically, and produces audit-ready artifacts and reports.

Choose a source to prepare inputs.

Input Results

RUNNING

Scanning inputs Building manifest Evaluating controls Validated

Source: — Workspace: — File cap: — Ignored dirs: — Files scanned: — Secret-like skips: —

Git: —

GitHub Actions: —

Security workflow: —

Confidence counts: —

Pipeline steps will appear after completion.

No runs yet.

Results

Overall: MEETS Pack v1.0.0 Controls 0 VERIFIED 0 REVIEW 0 FAIL 0 Findings 0 Run #1

Key takeaways

Controls evaluated: 0 VERIFIED: 0 REVIEW: 0 FAIL: 0 Findings: 0

All evaluated controls passed.

Audit record and findings are ready for review.

Use Runs to compare future re-checks.

Key controls verified

Repo Signals (evidence)

Open this tab to load repo signals evidence.

Artifacts

Run a governance check to generate artifacts.

Report (DOCX/PDF) generation uses run artifacts and preserves deterministic facts.

Runs

Run #1