Use Case
Gate AI releases before they merge or deploy.
AI deploy gates help engineering teams test real AI behavior and enforce policy in the release path instead of relying on a report after the fact.
Sample gate decision
AI release blocked before deploy
An AI assistant leaked protected context during testing. The attested block decision prevents deployment until remediation and retest.
A PR, preview deploy, API target, or AI workflow is ready for review.
ShakerScan tests the real web, API, or AI behavior with a selected scan profile and policy.
Findings, transcripts, and runtime artifacts are normalized into evidence.
Policy returns allow, block, or needs_approval.
CI/CD verifies the signed evidence and either proceeds, blocks, or waits for an eligible scoped approval-token workflow.
Why ShakerScan
The output is a release control, not just a report.
ShakerScan is built around release evidence: a tested target, a policy result, a verifier command, and an approval path when risk needs human review.
Signed evidence
Evidence hashes and AI Gate attestations bind the decision to the target, environment, policy, probe pack, and release scope when signing is configured.
CI-verifiable decision
GitHub Actions or the shakerscan CLI can verify that the decision matches the expected repo, commit, branch, environment, target, policy, and evidence hash.
Approval workflow
When an eligible workflow is approved, scoped approval tokens record the reason, audience, expiry, and decision path instead of bypassing the gate silently.
Checklist
Deploy gate checklist
Start with the AI surface most likely to face customer review.
Bind the gate to preview or staging before production.
Define hard-block findings and approval-required findings.
Retest after remediation and keep decision history.
Limitations
What this page does not claim
ShakerScan does not replace human security review, threat modeling, or a scoped penetration test.
AI Gate decisions depend on the configured target, probe pack, policy, scan profile, and available evidence.
Production targets require authorization, safe scope, rate limits, and operational approval.
FAQ
Is ShakerScan an AI pentesting replacement?
No. ShakerScan is a verifiable security gate for release workflows. It complements deeper manual testing by producing repeatable runtime evidence and CI-verifiable allow, block, or needs_approval decisions.
Can ShakerScan scan any target?
No. Targets must be owned by the customer or explicitly authorized. Production scans should use safe profiles, rate limits, and defined scope.