Audit AI-generated code the way an expert operator would.
Strong AI coding can be a real advantage. The risk comes from casual generation without strong prompting, verification, and production discipline. Verity reviews the system the way an experienced AI-native engineer would: as attacker, operator, maintainer, and teammate for future agents.
- You are about to launch with user data or payments
- You prompted until the app worked, but there is no reliable review loop
- Row-level security, API permissions, or admin routes feel uncertain
- The app uses generated database queries or generated webhook handlers
- You need investor, customer, or enterprise confidence
- Prioritized security findings
- Authn/authz review
- Secrets and environment review
- Input validation and injection risk review
- Webhook and payment flow review
- Dependency and deployment risk review
- Written security audit
- Risk severity and exploitability notes
- Fix-first remediation plan
- Validation checklist for launch
- Prompting and agent workflow recommendations
Is this a penetration test?
It is a security and production-readiness review. For regulated or enterprise environments, it can prepare you for a formal pentest by fixing obvious gaps first.
Do you review the workflow or only the code?
Both. Weak prompts and weak agent loops leave fingerprints in the codebase. We review the system and the way it is being built so the same problems do not keep coming back.
Do you need repository access?
Yes, for a useful audit we need code access and enough context to understand the product, data model, deployment, and integrations. Read-only access is usually enough for the first pass.
Can you fix the findings too?
Yes. Most engagements start with the audit, then continue into focused remediation for the highest-risk areas.