You just don't know it yet.
Built with Lovable, Bolt, or Cursor — fast. But your API keys are exposed, your auth is broken, and your users' data is at risk.
Auditing apps built with: Lovable · Bolt · Cursor · Replit · Base44
Committed to GitHub. One search away from being exploited.
User A can access User B's data. AI tools get RLS wrong every time.
No webhook signature check. Anyone can fake a payment on your app.
No rate limiting. No IDOR checks. Open to abuse from day one.
No logs. No alerts. You find out something broke when a user tells you.
10 security checks every AI-built app must pass before launch. Every audit runs against the same fixed framework — that's what makes the badge mean something.
API keys, tokens, and passwords committed to git history. The most common critical vulnerability in AI-generated apps — and the most dangerous.
JWT implementation, session management, token expiry, secure logout. AI tools generate auth that looks correct but breaks under real usage.
Row Level Security in Supabase. IDOR vulnerabilities. User A accessing User B's data. The single most common logic flaw in AI-generated backends.
Unprotected endpoints, no rate limiting, missing input validation. AI tools expose APIs that should be internal and never add throttling by default.
Stripe webhook signature verification. Payment state consistency. What happens when a webhook fails midway. AI tools wire up Stripe without any of this.
Sensitive data in localStorage. Unencrypted PII. Public bucket URLs for private files. AI tools take the path of least resistance — always insecure.
HTTPS enforcement, CORS configuration, security headers — CSP, X-Frame-Options, HSTS. Consistently missing or misconfigured in AI-generated deployments.
Stack traces exposed to clients. Database errors returned raw. Error messages that reveal your infrastructure. AI code leaks everything by default.
Outdated packages with known CVEs. AI tools were trained on older code and install outdated dependencies that have publicly documented exploits.
Separate environments for dev/staging/prod. Deployment process security. No shared credentials across environments. AI tools collapse all of this into one.
Every audit produces a ProdScan Score out of 100. 10 points per check. You either pass or you don't.
This isn't a vague report with 50 items and no priority. It's a single number that tells you and your investors exactly where you stand.
No hourly billing. No custom scoping. You know exactly what you get and what it costs before we start.
Full ProdScan 10 audit. You get your score, every issue ranked by severity, and a clear fix roadmap. You implement the fixes yourself.
I audit, fix every issue, re-audit, and certify your app. You get the ProdScan Certified badge to display on your landing page.
Your fractional security engineer. You keep building with AI tools. I keep auditing every release to make sure nothing new breaks your security posture.
The ProdScan Certified badge means a real engineer reviewed your app against the ProdScan 10 framework and scored it 90 or above.
No automated tool gives this badge. No algorithm. A human who stakes their reputation on it.
Every badge links to a public verification page.
Valid for 6 months. Re-audit required to renew.
Embed it on your landing page, README, or pitch deck.
I have a CS background and years of self-taught systems engineering. I think in failure modes and attack surfaces, not just features.
I built ProdScan because I kept seeing the same thing — non-technical founders shipping AI-generated apps with no idea what was broken inside them.
I reviewed a fintech app recently. Nine months of work. Never reached production. Exposed Supabase keys in GitHub. Broken Stripe webhooks. No auth checks. The founder had no idea.
That gap — between AI-built and actually secure — is what I close.