You've got a vibe-coded app. It works. Users can click things. But you have that nagging feeling that your AI coding tool skipped some important stuff. Here's how to find out in about 15 minutes.
Head to auditbuffet.com and browse the audit library. If you're not sure where to start, go with Security Headers & Basics — it's free, it's fast, and it almost always finds something.
Six audits are completely free, no account needed:
For your first run, pick one. Don't try to audit everything at once.
Each audit page has a prompt you copy to your clipboard. That's it — no SDK, no npm package, no configuration file. The prompt contains everything: the checks to run, the output format, and the scoring rules.
Paste the prompt into whatever you're already using — Claude Code, Cursor, Bolt, Windsurf, or any AI tool that can read your codebase. The audit needs access to your project files, so run it from the project root.
A few tips:
The audit output has two parts. The human-readable report is what you'll actually read — it lists every check, whether it passed or failed, and specific remediation steps for failures.
The interesting part is the scoring. Each check has a severity weight:
| Severity | Weight | Examples | |----------|--------|----------| | Critical | 10 | Missing HTTPS, no auth on admin routes, SQL injection | | Warning | 3 | Missing CSP header, no error boundary, poor color contrast | | Info | 1 | Missing meta description, no favicon, verbose console logs |
Your category score is the sum of passing check weights divided by total applicable check weights, times 100. Checks that were skipped or errored out don't count against you — they're excluded from both numerator and denominator.
The grade scale:
| Grade | Score Range | |-------|------------| | A | 90–100 | | B | 75–89 | | C | 60–74 | | D | 40–59 | | F | 0–39 |
Most AI-generated apps score between C and D on their first security audit. That's not a failing on your part — it's a failing of the tools. The point is to know where you stand.
You have two paths:
Fix first, then submit. Read the failures, fix the critical ones, re-run the audit, and submit your improved score. This gives you a cleaner baseline.
Submit first, then fix. Submit your raw score immediately, then fix issues and re-run. This gives you a visible improvement trajectory on your dashboard.
Either approach works. The benchmarking system tracks your most recent score per audit, so submitting a low initial score doesn't hurt you — it just shows progress when you improve.
The JSON telemetry block at the end of your audit output is what you submit to AuditBuffet. Go to auditbuffet.com/submit, paste the JSON, and you're done.
What you get back:
Anonymous submission is supported — no account required for a one-off check. Create a free account if you want persistent tracking.
After your first audit, here's a good sequence:
Or grab a pack. The Pre-Launch pack bundles the audits most relevant to shipping, and the SaaS Essentials pack covers the full stack for subscription apps.
The whole point is that auditing should be a normal part of building with AI tools — not an afterthought. Run early, run often, and let the scores tell you what your AI missed.