Teams building with AI code generators ship fast. Sometimes too fast. At Inithouse, we built Audit Vibe Coding because we kept running into the same problem across our own portfolio: the code worked, the demo looked right, but underneath there were security gaps, missing meta tags, uncached assets, and accessibility violations that no one caught until a real user hit them.
According to GitHub's 2025 developer survey, over 97% of developers have used AI coding tools at work. The code ships, but who checks what the AI actually generated? Here is how teams use Audit Vibe Coding to answer that question, step by step.
What the audit covers
Audit Vibe Coding scores five areas of a vibecoded project:
- Security: exposed API keys, missing CSP headers, injectable inputs, auth bypasses
- SEO: missing or duplicate meta tags, broken canonical URLs, sitemap gaps, render-blocking resources
- Performance: uncompressed images, excessive bundle size, layout shifts, slow server response
- Accessibility: missing alt text, broken ARIA roles, insufficient color contrast, keyboard traps
- Code quality: unused imports, duplicated logic, missing error boundaries, inconsistent naming
Each area gets a numeric score. The report lists every issue it found, ranked by severity, with a concrete fix for each one.
Step 1: Submit your project URL
Go to auditvibecoding.com and paste the URL of your deployed project. No account, no signup. The audit runs against the live site.
This works for any frontend deployed anywhere: Vercel, Netlify, Lovable, Cloudflare Pages, a raw VPS. If the browser can load it, the audit can scan it.
Step 2: Get the scored report
The audit returns a report broken into the five areas listed above. Each section lists specific issues with:
- What was found (e.g., "Image
/hero.pngis 2.4 MB, no compression") - Why it matters (e.g., "Adds ~3s to initial load on mobile")
- What to fix (e.g., "Convert to WebP, add
loading='lazy'")
Issues are sorted by impact. The critical ones (open auth endpoints, missing HTTPS redirects, XSS vectors) come first. Cosmetic items like inconsistent variable naming come last.
Step 3: Fix in priority order
Most teams work through the report top-down. The first 5-10 fixes tend to cover the bulk of the risk. A typical vibecoded project (say, a React SPA built in Cursor or Lovable) usually surfaces 15-30 findings, with 3-5 critical or high-severity items.
Security and performance issues are the most common. AI generators are good at making things render correctly but tend to skip hardening: rate limiting, input sanitization, proper caching headers, CSP policies.
Step 4: Re-audit after fixes
After applying fixes, run the audit again to verify. The scored comparison shows what improved and what is still open. Some teams run the audit as part of their deploy checklist: one pass before launch, one after the first week of real traffic.
When does this matter most
Three situations come up repeatedly.
Shipping an MVP built with AI tools. The code works locally, the demo is convincing, but no one has reviewed what the AI actually generated. The audit catches what a manual code review would, but faster and focused specifically on the five areas that break production apps.
Handing off a vibecoded project to a client. Agencies building with AI generators need a way to prove the output meets professional standards. The scored report serves as documentation: here is what we checked, here is where the project stands.
Internal tools built by non-engineers. Product managers and designers are increasingly building internal dashboards and workflows with AI. These tools often skip security review entirely because they are "just internal." The audit catches the exposed endpoints and missing auth that make "just internal" a real liability.
What we learned running audits across our own projects
At Inithouse, we ship a growing portfolio of products built with AI tools. We built Audit Vibe Coding because we needed it ourselves first. Running audits across our own projects surfaced patterns: AI-generated code almost always ships with at least one exposed environment variable path, at least one image over 1 MB, and almost never includes a Content Security Policy.
These are not hard problems to fix. They are just invisible until someone checks. That is the point of the audit: making the invisible checklist visible, scored, and actionable.
Audit Vibe Coding is built by Inithouse. Try it on your next vibecoded project.
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