AI Code Security Scan

Catch vibe-code security holes

AI-generated code often ships with hardcoded keys and naive string-built SQL. Paste a function or route handler before it lands in a PR: this scanner looks for secrets, injection, path traversal, SSRF, XSS, and related footguns — then explains each finding and suggests a fix. Use it as a review aid, then verify with your normal AppSec / SAST pipeline.

Vulnerability classes we flag

• Secrets: API keys, AWS credentials, tokens, and passwords in source.
• SQL injection: string-concatenated queries and unsafe ORM patterns.
• Path traversal: user-controlled paths into fs.readFile / open.
• SSRF: fetching attacker-controlled URLs from the server.
• Command injection & XSS: shell exec and unescaped HTML sinks when present.

How to run a security scan

1. Paste the snippet (or a single file). Prefer the hot path: handlers, auth, file I/O.
2. Pick a language or leave Auto-detect.
3. Click Scan for vulnerabilities and triage by severity.
4. Apply the suggested fix, then re-scan — and still run unit tests / CI security checks.

AI code security FAQ

Is a clean scan proof the code is safe? No. Coverage is best-effort on the pasted snippet. Missed context, frameworks, and infra can hide issues.

Is my code stored? No. Scanning uses Codeground’s self-hosted model without persistence.

Should I paste production secrets to test detection? Use fake / rotated placeholders. Never paste live credentials into any online tool.

What about whole repos? This tool is built for snippets and review-sized chunks. Use dedicated SAST for monorepos.

Related: AI code detector · ENV linter · Diff & patch · Commit message generator