ToolPilot

AI Output Sanitizer

Check AI-generated code, HTML, SQL, and shell commands for security issues before running them. Detects injection, unsafe patterns, hallucinated packages, and malformed output.

Paste AI-generated code

Why You Should Sanitize AI-Generated Code Before Running It

AI models generate code that looks correct but can contain subtle security vulnerabilities. SQL injection, XSS in HTML, shell command injection, and unsafe file operations are common in AI output — especially when the AI hallucinates library functions or misunderstands security contexts.

Our AI Output Sanitizer scans code and text generated by any AI model for security issues across multiple languages: HTML (XSS, script injection, dangerous attributes), SQL (injection patterns, DROP/TRUNCATE), shell commands (command chaining, dangerous operations like rm -rf), JavaScript (eval, innerHTML, prototype pollution), and JSON (structural validation).

It also flags potential hallucinations: references to npm packages, Python modules, or API endpoints that may not exist. AI models frequently invent plausible-sounding but nonexistent libraries — running `npm install` on these can expose you to typosquatting attacks.

Use it as a safety net between AI generation and execution. Paste the AI's output, get an instant security report, and fix issues before they reach production. All analysis runs client-side — your code never leaves your browser.

Frequently Asked Questions

What languages does it check?▾
HTML, SQL, shell/bash, JavaScript/TypeScript, and JSON. Each has language-specific security checks tailored to common AI generation mistakes.
Does it catch all vulnerabilities?▾
No — it catches common patterns like injection, unsafe operations, and obvious hallucinations. For production security, combine with proper code review, static analysis tools (ESLint, Semgrep), and penetration testing.
What are hallucinated packages?▾
AI models sometimes invent library or package names that don't exist (e.g., `npm install python-helper-utils`). Attackers can register these names and publish malicious code — a real supply-chain attack vector called dependency confusion.
Can AI agents use this tool?▾
Yes. The tool is available via MCP and REST API. Agents can call it to validate their own output before presenting it to users — a built-in safety check.

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