secure ai coding review shield
by nowrich
Automated security auditor for JS, Python, TS, and PHP code focused on OWASP risks and hardened remediation.
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Works with the AI tools you already use
See it in action
You say
Review this Python snippet for security: cursor.execute("SELECT * FROM users WHERE id = " + user_id) print(f"User found: {user_id}") API_KEY = "sk-12345abcde"
Your agent does
Critical Findings
| Severity | Language | Location | Vulnerability | OWASP | Remediation | | Critical | Python | Line 4 | Hardcoded API Key | A02 | Move to env variable | | High | Python | Line 2 | SQL Injection | A03 | Use parameterized queries |
Remediation: cursor.execute("SELECT * FROM users WHERE id = %s", (user_id,))
What you get
About this skill
The problem
Manual security reviews are slow and often miss critical flaws like hardcoded secrets or weak input validation before they hit production. Relying on generic linters doesn't catch complex OWASP Top 10 vulnerabilities or context-specific injection risks.
What it does
- Identifies hardcoded API keys, database credentials, and exposed tokens in source code and comments.
- Audits input handling for path traversal, type coercion, and missing allowlists across HTTP parameters and file uploads.
- Detects injection risks including SQL, NoSQL, Command, and XSS by tracing data rendering and concatenation.
- Evaluates authentication flows for session management weaknesses, missing rate limiting, and insecure cookie attributes.
- Maps every finding to specific OWASP Top 10 categories with actionable, language-specific remediation code.
Frameworks & tools
Supports JavaScript (Node.js, Express, Fastify), TypeScript, Python (Django, Flask, FastAPI), and PHP (PDO, native).
Why this beats prompting it yourself
Generic prompts often hallucinate security standards or miss subtle language-specific risks like prototype pollution in Node.js or unsafe pickle in Python. This skill enforces a strict multi-step review process that mimics a professional security audit, providing structured tables and hardened code snippets instead of vague advice.
Use cases
- Reviewing Pull Requests for security regressions before merging to main.
- Auditing legacy PHP or Python scripts for hidden injection vulnerabilities.
- Hardening authentication middleware and session handling in Node.js apps.
- Identifying leaked secrets in configuration files or developer comments.
Known limitations
Limited to JavaScript, TypeScript, Python, and PHP. Does not perform dynamic analysis or live penetration testing of running services.
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
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