🚀 Why Prompts Beat Checklists
Every developer knows about the OWASP Top 10, but let’s be honest — most of us don’t check it every time we write code.
That’s where AI coding tools (Cursor, Lovable, Claude, Codex CLI) come in. With the right prompts, your AI becomes a real-time security reviewer, spotting vulnerabilities and rewriting fixes in your framework of choice.
Here’s the 10-prompt playbook you can copy-paste into your AI tool to make your app hack-resilient by design.
🛡️ 1. Input Validation & Injection Protection
Prompt:
Review this endpoint for SQLi/NoSQLi risk. Highlight where untrusted user input touches DB queries. If raw SQL or operators are interpolated, rewrite using parameterized queries (e.g., $1 placeholders in Postgres, ORM filters in Django/Rails, or prepared statements in Mongo/Mongoose). Add schema validation with Joi/Zod/NestJS DTOs before DB calls. Show both the insecure and the corrected version.Use it in AI tools:
Cursor/Lovable: Paste endpoint → AI highlights injection risks → returns secure ORM/params fix.
Claude: Drop controller file → get secure refactor suggestions.
🔑 2. Session & Authentication Security
Prompt:
Check this auth/session logic. Ensure access tokens are short-lived (<15m) and refresh tokens are rotated with jti replay detection. Store tokens in HttpOnly + Secure + SameSite cookies. Show example fixes in my stack (Express/NestJS/Django/Rails). If localStorage is used for JWT, rewrite to HttpOnly cookie storage.Use it in AI tools:
Cursor: Run on
auth.js→ see JWT moved into HttpOnly cookies.Codex CLI: Pipe file in → patched session logic out.
🔒 3. CSRF Protection
Prompt:
Scan this code for CSRF exposure. If it uses cookies for auth, inject anti-CSRF tokens, enforce SameSite=Strict, and verify Origin/Referer headers on money-sensitive routes. Add middleware in Express (csurf), Django ({% csrf_token %}), or Rails (protect_from_forgery). Show how an attacker could exploit it, then show a secure fix.Use it in AI tools:
Cursor: Audit all POST routes in one sweep.
Lovable: Paste checkout code → get CSRF token integration.
⚡ 4. XSS & CSP
Prompt:
Check if this code renders untrusted HTML. If you see dangerouslySetInnerHTML, safe, or raw, sanitize with DOMPurify (React/Next.js), Bleach (Django), or Rails’ sanitize helper. Escape by default. Add a strict Content Security Policy (default-src 'self'; script-src 'self'). Output the attack payload, the vulnerable render, and the corrected safe code.Use it in AI tools:
Cursor: Highlight React component → AI swaps in DOMPurify.
Claude: Paste template → AI enforces escaping.
🌐 5. Transport Security
Prompt:
Confirm this app enforces HTTPS. If Express, enable trust proxy + redirect. If Rails/Django, set force_ssl or SECURE_SSL_REDIRECT. Add HSTS headers (max-age=31536000; includeSubDomains; preload). Show the config snippet for Nginx/Express/Rails/Django. Flag any downgrade or mixed content risks.Use it in AI tools:
Codex CLI: Feed in
nginx.conf→ get hardened version.Claude: Paste
server.js→ see auto HTTPS redirect added.
🔐 6. Account Hardening
Prompt:
Audit password handling. Ensure hashing uses Argon2id (Node), PBKDF2 (Django), or bcrypt (Rails). Enforce ≥12 chars, rate-limit login attempts, and add 2FA option. Show insecure example (MD5, no rate-limit) and corrected version with secure hashing + express-rate-limit/Nginx rate-limits.Use it in AI tools:
Cursor: Run on login code → AI replaces MD5 with Argon2id.
Lovable: Adds express-rate-limit middleware automatically.
📡 7. WebSockets Security
Prompt:
Check this WebSocket connection. If tokens are passed in query strings, replace with auth field in the handshake and verify JWT + Origin on connect. Reject if Origin mismatch or token invalid. Show example exploit (leaked query token) and secure fix for Express/Socket.io or Rails Action Cable.Use it in AI tools:
Cursor: Patch socket handshake logic inline.
Lovable: Suggests origin check middleware.
🔑 8. Secrets Management
Prompt:
Scan this repo for hardcoded secrets (API keys, DB creds, JWT secrets). If found, rewrite to use platform secrets/KMS (AWS SSM, GCP Secret Manager, Vault, Vercel/Netlify/Heroku env vars). Add rotation guidelines. Never log secrets. Show an example of insecure vs secure key usage.Use it in AI tools:
Claude: Run on repo dump → flags all secrets.
Codex CLI: Suggests KMS-backed env usage.
👀 9. Detection & Response
Prompt:
Instrument this app for detection. Log failed logins, rate-limit triggers, refresh token replay (jti mismatch), and CSP violation reports. Pipe logs to ELK/Datadog. Show example Express middleware for logging anomalies + alert triggers. Suggest automated responses (force logout, 2FA step-up, alert Slack/PagerDuty).Use it in AI tools:
Cursor: Insert middleware template → instantly log brute-force attempts.
Lovable: Adds Slack alert hooks.
🚨 10. High-Impact Attack Scan
Prompt:
Check this code for high-risk patterns: shell exec with user input (→ command injection), sendFile with untrusted path (→ path traversal), missing frame-ancestors (→ clickjacking), server-side fetch with arbitrary URLs (→ SSRF). Show the insecure example, attacker payload, and fixed version.Use it in AI tools:
Cursor/Lovable: Full-file scan → AI red-flags dangerous APIs.
Codex CLI: Pipe utilities → get hardened replacements.
💡 How to Use This Playbook
Cursor/Lovable → Paste snippet → run prompt → secure rewrite inline.
Claude → Paste whole service/controller → AI returns attack+fix examples.
Codex CLI → Pipe code files (
cat auth.js | codex --prompt "Session security") → get patched output.
Think of these as “security super-linters”. Instead of waiting for a pentest, you get real-time attack→fix insights as you code.
🙋♂️ FAQ
Q: Do frameworks already protect me from most attacks?
Yes, but only if you don’t bypass safeguards (e.g., raw, safe, dangerouslySetInnerHTML). These prompts catch exceptions.
Q: Do I need all 10 prompts?
Pick based on features. WebSockets prompt for chat apps, CSRF prompt for fintech flows, etc.
Q: Why not just use static security scanners?
Scanners flag issues, but prompts give attack payloads + framework-specific fixes — context you can apply instantly.
Potential Gaps
False positives / over-generalization: AI tools may misinterpret context; prompts might suggest fixes that don’t align perfectly with specific app architecture or requirements.
Performance & complexity trade-offs: Some “secure” suggestions (e.g. very strict CSP, lots of token/rotation logic) could add complexity or affect performance or user experience; sometimes security vs usability trade-offs are glossed over.
Framework nuance & legacy code: Many projects have legacy patterns or older codebases; integrating fixes might require large refactors. The prompts assume somewhat clean structure.
Coverage of certain attacks: While high-impact attack scan covers many issues, there might be more advanced or domain-specific attacks not covered (e.g. GraphQL specific issues, supply chain attacks, etc).
Over-reliance on tools / prompts: While prompts are good, developers still need domain knowledge to judge suggestions; also, AI tools can be misused or produce insecure code if prompts are bad.
Check the Video overview →
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