You Built It in a Weekend. Take 10 Minutes to Secure It.
AI coding tools are incredible. You describe what you want, and Cursor, Bolt, Lovable or Replit Agent builds it. In a weekend you have a working SaaS product with authentication, a dashboard, payment processing and a deployment pipeline.
What you do not have is security. AI coding tools optimize for making features work, not for making them safe. Every vibe coded application we have audited at Sherlock Forensics has had critical vulnerabilities.
These seven prompts will not replace a professional security audit, but they will catch the most dangerous issues before you ship. Copy each one, paste it into your AI coding tool and fix what it finds. Ten minutes per prompt could save you from a data breach.
For the full library of 25+ prompts covering every security category, visit our AI Security Prompt Library.
Prompt 1: Authentication Audit
Authentication is the front door of your application. AI tools build login flows that look complete but miss critical security requirements. This prompt catches the gaps.
Review my authentication implementation for security vulnerabilities. Check for: plaintext password storage (must use bcrypt/scrypt/argon2 with cost factor >= 10), missing rate limiting on login endpoints, JWT tokens without expiration or with expiration longer than 24 hours, session tokens that persist after logout, password reset links that do not expire within 1 hour, and missing CSRF protection on login forms. List each issue found with severity (critical/high/medium) and the exact code change needed to fix it.Why this matters: We find plaintext or weakly hashed passwords in over 60% of vibe coded applications. If an attacker gets your database, every user's password is immediately compromised.
Prompt 2: Authorization Check
The most dangerous vulnerability in vibe coded apps is not broken authentication. It is missing authorization. The app checks whether someone is logged in but never checks whether they should access the specific resource they requested.
Review all API endpoints in my application for authorization vulnerabilities. For each endpoint check: does it verify the authenticated user has permission to access the specific resource requested (not just that they are logged in), does it prevent horizontal privilege escalation (User A accessing User B's data by changing an ID), does it prevent vertical privilege escalation (regular user accessing admin endpoints), and are all sensitive operations protected by authentication? List every endpoint with its current authorization status and the fix needed.Why this matters: Broken access control has been the number one vulnerability on the OWASP Top 10 since 2021. In vibe coded apps, it is trivially exploitable by simply changing an ID parameter in a URL.
Prompt 3: Secrets Scanner
AI tools put API keys wherever is fastest. In vibe coded apps, that usually means client-side JavaScript that ships to every browser.
Search my entire codebase for hardcoded secrets, API keys and credentials. Look for: strings that match API key patterns (sk_, pk_, key_, token_, secret_), database connection strings with embedded passwords, AWS access keys (AKIA...), private keys or certificates stored in code, .env files committed to the repository, and any configuration files that contain credentials. For each finding, show the file, line number and a secure alternative using environment variables.Why this matters: An attacker can find your Stripe, OpenAI or Supabase keys in seconds using browser developer tools. Once they have them, they can charge your accounts, access your data and impersonate your application.
Prompt 4: SQL Injection Detection
Every vibe coded app we have tested with a relational database has at least one SQL injection vulnerability. AI tools generate database queries using string concatenation because it is the fastest way to build a working query.
Audit all database queries in my application for SQL injection vulnerabilities. Find every query that uses string concatenation or template literals to include user input. Replace each one with parameterized queries or prepared statements. Also check for: NoSQL injection in MongoDB queries, ORM misuse that bypasses parameterization, and any raw query functions that accept user-controlled input. Show the vulnerable code and the fixed version side by side.Why this matters: A single SQL injection vulnerability can give an attacker full access to your database. They can read, modify or delete every record.
Prompt 5: Security Headers
Security headers are free protection that AI tools almost never configure. They instruct browsers to enable built-in defenses against XSS, clickjacking and content sniffing.
Review my deployment configuration for security issues. Check that: debug mode is disabled in production, error messages do not expose stack traces or internal paths, source maps are not deployed to production, environment variables are used for all secrets (none hardcoded), the deployment uses HTTPS with a valid certificate, HTTP Strict Transport Security (HSTS) is enabled, and the server returns security headers including Content-Security-Policy, X-Frame-Options, X-Content-Type-Options and Referrer-Policy. Show me the exact configuration needed for my hosting platform.Why this matters: Without security headers, your users are vulnerable to clickjacking, XSS and man-in-the-middle attacks, even if your application code is otherwise secure.
Prompt 6: Dependency Verification
AI tools hallucinate package names. Attackers register the fake names with malicious code. This is a real, active attack vector.
Audit all dependencies in my package.json (or requirements.txt or composer.json). For each dependency check: does this package actually exist on the official registry (npm, PyPI, Packagist), is the package name spelled correctly (check for typosquatting), does the package have a reasonable number of downloads and a maintained repository, are there any known vulnerabilities reported in the package (check npm audit, pip-audit or similar), is the version pinned to avoid unexpected updates, and are there any packages that could be replaced with built-in language features? Flag any suspicious or unnecessary dependencies.Why this matters: Installing a hallucinated or typosquatted package can give an attacker code execution on your server and every machine that builds your project.
Prompt 7: Error Handling Review
AI tools leave debug mode enabled because it helps during development. When you deploy to production, those detailed error messages become a roadmap for attackers.
Review my application's error handling for information disclosure vulnerabilities. Check that: production error responses return generic messages (not stack traces, file paths or database schemas), API errors return consistent JSON format with appropriate HTTP status codes, unhandled exceptions are caught by a global error handler, error logging captures full details server-side without exposing them to the client, database error messages are not passed through to users, and custom error pages are configured for 404, 403 and 500 responses. Show every location where detailed errors could leak to users and provide the secure error handling pattern for my framework.Why this matters: Verbose error messages reveal your database schema, file structure, framework version and internal logic. Attackers use this information to craft targeted exploits.
These Are a Start, Not a Finish
These seven prompts catch the most common and most dangerous vulnerabilities in vibe coded applications. They are a strong first pass that takes less than an hour to complete.
They are not a substitute for a professional security audit. Prompts cannot detect business logic flaws, complex authorization bypasses or architecture-level vulnerabilities that require human analysis to identify.
For the full library of 25+ prompts covering authentication, API security, database hardening, deployment, input validation, session management and more, visit our AI Security Prompt Library.
When you are ready for the thorough review, scope a vibe coding security audit starting at $1,500 CAD.