SECURITY AUDIT CHECKLIST FOR AI-GENERATED APPS | VIBEEVAL

Pre-Launch Security is Critical

AI-generated applications often ship with security vulnerabilities that could have been caught with a proper audit. A comprehensive security audit before launch prevents costly breaches and protects your users.

Complete Security Audit Checklist

Follow these 12 steps for a thorough security audit. Critical items must be addressed before launching to production.

Authentication security review

Verify password policies, MFA implementation, session management, and account recovery mechanisms are secure.

Authorization and access control

Test that users can only access authorized resources and check for privilege escalation vulnerabilities.

Input validation audit

Review all input fields for SQL injection, XSS, command injection, and other injection attack vectors.

API security assessment

Audit API authentication, rate limiting, input validation, and response data exposure.

Cryptography review

Verify secure hashing algorithms, encryption at rest and in transit, and key management practices.

Third-party dependency scan

Identify vulnerable dependencies, outdated libraries, and packages with known CVEs.

Security headers verification

Check for CSP, HSTS, X-Frame-Options, and other security headers to prevent common attacks.

Error handling review

Ensure error messages do not leak sensitive information like stack traces or database details.

Logging and monitoring audit

Verify security events are logged, sensitive data is not logged, and monitoring is configured.

Data privacy compliance

Review GDPR, CCPA, or relevant data privacy regulations compliance in data handling practices.

File upload security

Test file upload functionality for path traversal, malicious file execution, and unrestricted file types.

Infrastructure security review

Audit deployment configuration, secrets management, firewall rules, and infrastructure hardening.

Common Audit Findings

Hardcoded Credentials

API keys, passwords, or tokens stored directly in source code or configuration files.

Missing Rate Limiting

Endpoints lack rate limiting, allowing brute force attacks or resource exhaustion.

Insecure Dependencies

Using libraries with known vulnerabilities or outdated packages with security patches available.

Verbose Error Messages

Error messages expose internal system details, database structure, or stack traces.

Related Resources

Penetration Testing Guide

Learn manual penetration testing for AI-generated apps

Code Security Scanning

Implement automated code security analysis

API Security Testing

Comprehensive API security testing methodology

Common Security Flaws

Most common vulnerabilities in AI-generated code

Automate Your Security Audit

VibeEval automates many security audit checks, helping you identify vulnerabilities faster. Get comprehensive security analysis designed specifically for AI-generated applications.