authentication-authorization-vulnerabilities-ai-code

Authentication vulnerabilities in AI code often include insecure password storage (MD5 hashing), missing session expiration, and weak token validation. Scan for plaintext passwords, lack of bcrypt hashing, absent session timeouts, and authorization checks that can be bypassed to detect the most common flaws.

Use bcrypt for password hashing instead of MD5 or plaintext storage. Bcrypt automatically handles salting and is resistant to brute-force attacks. Apply it during user registration and verification, never log or transmit passwords, and validate input before hashing.

Enforce session expiration, regenerate session IDs after login, use secure token-based activation, and validate sessions on every request. Remove hardcoded timeouts, implement logout functionality, and store session data server-side rather than trusting client-supplied tokens.

Implement role-based access control (RBAC) with explicit permission checks before granting resource access. Validate user roles on every request, avoid relying solely on client-side checks, and ensure authorization logic runs server-side and cannot be circumvented.

AI models may prioritize functionality over security best practices, generating code with plaintext passwords, missing input validation, or incomplete session handling. These flaws create common vulnerabilities like unauthorized access and credential exposure that require manual review and remediation.

Yes, authentication and authorization vulnerabilities are framework-agnostic patterns. The vulnerability detection and secure remediation apply to authentication flows, password handling, session management, and access-control logic regardless of language or framework.