AI-generated authentication is a security incident waiting to happen

Authentication is a system-level concern that touches every layer of your application — and AI tools generate it as if it's a feature you bolt on. The typical AI-generated auth flow creates a login form, sends credentials to an endpoint, stores a JWT in localStorage, and checks for its existence on protected pages. This pattern has at least four critical vulnerabilities that the AI will never flag: localStorage is accessible to any XSS attack, JWTs without proper rotation and revocation give attackers permanent access, password comparison without constant-time equality checking leaks timing information, and client-side route protection without server-side verification means your API is wide open.

The deeper issue is that AI tools learn from millions of tutorial-quality auth implementations — and tutorials optimize for understanding, not security. They skip refresh token rotation because it's complex to explain. They store tokens in localStorage because it's simpler than HttpOnly cookies. They hash passwords with bcrypt but use a cost factor of 4 instead of 12. Each shortcut is reasonable in a tutorial context but catastrophic in production. The AI has no way to distinguish between 'code that teaches a concept' and 'code that protects real users.'

OAuth flows expose another failure mode entirely. AI tools can generate the redirect-to-provider step, but they consistently botch the callback handling — failing to validate the state parameter (enabling CSRF attacks on your login flow), not checking email verification status from the provider, and creating race conditions when the same email exists across multiple OAuth providers. The result is an auth system that lets attackers link their Google account to someone else's existing account.