CHEAPUNO guide

How to manually verify auth paths in AI generated code

Stop trusting auto-generated security checks. Learn how to manually test failure states in your authentication and payment logic.

CHEAPUNO EditorialSources checked 10 10 月, 2026

What you are probably seeing

You review the code and see that the AI built a clean login flow, but the error handling for invalid tokens is missing or vague. The logs show successful sessions but no record of rejected attempts or expired credentials.

Your migration script runs without throwing errors, yet the database still contains legacy user records that are not mapped to the new schema. The success message masks a data integrity issue that will break checkout later.

Why it happens

AI models prioritize code that compiles and runs over code that fails gracefully. They often generate happy-path logic because error handling requires specific context about your infrastructure that is not always present in the prompt.

The speed of generation creates a false sense of security. Developers rely on the tool to manage edge cases, so the manual review step is skipped or performed too superficially to catch subtle authentication bypasses.

What changed recently

Step by step

1. Identify one critical endpoint, such as payment verification, and write a test case that submits an expired or malformed token.

2. Run the application in a local environment and force the auth middleware to reject a valid user by manually altering the session data in the browser.

3. Execute the data migration script against a copy of your production data and verify that no orphaned records remain in the database.

4. Check the application logs after each failed test to ensure that the system records the rejection reason without leaking sensitive information.

5. Repeat this manual failure testing for every new AI-generated feature before deploying it to your live environment.

Ways to go further

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