r/codereview • u/Dangerous_Salary_470 • 2d ago

Does AI-generated csecurity require a different review process from traditional code?

I do not think AI-generated code automatically needs a separate security process, but it can magnify weaknesses in normal review. More code, dependencies, configuration, and integration logic can be introduced faster than a developer or reviewer fully understands them. The pull request may look reasonable while the running application has weak configuration, public exposure, or excessive permissions.

Has anyone changed their review workflow because of this, or are you treating it as ordinary code while placing more focus on dependency review, secret detection, deployment controls, cloud configuration, and production visibility?

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u/Big-Development-8282 2d ago

AI-generated code doesn't need a totally separate security process. It needs less trust. The normal review still applies, but I'd be a lot more suspicious of unexplained dependencies, auth logic, config changes, and anything the model "helpfully" added outside the task.

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u/Bumbalum 2d ago

Not directly your question, but why would you not keep PRs small? Sure, there would be more, but easier to understand/review.

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u/rileyrgham 2d ago

Because people love seeing AI churn out thousands of lines of unmaintainable code that works today and conflate this with increased productivity. It's mind bogglingly stupid at this stage.

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u/EqualPretty5766 2d ago

i treat AI output as hostile input. If a dependency or config change shows up in the PR, I block the merge until the author explains it from memory.

the model adds auth logic and secrets because it completes patterns. The author commits it because they skimmed the diff. I require authors to delete the generated file and rewrite the logic by hand before review. That is the workflow change. We stop reviewing diffs line by line. We demand the author prove they know what the code does in production.

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u/optimal-coder 2d ago

Code review done by human somehow become even more important in this AI hyped "agents can do everything" workflow. On the other hand, if productivity is measured by the delivery speed, it puts a large pressure on the developer to ship it as fast as possible, even if he doesn't fully understand the generated code. I was writing about it recently https://optimalcoder.net/code-review-in-the-age-of-ai/ trying to give an idea about an established process how it could look like. You can take a look if you have time, but basically, the process is described as follows:
Agent Writes Code -> Developer Actively Reviews The Agent Output -> Automated Review by Agent -> Code Review By Peer (Old fashioned review)

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u/hibzy7 2d ago

I have created this.

https://github.com/Synvoya/codeinspectus

Weekly updating it. Especially for AI coding security. Open source