How to Detect AI-Generated Code in Any Repo

As AI coding assistants become more capable, the "code dump" — where a developer ships hundreds of lines of AI-generated code they didn't write and don't understand — is becoming a major source of technical debt.

The 5 Dead Giveaways:

1. The "Perfect Comment" Syndrome: AI models love to explain the obvious. If you see "// Increments the counter" above a simple "count++", it's likely AI.

2. Hallucinated Utilities: Models often use high-level helper functions that don't exist in the current scope, or try to import from nonexistent files.

3. Perfect Formatting, Odd Logic: Humans make small formatting mistakes or leave inconsistent indentation. AI is perfectly uniform, but will sometimes write a complex loop for a task that has a built-in library method.

Detection isn't just about intuition; it's about spotting specific, non-human patterns in the code's DNA. Humans write code in bursts. We pause, we refactor, we leave small inconsistencies that make sense in context. AI is perfectly uniform. It follows a mathematical distribution of tokens that no human can replicate naturally.

At VibeFix, we look at "Structural Entropy" — the ratio of boilerplate to logic. AI code often has a low entropy, meaning it's too repetitive to be hand-written by a thoughtful developer.

If you don't know code was AI-generated, you can't properly review the risks. High-quality AI code is fine; unvetted AI junk is a security and maintenance ticking time bomb.