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This is the honest counterweight to the tutorials: a clear-eyed look at where AI-generated code quietly falls apart, from hallucinated packages to security holes a non-technical builder cannot see. It matters because you carry the liability for what you ship, even when you did not read a line of the code. Read it before you put anything with real user data in front of people.
When the Vibes Are Off: The Security Risks of AI-Generated Code
From Lawfare by Carolin Kemper
- AI often invents plausible but fake libraries, and attackers register those names to slip malware into your project (called slopsquatting).
- Code can pass basic tests and still be insecure, so looking finished is not the same as being safe.
- AI can also generate convincing security documentation for code that is not actually secure, which means you cannot outsource judgment entirely, some human review stays non-negotiable.
