- cross-posted to:
- programming@kbin.social
- ai_infosec
- cross-posted to:
- programming@kbin.social
- ai_infosec
From https://twitter.com/llm_sec/status/1667573374426701824
- People ask LLMs to write code
- LLMs recommend imports that don’t actually exist
- Attackers work out what these imports’ names are, and create & upload them with malicious payloads
- People using LLM-written code then auto-add malware themselves
I wouldn’t trust the packages used by an LLM, or any other part of code they write, or any other text response they generate. Everything must be treated skeptically and verified!
I use ChatGPT daily to assist with my job as a fullstack web developer. If I’m asking it for boilerplate code, I already know exactly what it should look like, and having ChatGPT generate the code and then proofreading it myself is usually a small timesaver. And even if it’s not, the lower perceived effort on my part is beneficial for my mental load.
When I ask it for code where I don’t already know the ‘right’ answer (e.g. refactoring an algorithm to use loops instead of recursion, example for library with poor documentation, creating new function from scratch), I always write a series of test cases to ensure the code behaves as expected.
Similarly if it suggests a library I am unfamiliar with, I’ll check it’s github or stats on npmjs to verify it’s maintained and commonly used. Though it almost always picks the same library that I had picked previously (when one of my previous projects was in a similar situation). Probably because those libraries were the most commonly used. I never experienced a made up import; however, there were a couple instances where it made up a function that did not actually exist inside of the library.