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this post was submitted on 02 Nov 2026
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I think this is definitely a concern, yes.
I think it's very likely that these models are effectively being tricked into retrieving source code of projects from memory of seeing the actual source code in the biases. This is why some project are much easier to uncover than others.
They aren’t being tricked. They are doing exactly what they were designed to do
Fair fair. Ih suppose what I mean is that it's not really reverse engineering so much as it is recollecting from training samples.
I'm no expert, but if my understanding of LLMs as 'probability calculators' is correct, then if you prompted one properly to produce code which does x (a Photoshop function for example) and it had only been trained on one example of this (the Photoshop source code) it would reproduce the PS source code because that has the highest probability of that being the correct 'answer'.
This is baasically correct, though what the models actually produce is a little more randomized than that. Though, if there aren't any words that are anywhere cllose to being likely to follow next, then there won't be a any other valid options to choose.