AI RESEARCH
LLM Hypnosis: Exploiting User Feedback for Unauthorized Knowledge Injection to All Users
arXiv CS.LG
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ArXi:2507.02850v3 Announce Type: replace-cross We describe a vulnerability in language models (LMs) trained with user feedback, whereby a single user can persistently alter LM knowledge and behavior given only the ability to provide prompts and upvote / downvote feedback on LM outputs. To implement the attack, the attacker prompts the LM to stochastically output either a "poisoned" or benign response, then upvotes the poisoned response or downvotes the benign one.