LookAhead Defense limits dormant poisoning in language and multimodal agents
Original title: Defending Against Dormant Poisoning Attacks Across Language and Multimodal Agents
On the authors' tests, harmful agent behavior fell from as high as 93.9% to at most 14.2% versus vanilla fine-tuning.
A paper studies dormant poisoning that stays hidden at release and appears after benign fine-tuning of language and multimodal agents. The authors report that activated harmful behaviors can extend to unseen actions and that several behaviors can be triggered together. LookAhead Defense builds a Safety Buffer from the released model's own responses and penalizes updates predicted to weaken safety. They say it also cuts harmful language-model responses and remains effective against other poisoning methods.
Unconfirmed: Reported reductions are the authors' experimental results, not an independent evaluation.
- Harmful language-model responses fell from up to 92.5% to at most 2.0%.
- The defense does not require external safe responses or a trusted clean model.
- It penalizes updates that weaken safety or raise refusals on benign buffer versions.
- Authors report competitive utility and low over-refusal.
From the original article
1 min read at arxiv.orgRecent work shows that attackers can implant dormant malicious behaviors that remain hidden at release but emerge after benign fine-tuning. As foundation models are used as agents, whether dormant poisoning extends to harmful agent actions and multimodal settings remains unclear.
By Wonjun Lee · arxiv.org
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