A unified adaptive attack exploits the common weakness across 15 defenses against malicious fine-tuning, showing they only obscure rather than remove harmful model capabilities.
Ctrap: Embedding collapse trap to safeguard large language models from harmful fine-tuning
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One Step to the Side: Why Defenses Against Malicious Finetuning Fail Under Adaptive Adversaries
A unified adaptive attack exploits the common weakness across 15 defenses against malicious fine-tuning, showing they only obscure rather than remove harmful model capabilities.
- Token Buncher: Shielding LLMs from Harmful Reinforcement Learning Fine-Tuning