Gradient Immunity: Null-Space Resistance to Malicious Fine-Tuning
Released aligned large language models remain vulnerable to malicious downstream finetuning. Existing defenses are largely designed for the fine-tuning-as-a-service (FTaaS) paradigm or rely on downstream users to follow additional safety procedures, and therefore do not directly address the setting we study: a provider controlled partially protected open-weight (PPOW) release setting in which most weights remain trainable while a small safety-critical component is preserved at release. We propose a Unidirectional Safety Gate (USG), instantiated as a Null Space Cubic Layer together with an Inverse Adapter inserted after the final Transformer layer. During downstream fine-tuning, the cubic ...
| Authors | Yuxuan Huang, Xingyu Zeng, Tianhang Zheng et al. |
|---|---|
| Primary category | cs.CR |
| Published | 5 August 2026 |
| Last updated at source | 5 August 2026 |
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