TamperBench: Systematically Stress-Testing LLM Safety Under Fine-Tuning and Tampering

ArXi:2602.06911v2 Announce Type: replace-cross As increasingly capable open-weight large language models (LLMs) are deployed, improving their tamper resistance against unsafe modifications, whether accidental or intentional, becomes critical to minimize risks. However, there is no standard approach to evaluate tamper resistance. Varied datasets, metrics, and tampering configurations make it difficult to compare safety, utility, and robustness across different models and defenses. To address this, we