Ablating Safety: Mechanisms for Removing Alignment in Language Models for Security Applications
Safety-aligned language models often refuse cybersecurity requests whose wording resembles misuse, even when the task is authorized and defensive. This makes security evaluation ambiguous: a failed answer may reflect missing capability or refusal-policy intervention. Ablating Safety studies alignment removal as a controlled transformation-evaluation protocol for authorized security tasks, comparing authorized-context prompting, reversible refusal-direction activation projection, representation-control projections, and LoRA-based de-alignment or task adaptation. We evaluate refusal, attempt rate, validated security success, general-capability retention, instability, and out-of-scope unsafe...
| Authors | Isaac David, Arthur Gervais |
|---|---|
| Primary category | cs.CR |
| Published | 17 May 2026 |
| Last updated at source | 17 May 2026 |
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