{
  "id": 4188,
  "url": "https://arxiv.org/abs/2605.17413v1",
  "title": "Ablating Safety: Mechanisms for Removing Alignment in Language Models for Security Applications",
  "summary": "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-c",
  "authors": "Isaac David, Arthur Gervais",
  "category": "research",
  "topics": "regulation,safety-alignment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-05-17T12:18:20.000Z",
  "fetched_at": "2026-07-14T16:30:50.570Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/4188",
  "original_url": "https://arxiv.org/abs/2605.17413v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}