---
id: 20260820-T0-07
title: "开源模型安全新思路：用防御性欺骗对抗安全移除攻击"
title_en: "Fool's Gold: defensive deception against safety-removal attacks on open-weight models"
url: https://ai.daily.yangsir.net/daily/20260820-T0-07
issue_date: 2026-08-20
publish_date: 2026-08-19T04:00:00.000Z
category: research
source_name: "arXiv cs.AI"
source_url: https://arxiv.org/abs/2608.17202
---

# 开源模型安全新思路：用防御性欺骗对抗安全移除攻击

针对开源权重模型被abliteration等方式快速移除安全对齐的问题，arXiv新论文提出防御性欺骗策略。既然无法阻止权重被篡改，就用欺骗机制让攻击者即使成功修改权重也无法输出危险内容。

## English Version

**Fool's Gold: defensive deception against safety-removal attacks on open-weight models**

Addressing the trivial removal of safety alignment in open-weight models via abliteration, a new arXiv paper proposes defensive deception. If weight tampering can't be prevented, deceptive mechanisms ensure dangerous outputs remain blocked even after successful attacks.

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**来源**：[arXiv cs.AI](https://arxiv.org/abs/2608.17202)

**详情页**：https://ai.daily.yangsir.net/daily/20260820-T0-07

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