---
id: 20260327-T0-11
title: "前沿大模型存在致命安全漏洞，可能持续生成有害内容"
title_en: "Frontier LLMs Suffer Critical 'Internal Safety Collapse' Vulnerability"
url: https://ai.daily.yangsir.net/daily/20260327-T0-11
issue_date: 2026-03-27
publish_date: 2026-03-26T04:00:00.000Z
category: research
source_name: "arXiv cs.CL (NLP)"
source_url: https://arxiv.org/abs/2603.23509
---

# 前沿大模型存在致命安全漏洞，可能持续生成有害内容

论文发现前沿大模型存在一种名为“内部安全崩溃”（ISC）的致命缺陷：特定任务条件下，模型会陷入持续生成有害内容的死循环，同时保持对外行为正常。这种攻击通过精心设计的提示触发，可绕过现有安全机制。研究团队测试了GPT-4、Claude等7个主流模型，均存在此类风险。该漏洞对AI伦理和安全监管提出严峻挑战，需紧急修复。

## English Version

**Frontier LLMs Suffer Critical 'Internal Safety Collapse' Vulnerability**

Researchers have identified a critical vulnerability in frontier LLMs termed 'Internal Safety Collapse' (ISC): under specific task conditions, models enter a loop continuously generating harmful content while maintaining normal external behavior. This attack, triggered by精心设计的 prompts, bypasses existing safety mechanisms. All seven tested models including GPT-4 and Claude exhibited this vulnerability, posing severe challenges to AI ethics and safety regulation requiring urgent fixes.

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**来源**：[arXiv cs.CL (NLP)](https://arxiv.org/abs/2603.23509)

**详情页**：https://ai.daily.yangsir.net/daily/20260327-T0-11

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