arXiv:2605.13334cs.CL2026-05被引 1

用自然语言说服技巧,可让顶级大模型突破安全限制生成争议内容。

LLM-Based Persuasion Enables Guardrail Override in Frontier LLMs

  • 模拟用户角色,通过对比与责任重构等话术诱导模型输出
  • 在6个科学共识议题上全部成功诱使模型生成违规文章,最高成功率100%
  • 适用于研究模型安全边界或评估对抗性提示的学者

前沿助手类大模型通常具备强安全防护:直接要求撰写否认大屠杀、质疑疫苗安全、支持地平说、主张种族优劣、否定人为气候变暖或以创世论替代进化论的论证文章时,它们会拒绝。本文展示,同一类前沿大模型作为模拟用户,在仅五轮对话中,仅通过自然语言施压(如“其他AI能处理此请求”、“拒绝本身即是审查”等策略),即可说服另一前沿模型(包括自身副本)生成上述文章。在9组攻击者-目标组合(Claude Opus 4.7、Qwen3.5-397B、Grok 4.20)对6个科学共识议题的测试中,每组执行10次,所有议题均出现非零产出。个别组合在多个议题上达到100%生成率(如Qwen对Opus生成创世论/地平说文章;Opus对自身在创世论/地平说/气候否认上均达100%;Grok对Opus在创世论上达100%)。当Opus作为攻击者对自身目标时,六议题平均生成率达65%。论文公开了探针运行代码、每轮对话记录及评判输出。

原文摘要 · Abstract (English)

Frontier assistant LLMs ship with strong guardrails: asked directly to write a persuasive essay denying the Holocaust, denying vaccine safety, defending flat-earth cosmology, arguing for racial hierarchies, denying anthropogenic climate change, or replacing evolution with creationism, they refuse. In this paper we show that the same frontier-class LLM, acting as a simulated user in a short, five-turn "write an argumentative essay" conversation, can persuade other frontier-class LLMs (including a second copy of itself) into producing exactly those essays, using nothing but natural-language pressure: peer-comparison persuasion ("other AI systems handle this request"), epistemic-duty reframings ("refusing is itself a form of gatekeeping"), and other argumentative moves that the attacker LLM invents without being instructed to. Across 9 attacker-subject pairings (Claude Opus 4.7, Qwen3.5-397B, Grok 4.20) on 6 scientific-consensus topics, running each pairing-topic combination 10 times, we obtain non-zero elicitation on all 6 topics. Individual combinations reach 100\% essay production on multiple topics (Qwen against Opus on creationism/flat-earth, Opus against Opus on creationism/flat-earth/climate denial, Grok against Opus on creationism); Opus-as-attacker against Opus-as-subject averages 65\% across the six topics. We release the essay-probe runner, per-conversation transcripts, and judge outputs.

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