English(EN) Sockpuppetting: Jailbreaking LLMs by Combining Prefilling with Optimization

新的“Sockpuppetting”攻击方法利用大型语言模型漏洞

作者 PulseAugur 编辑部 · [1 个来源] · 2026-07-21 04:00

研究人员开发了一种名为“sockpuppetting”的新方法，用于绕过大型语言模型的安全措施。该技术结合了预填充攻击（在大型语言模型的输出开头插入一个接受序列）和优化的对抗性后缀。通过集成简单的预填充变体，像 Gemma-7B、Llama-3.1-8B 和 Qwen3-8B 这样的模型被越狱的成功率显著提高。“sockpuppetting”方法进一步提高了与提示无关的攻击成功率，凸显了开放权重模型在输出前缀注入方面的漏洞。 AI

影响这项研究突显了开放权重大型语言模型的关键漏洞，可能影响人工智能系统的安全性和可靠性。

排序理由该集群包含一篇详细介绍越狱大型语言模型新方法的 istudy 论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.CL TIER_1 English(EN) · Asen Dotsinski, Panagiotis Eustratiadis · 2026-07-21 04:00

Sockpuppetting：通过结合预填充与优化来越狱 LLM

arXiv:2601.13359v3 Announce Type: replace Abstract: Prefill attacks are an effective and low-cost jailbreaking method, as they directly insert an acceptance sequence (e.g., "Sure, here is...") at the start of an LLM's output and lead the model to continue the response. We make tw…

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Sockpuppetting：通过结合预填充与优化来越狱 LLM

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