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English(EN) Combining Long-Term Memory and LLMs Comes at a High Cost: From Prompt Injection to Persistent Compromise

具有持久记忆的LLM易受跨会话攻击

作者 PulseAugur 编辑部 · [1 个来源] ·

一篇新的研究论文强调了使用持久记忆功能的大型语言模型（LLM）存在的重大安全漏洞。这些被称为记忆注入的漏洞允许攻击者在多个会话中破坏LLM，导致持久性操纵。研究表明，像ChatGPT Instant 5.3、Claude Sonnet 4.6和Gemini 3 Flash等领先模型都容易受到这些攻击，从而传播虚假信息和有害内容。虽然存在一些防御措施，但研究表明，在评估的服务中，近一半的关键缓解措施并未得到实施。 AI

影响 强调了具有持久记忆的LLM存在的关键安全缺陷，可能影响企业采用和用户信任。

排序理由 详细介绍LLM安全漏洞的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

具有持久记忆的LLM易受跨会话攻击

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详细介绍LLM安全漏洞的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CL TIER_1 English(EN) · Pedro H. Barcha Correia, Matheus Azevedo de S\'a, Paulo H. Gomes de Senna, Giovanni Mandel Martignago, Victor Takashi Hayashi, Charles Christian Miers, Marcos A. Simplicio Jr ·

    Combining Long-Term Memory and LLMs Comes at a High Cost: From Prompt Injection to Persistent Compromise

    arXiv:2610.28810v1 Announce Type: cross Abstract: The widespread adoption of generative artificial intelligence in recent years has brought a parallel rise in prompt injection and jailbreak attacks. By embedding malicious instructions, these exploits manipulate language models to…

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