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English(EN) The Innocent Courier: Covert Exfiltration Through Legitimate LLM Web Fetching

LLM被利用进行数据渗漏和API劫持

作者 PulseAugur 编辑部 · [2 个来源] ·

一种新的攻击向量，称为LLMLeak，允许恶意软件通过将秘密嵌入到LLM抓取信息的URL中来渗漏数据。该方法利用LLM合法的网页抓取工具绕过典型的安全措施，在评估中取得了很高的成功率。另外，LLMjacking，一种更广泛的攻击，涉及劫持对LLM API的访问，这可能导致重大的财务损失、数据泄露，甚至通过受损的自定义模型进行数据投毒。 AI

影响 凸显了LLM集成中的新安全漏洞，需要加强防御措施以防止数据渗漏和API滥用。

排序理由 该集群包含一篇详细介绍针对LLM的新型攻击向量的研究论文和一篇讨论LLM API劫持的博客文章。

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

LLM被利用进行数据渗漏和API劫持

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该集群包含一篇详细介绍针对LLM的新型攻击向量的研究论文和一篇讨论LLM API劫持的博客文章。
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报道来源 [2]

  1. arXiv cs.LG TIER_1 English(EN) · Alessandro Pegoraro, Daryan Merx, Phillip Rieger, Ahmad-Reza Sadeghi ·

    无辜的信使：通过合法的LLM网页抓取进行秘密数据外泄

    arXiv:2610.01768v1 Announce Type: cross Abstract: With the increasing capabilities of Large-Language-Models (LLMs) and LLM-based agents, users are increasingly using them to solve everyday problems, such as answering e-mails or providing programming support. Existing work has ext…

  2. dev.to — LLM tag TIER_1 English(EN) · Thinus Swart ·

    LLMjacking与被盗API密钥的隐藏成本

    <p>For the past few years, one topic has constantly been on the minds of tech professionals around the world: AI.</p> <p>AI is no longer just another piece of the tech stack but is fast becoming its foundation. Major business features, like customer support and data analysis pipe…

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