English(EN) What Guides the Agent? Adjudicating Unauthorized Behavior via Localizing Behavior-Guiding Instructions

新框架Attnlocate检测LLM代理中的恶意指令

作者 PulseAugur 编辑部 · [1 个来源] · 2026-08-26 04:00

研究人员开发了一个名为Attnlocate的新框架，用于检测和本地化LLM代理上下文中的恶意指令。该系统解决了不可信的外部数据可以被动态解释为行为指导指令，从而导致代理被颠覆的漏洞。Attnlocate将这种本地化视为一个目标检测问题，通过分析注意力矩阵来识别指示恶意内容的特定激活痕迹。该框架在各种LLM配置和场景中都表现出强大的性能，包括提示注入和工具投毒，并且即使在未见过的模型上也能有效。 AI

影响通过检测和本地化恶意指令来增强LLM代理的安全性，这对于与外部资源的安全集成至关重要。

排序理由详细介绍LLM代理安全新技术框架的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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

本文如何被排名

Signal score: 0 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Tool; 详细介绍LLM代理安全新技术框架的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
Source corroboration: Single-source cluster; Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics: paper, safety; Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance: High; Clearly on-topic for AI-industry coverage.
Story freshness: 51 days old; Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

完整方法见我们的编辑标准。

报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Yichao Gao, Yumo Zhang, Yunhao Yao, Haohua Du, Puhan Luo, Ruiqi Li, Zhiqiang Wang · 2026-08-26 04:00

什么在指导代理？通过本地化指导行为的指令来裁决未经授权的行为

arXiv:2608.24022v1 Announce Type: cross Abstract: LLM agents integrated with external resources gain complex task capabilities, yet the unified natural-language context channel makes them vulnerable to injection attacks: untrusted external data may be dynamically parsed as behavi…

本文如何被排名

报道来源 [1]

什么在指导代理？通过本地化指导行为的指令来裁决未经授权的行为

相关实体

相关话题