English(EN) Towards Agentic Investigation of Security Alerts

LLM驱动的代理可更准确地自动执行安全警报调查

作者 PulseAugur 编辑部 · [1 个来源] · 2026-04-28 16:52

研究人员开发了一种代理式工作流，该工作流使用大型语言模型（LLM）来自动执行安全警报调查的初始阶段。该系统集成了预定义的查询和工具访问，例如日志上的SQL和文本搜索，以关联来自多个来源的信息。LLM组件负责规划调查和提取证据，其准确性高于未使用此结构化工作流的LLM。 AI

影响自动执行初始安全警报调查，可能减轻安全分析师的手动工作量。

排序理由这是一篇研究论文，详细介绍了使用LLM进行安全警报调查的新颖方法。

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

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Newsworthiness bucket: Research; 这是一篇研究论文，详细介绍了使用LLM进行安全警报调查的新颖方法。
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, product; 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.
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完整方法见我们的编辑标准。

arXiv cs.AI TIER_1 English(EN) · Gudmund Grov · 2026-04-28 16:52

迈向安全警报的代理式调查

Security analysts are overwhelmed by the volume of alerts and the low context provided by many detection systems. Early-stage investigations typically require manual correlation across multiple log sources, a task that is usually time-consuming. In this paper, we present an exper…