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English(EN) VulnAgent-R2: Evidence-Calibrated Multi-Agent Auditing for Repository-Level Vulnerability Detection

VulnAgent-R2 框架增强了仓库级软件漏洞检测能力

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了 VulnAgent-R2，这是一个先进的多智能体审计框架，旨在检测仓库级别的软件漏洞。该系统通过纳入反事实证据重加权、构建感知验证计划合成以及成本风险帕累托调度器等模块，改进了先前的方法。VulnAgent-R2 在多个基准数据集上展示了增强的性能，取得了高 F1 和 AUROC 分数，同时还减少了执行所需的计算令牌数量。 AI

影响 通过提高漏洞检测的准确性和效率，增强了 AI 在安全软件开发中的能力。

排序理由 该集群包含一篇详细介绍软件漏洞检测新框架的研究论文。[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 →

VulnAgent-R2 框架增强了仓库级软件漏洞检测能力

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该集群包含一篇详细介绍软件漏洞检测新框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Renwei Meng, Haoyi Wu, Jingming Wang ·

    VulnAgent-R2：面向仓库级漏洞检测的证据校准多智能体审计

    arXiv:2603.13384v2 Announce Type: replace-cross Abstract: Software vulnerabilities often depend on cross-file data flow, build options, framework conventions, and runtime guards, so isolated function classifiers produce fragile and poorly calibrated warnings. Repository-level LLM…

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