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自动化AI渗透测试框架使用免费LLM降低成本

研究人员开发了PentestChain,一个用于自动化渗透测试的新型框架,该框架利用免费层级和本地大型语言模型(LLMs)来降低成本。该系统采用成本感知级联,从本地Ollama模型(qwen2.5-7b)开始,然后过渡到OpenRouter和Cerebras等免费层级服务,并有基于规则的回退机制。这种方法旨在通过最大限度地减少API费用,使持续的自动化安全测试能够被小型组织所接受。该框架还解决了与暴露MCP编排引擎相关的安全问题,并提出了潜在漏洞的缓解措施。 AI

影响 该框架可以显著降低AI驱动的安全测试的入门门槛,使小型组织也能获得高级功能。

排序理由 该项目描述了在学术论文中提出的一个新颖框架和评估协议。[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 →

自动化AI渗透测试框架使用免费LLM降低成本

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该项目描述了在学术论文中提出的一个新颖框架和评估协议。[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) · Rushabh Vipulkumar Patel, Dipo Dunsin, Mohammed Almaiah, Mohamed Chahine Ghanem ·

    PentestChain:一个成本感知、MCP编排的框架,用于使用免费层级LLM进行自动化渗透测试

    arXiv:2609.18120v1 Announce Type: cross Abstract: AI-driven penetration testing has been demonstrated with premium frontier models such as GPT-4, but the per-engagement token cost makes continuous, automated testing unaffordable for the smaller organisations that need it most. Th…