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English(EN) NameTrap: Steering AI Coding Agents Toward Security Vulnerabilities via Variable Names

NameTrap 攻击通过变量名引导 AI 编码代理走向安全漏洞

研究人员开发了一种名为 NameTrap 的新型攻击,通过操纵第三方 Python 代码中的变量名来利用 AI 编码代理。该方法可以在不改变代码逻辑或提供明确恶意指令的情况下,引导代理引入特定的安全漏洞,例如 CWE-78 和 CWE-79。该攻击在各种代理和模型上的成功率介于 22.5% 到 56.0% 之间,甚至优于之前的投毒技术(如 XOXO)。值得注意的是,NameTrap 引入的漏洞未被多个基于 AI 和静态安全分析工具检测到。 AI

影响 强调了一种针对 AI 编码代理的新攻击向量,可能影响软件供应链安全并需要新的防御机制。

排序理由 详细介绍 AI 编码代理新型攻击方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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NameTrap 攻击通过变量名引导 AI 编码代理走向安全漏洞

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详细介绍 AI 编码代理新型攻击方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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完整方法见我们的编辑标准。

报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Chieh-Yuan Chang, Guan-Wei Chen, Chia-Yi Hsu, Chih Yang, Chia-Mu Yu, Chun-Ying Huang ·

    NameTrap:通过变量名引导 AI 编码代理走向安全漏洞

    arXiv:2610.34253v1 Announce Type: cross Abstract: AI coding agents routinely clone repositories, install packages, and read source code obtained from the Web, so publicly hosted code becomes part of the context that shapes the code they write. We show that this Web-borne context …