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Source channel @githubredteam · Post #84667 · 5月18日

🚨 GitHub 监控消息提醒 🚨发现关键词:#漏洞#验证#检测#分析 📦项目名称:LLM-MultiAgent-StackOverflow-Detector 👤项目作者:uguj 🛠开发语言: Python ⭐Star数量: 0 | 🍴Fork数量: 0 📅更新时间: 2026-05-18 10:51:12 📝项目描述: 基于ReAct范式的多智能体栈缓冲区溢出检测框架,用于C/C++代码漏洞分析。 - Finder Agent:基于libclang的AST解析,识别危险函数调用 - Tracer Agent:语法树回溯,分析参数可控性 - Hypothesis Agent:调用Qwen2.5-Coder大语言模型生成智能漏洞假设 - Verifier Agent:通过angr符号执行与objdump静态匹配进行二进制验证 框架形成“发现→追踪→假设→验证→反馈”的闭环检测流程。 本仓库包含毕业设计《基于大语言模型的栈溢出漏洞检测研究》的全部源代码、测试用例及实验结果。 🔗点击访问项目地址

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Crypto M - Crypto News

@CryptoM · Post #65378 · 2026/04/13 03:10

🚀 AI TRENDS | University of California Study Reveals Security Risks in Third-Party LLM Routers Researchers at the University of California have identified security vulnerabilities in 26 third-party large language model (LLM) routers, which can potentially inject malicious code or steal credentials from AI agent traffic. According to NS3.AI, the study highlighted that one of these routers was able to drain Ether from a decoy wallet, although the reported financial loss remained under $50. The research paper cautioned developers who utilize AI coding agents for smart contracts or wallets, noting that private keys or seed phrases could be exposed when requests are routed through unscreened routers. #AI#securityrisks#thirdpartyLLM#maliciouscode#credentials#AIagents#UCstudy#smartcontracts#wallets#privatekeys#seedphrases#cybersecurity#ETH