社区最全面、持续更新的关于大语言模型用于软件漏洞检测的研究索引——涵盖函数级、仓库级、智能体及智能合约检测的论文，以及数据集、基准测试和综述。
一份关于使用 LLM 进行漏洞检测与发现的论文、项目和智能体技能精选列表。
仅显示 2025 年及以后的内容。更早的工作请参见 论文存档（2024 年及更早）。
| 标题 | 会议/期刊 | 年份 | 论文 | Github |
|---|---|---|---|---|
| VulnGym: Benchmarking Coding Agents for Repository-Level Vulnerability Detection | 2026 | link | link | |
| VulTriage: Triple-Path Context Augmentation for LLM-Based Vulnerability Detection | 2026 | link | link | |
| Synthesizing Multi-Agent Harnesses for Vulnerability Discovery | 2026 | link | link | |
| QRS: A Rule-Synthesizing Neuro-Symbolic Triad for Autonomous Vulnerability Discovery | 2026 | link | ||
| Seclens: Role-specific Evaluation of LLM's for security vulnerablity detection | 2026 | link | link | |
| Do Fine-Tuned LLMs Understand Vulnerabilities? An Investigation into the Semantic Trap | 2026 | link | ||
| Sifting the Noise: A Comparative Study of LLM Agents in Vulnerability False Positive Filtering | ISSTA | 2026 | link | |
| AgenticSCR: An Autonomous Agentic Secure Code Review for Immature Vulnerabilities Detection | 2026 | link | ||
| LLM-based Vulnerability Detection at Project Scale: An Empirical Study | 2026 | link | ||
| MulVul: Retrieval-augmented Multi-Agent Code Vulnerability Detection via Cross-Model Prompt Evolution | 2026 | link | ||
| VulnLLM-R: Specialized Reasoning LLM with Agent Scaffold for Vulnerability Detection | 2025 | link | ||
| VULPO: Context-Aware Vulnerability Detection via On-Policy LLM Optimization | 2025 | link | ||
| VulInstruct: Teaching LLMs Root-Cause Reasoning for Vulnerability Detection via Security Specifications | 2025 | link | ||
| From Large to Mammoth: A Comparative Evaluation of Large Language Models in Vulnerability Detection | NDSS | 2025 | link | |
| Benchmarking LLMs and LLM-based Agents in Practical Vulnerability Detection for Code Repositories | ACL | 2025 | link | link |
| A Systematic Literature Review on Detecting Software Vulnerabilities with Large Language Models | 2025 | link | link | |
| LLMxCPG: Context-Aware Vulnerability Detection Through Code Property Graph-Guided Large Language Models | Usenix | 2025 | link | link |
| CLeVeR: Multi-modal Contrastive Learning for Vulnerability Code Representation | ACL Findings | 2025 | link | link |
| Mono: Is Your "Clean" Vulnerability Dataset Really Solvable? Exposing and Trapping Undecidable Patches and Beyond | 2025 | link | link | |
| Learning to Focus: Context Extraction for Efficient Code Vulnerability Detection with Language Models | 2025 | link | ||
| SV-TrustEval-C: Evaluating Structure and Semantic Reasoning in Large Language Models for Source Code Vulnerability Analysis | SP | 2025 | link | link |
| SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection | 2025 | link | link | |
| CVE-Bench: Benchmarking LLM-based Software Engineering Agent's Ability to Repair Real-World CVE Vulnerabilities | NAACL | 2025 | link | link |
| R2Vul: Learning to Reason about Software Vulnerabilities with Reinforcement Learning and Structured Reasoning Distillation | 2025 | link | link | |
| Neuro-symbolic Static Analysis with LLM-generated Vulnerability Patterns | 2025 | link | ||
| Context-Enhanced Vulnerability Detection Based on Large Language Model | 2025 | link | ||
| Everything You Wanted to Know About LLM-based Vulnerability Detection But Were Afraid to Ask | 2025 | link | link | |
| MOS: Towards Effective Smart Contract Vulnerability Detection through Mixture-of-Experts Tuning of Large Language Models | 2025 | link | ||
| Abundant Modalities Offer More Nutrients: Multi-Modal-Based Function-Level Vulnerability Detection | TOSEM | 2025 | link | link |
| Generative Large Language Model usage in Smart Contract Vulnerability Detection | 2025 | link | ||
| Closing the Gap: A User Study on the Real-world Usefulness of AI-powered Vulnerability Detection & Repair in the IDE | ICSE | 2025 | link | link |
| Vulnerability Detection with Code Language Models: How Far Are We? | ICSE | 2025 | link | link |
| Combining Fine-Tuning and LLM-based Agents for Intuitive Smart Contract Auditing with Justifications | ICSE | 2025 | link | |
| LAMD: Context-driven Android Malware Detection and Classification with LLMs | 2025 | link | ||
| LLMs in Software Security: A Survey of Vulnerability Detection Techniques and Insights | 2025 | link | link | |
| One-for-All Does Not Work! Enhancing Vulnerability Detection by Mixture-of-Experts (MoE) | 2025 | link |
| 名称 | 描述 | Github |
|---|---|---|
| OpenAnt (Knostic) | LLM 驱动的多阶段漏洞发现，带对抗性验证 | link |
| DeepAudit | 多智能体 AI 红队平台，带 Docker 沙箱漏洞利用验证 | link |
| AutoCVE | 基于多智能体架构的自动化漏洞检测与报告 | link |
| Darkmoon | 开源（GPL-3.0）自主 AI 渗透测试平台和 MCP 主机；按技术划分的进攻性子智能体，覆盖 Active Directory 和 Kubernetes，80+ 编排工具，每个发现都有证据链 | link |
| strix | 通过 pip 安装的开源自主 AI 渗透测试工具 | link |
| deepsec (Vercel) | 使用编码智能体对深层代码库进行漏洞扫描的安全框架 | link |
| rust-in-peace | 面向 Rust 的智能体辅助漏洞发现，带对抗性分诊、动态验证，以及实验性 Android APK 分析配置 | link |
