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UpdatedAug 31, 2026

Awesome-LLMs-for-Vulnerability-Detection — Updated!

Die umfassendste, kontinuierlich aktualisierte Sammlung der Community zu Forschung über Large Language Models zur Erkennung von Software-Schwachstellen – mit Papers zu Funktionsebene, Repository-Ebene, agentischer und Smart-Contract-Erkennung sowie Datensätzen, Benchmarks und Übersichtsarbeiten.

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Awesome Large Language Models für Schwachstellenerkennung

Eine kuratierte Liste von Papers, Projekten und Agent-Skills zur Nutzung von LLMs für die Erkennung und Entdeckung von Schwachstellen.


📄 Papers

Es werden nur Arbeiten ab 2025 gezeigt. Für frühere Arbeiten siehe Papers-Archiv (2024 und früher).

TitelVeranstaltungJahrPaperGithub
VulnGym: Benchmarking Coding Agents for Repository-Level Vulnerability Detection2026linklink
VulTriage: Triple-Path Context Augmentation for LLM-Based Vulnerability Detection2026linklink
Synthesizing Multi-Agent Harnesses for Vulnerability Discovery2026linklink
QRS: A Rule-Synthesizing Neuro-Symbolic Triad for Autonomous Vulnerability Discovery2026link
Seclens: Role-specific Evaluation of LLM's for security vulnerablity detection2026linklink
Do Fine-Tuned LLMs Understand Vulnerabilities? An Investigation into the Semantic Trap2026link
Sifting the Noise: A Comparative Study of LLM Agents in Vulnerability False Positive FilteringISSTA2026link
AgenticSCR: An Autonomous Agentic Secure Code Review for Immature Vulnerabilities Detection2026link
LLM-based Vulnerability Detection at Project Scale: An Empirical Study2026link
MulVul: Retrieval-augmented Multi-Agent Code Vulnerability Detection via Cross-Model Prompt Evolution2026link
VulnLLM-R: Specialized Reasoning LLM with Agent Scaffold for Vulnerability Detection2025link
VULPO: Context-Aware Vulnerability Detection via On-Policy LLM Optimization2025link
VulInstruct: Teaching LLMs Root-Cause Reasoning for Vulnerability Detection via Security Specifications2025link
From Large to Mammoth: A Comparative Evaluation of Large Language Models in Vulnerability DetectionNDSS2025link
Benchmarking LLMs and LLM-based Agents in Practical Vulnerability Detection for Code RepositoriesACL2025linklink
A Systematic Literature Review on Detecting Software Vulnerabilities with Large Language Models2025linklink
LLMxCPG: Context-Aware Vulnerability Detection Through Code Property Graph-Guided Large Language ModelsUsenix2025linklink
CLeVeR: Multi-modal Contrastive Learning for Vulnerability Code RepresentationACL Findings2025linklink
Mono: Is Your "Clean" Vulnerability Dataset Really Solvable? Exposing and Trapping Undecidable Patches and Beyond2025linklink
Learning to Focus: Context Extraction for Efficient Code Vulnerability Detection with Language Models2025link
SV-TrustEval-C: Evaluating Structure and Semantic Reasoning in Large Language Models for Source Code Vulnerability AnalysisSP2025linklink
SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection2025linklink
CVE-Bench: Benchmarking LLM-based Software Engineering Agent's Ability to Repair Real-World CVE VulnerabilitiesNAACL2025linklink
R2Vul: Learning to Reason about Software Vulnerabilities with Reinforcement Learning and Structured Reasoning Distillation2025linklink
Neuro-symbolic Static Analysis with LLM-generated Vulnerability Patterns2025link
Context-Enhanced Vulnerability Detection Based on Large Language Model2025link
Everything You Wanted to Know About LLM-based Vulnerability Detection But Were Afraid to Ask2025linklink
MOS: Towards Effective Smart Contract Vulnerability Detection through Mixture-of-Experts Tuning of Large Language Models2025link
Abundant Modalities Offer More Nutrients: Multi-Modal-Based Function-Level Vulnerability DetectionTOSEM2025linklink
Generative Large Language Model usage in Smart Contract Vulnerability Detection2025link
Closing the Gap: A User Study on the Real-world Usefulness of AI-powered Vulnerability Detection & Repair in the IDEICSE2025linklink
Vulnerability Detection with Code Language Models: How Far Are We?ICSE2025linklink
Combining Fine-Tuning and LLM-based Agents for Intuitive Smart Contract Auditing with JustificationsICSE2025link
LAMD: Context-driven Android Malware Detection and Classification with LLMs2025link
LLMs in Software Security: A Survey of Vulnerability Detection Techniques and Insights2025linklink
One-for-All Does Not Work! Enhancing Vulnerability Detection by Mixture-of-Experts (MoE)2025link

🚀 Projekte

NameBeschreibungGithub
OpenAnt (Knostic)LLM-gestützte mehrstufige Schwachstellenentdeckung mit adversarischer Verifikationlink
DeepAuditMulti-Agenten-KI-Red-Team-Plattform mit Docker-Sandbox-Exploit-Validierunglink
AutoCVEAutomatisierte Schwachstellenerkennung und -meldung mit Multi-Agenten-Architekturlink
DarkmoonOpen-Source- (GPL-3.0) autonome KI-Pentest-Plattform und MCP-Host; technologie-spezifische offensive Sub-Agenten, Active-Directory- und Kubernetes-Abdeckung, 80+ orchestrierte Tools, Beweiskette pro Befundlink
strixOpen-Source-autonomes KI-Penetrationstest-Tool via piplink
deepsec (Vercel)Sicherheits-Harness für tiefgehendes Schwachstellen-Scannen von Codebasen mit Coding-Agentenlink

🧩 Agent-Skills

NameBeschreibungLink
codex-security (OpenAI)Autonomes Schwachstellen-Scannen auf Repository-Ebene über Codex-Agentenlink
defending-code-reference-harness (Anthropic)Referenz-Skills für Threat Modeling, Scannen, Triage und Patchen mit Claude Codelink
security-audit-skill (Cloudflare)Sechsphasiger Security-Audit-Skill mit parallelen Hunting-Agenten und adversarischer Validierunglink

📡 arxiv.md

Automatische tägliche Erfassung und Aktualisierung von Arxiv-Papers für bestimmte Schlüsselwörter über Workflows.

Danksagungen

Der Workflow „Updated Arxiv Papers Daily" des Projekts übernimmt Ideen aus diesem Projekt LLM4SE. Ich habe dessen ursprünglichen Code mithilfe der arxiv-Bibliothek refaktoriert.

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