mlsanityData to 14 Oct 2026

LProtector: An LLM-driven Vulnerability Detection System

arXiv 2411.06493 ↗First posted 10 Nov 2024cs.CR cs.AIcited by 8

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Abstract (arXiv)

This paper presents LProtector, an automated vulnerability detection system for C/C++ codebases driven by the large language model (LLM) GPT-4o and Retrieval-Augmented Generation (RAG). As software complexity grows, traditional methods face challenges in detecting vulnerabilities effectively. LProtector leverages GPT-4o's powerful code comprehension and generation capabilities to perform binary classification and identify vulnerabilities within target codebases. We conducted experiments on the Big-Vul dataset, showing that LProtector outperforms two state-of-the-art baselines in terms of F1 score, demonstrating the potential of integrating LLMs with vulnerability detection.

Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 20 of its 37 references that are in the map. First posted on arXiv 10 Nov 2024.

Builds on

20 of 37 references.

References · 20

  1. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,459
  2. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
  3. 2023A Survey on Large Language Model (LLM) Security and Privacy: The Good, the Bad, and the Uglycited by 387
  4. 2023LEVER: Learning to Verify Language-to-Code Generation with Executioncited by 239
  5. 2024Chain-of-Thought Reasoning Without Promptingcited by 210
  6. 2024Beyond Functional Correctness: Exploring Hallucinations in LLM-Generated Codecited by 107
  7. 2024IRIS: LLM-Assisted Static Analysis for Detecting Security Vulnerabilitiescited by 103
  8. 2024AutoAttacker: A Large Language Model Guided System to Implement Automatic Cyber-attackscited by 96
  9. 2024Vul-RAG: Enhancing LLM-based Vulnerability Detection via Knowledge-level RAGcited by 68
  10. 2018The Art, Science, and Engineering of Fuzzing: A Surveycited by 62
  11. 2024LLM4Vuln: A Unified Evaluation Framework for Decoupling and Enhancing LLMs' Vulnerability Reasoningcited by 59
  12. 2024LLM-Based Test-Driven Interactive Code Generation: User Study and Empirical Evaluationcited by 49
8 more
  1. 2018Evaluating Fuzz Testingcited by 32
  2. 2024Harnessing XGBoost for Robust Biomarker Selection of Obsessive-Compulsive Disorder (OCD) from Adolescent Brain Cognitive Development (ABCD) datacited by 26
  3. 2023A Survey on Automated Program Repair Techniquescited by 13
  4. 2024Autonomous Navigation of Unmanned Vehicle Through Deep Reinforcement Learningcited by 12
  5. 2024Enhancing Large Language Models for Text-to-Testcase Generationcited by 7
  6. 2024VERCATION: Precise Vulnerable Open-source Software Version Identification based on Static Analysis and LLMcited by 6
  7. 2024Enhanced Credit Score Prediction Using Ensemble Deep Learning Modelcited by 2
  8. 2024In-context Demonstration Matters: On Prompt Optimization for Pseudo-Supervision Refinementcited by 1

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 6; 2026: 2.

8 papers.

  1. 2025Large Language Models for Security Operations Centers: A Comprehensive Surveycited by 9
  2. 2025Benchmarking LLM-Assisted Blue Teaming via Standardized Threat Huntingcited by 6
  3. 2025AutoPatch: Multi-Agent Framework for Patching Real-World CVE Vulnerabilitiescited by 4
  4. 2025Detecting Malicious Source Code in PyPI Packages with LLMs: Does RAG Come in Handy?cited by 3
  5. 2025Can LLMs Find Bugs in Code? An Evaluation from Beginner Errors to Security Vulnerabilities in Python and C++cited by 3
  6. 2025LLaVul: A Multimodal LLM for Interpretable Vulnerability Reasoning about Source Codecited by 0
  7. 2026VulReaD: Knowledge-Graph-guided Software Vulnerability Reasoning and Detectioncited by 0
  8. 2026FuzzingBrain-Bench V1: Evaluating Open-Ended Bug Discovery by LLMscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026An Empirical Evaluation of LLM-Based Approaches for Code Vulnerability Detection: RAG, SFT, and Dual-Agent Systems
  2. 2025A Systematic Study of Code Obfuscation Against LLM-based Vulnerability Detection
  3. 2026Representation Matters: An Empirical Study of Program Representations for LLM Vulnerability Reasoning
  4. 2025Reasoning with LLMs for Zero-Shot Vulnerability Detection
  5. 2024Towards Explainable Vulnerability Detection with Large Language Models
  6. 2026Revisiting Vul-RAG: Reproducibility and Replicability of RAG-based Vulnerability Detection with Open-Weight Models
  7. 2024VulScribeR: Exploring RAG-based Vulnerability Augmentation with LLMs
  8. 2026VulTriage: Triple-Path Context Augmentation for LLM-Based Vulnerability Detection