Cover Image

Graph Neural Networks for Vulnerability Detection: A Counterfactual Explanation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Chu, Zhaoyang, Wan, Yao, Li, Qian, Wu, Yang, Zhang, Hongyu, Sui, Yulei, Xu, Guandong, Jin, Hai
Format:	Preprint
Published:	2024
Subjects:	Software Engineering Artificial Intelligence Cryptography and Security
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Coca: Improving and Explaining Graph Neural Network-Based Vulnerability Detection Systems
by: Cao, Sicong, et al.
Published: (2024)

Scrub It Out! Erasing Sensitive Memorization in Code Language Models via Machine Unlearning
by: Chu, Zhaoyang, et al.
Published: (2025)

On the Effectiveness of Function-Level Vulnerability Detectors for Inter-Procedural Vulnerabilities
by: Li, Zhen, et al.
Published: (2024)

Does the Vulnerability Threaten Our Projects? Automated Vulnerable API Detection for Third-Party Libraries
by: Zhang, Fangyuan, et al.
Published: (2024)

HALURust: Exploiting Hallucinations of Large Language Models to Detect Vulnerabilities in Rust
by: Luo, Yu, et al.
Published: (2025)

DLAP: A Deep Learning Augmented Large Language Model Prompting Framework for Software Vulnerability Detection
by: Yang, Yanjing, et al.
Published: (2024)

ChainFuzzer: Greybox Fuzzing for Workflow-Level Multi-Tool Vulnerabilities in LLM Agents
by: Wu, Jiangrong, et al.
Published: (2026)

Vulnerability-Hunter: An Adaptive Feature Perception Attention Network for Smart Contract Vulnerabilities
by: Chen, Yizhou
Published: (2024)

VulnRepairEval: An Exploit-Based Evaluation Framework for Assessing Large Language Model Vulnerability Repair Capabilities
by: Wang, Weizhe, et al.
Published: (2025)

Game Rewards Vulnerabilities: Software Vulnerability Detection with Zero-Sum Game and Prototype Learning
by: Wen, Xin-Cheng, et al.
Published: (2024)

Smart Cuts: Enhance Active Learning for Vulnerability Detection by Pruning Hard-to-Learn Data
by: Lan, Xiang, et al.
Published: (2025)

Profile of Vulnerability Remediations in Dependencies Using Graph Analysis
by: Vera, Fernando, et al.
Published: (2024)

Software Vulnerability Detection Using a Lightweight Graph Neural Network
by: Farmer, Miles, et al.
Published: (2026)

Detecting Protracted Vulnerabilities in Open Source Projects
by: Sridharkumar, Arjun, et al.
Published: (2026)

Triggering and Detecting Exploitable Library Vulnerability from the Client by Directed Greybox Fuzzing
by: Zhao, Yukai, et al.
Published: (2026)

An Empirical Study on the Security Vulnerabilities of GPTs
by: Wu, Tong, et al.
Published: (2025)

Uncover the Premeditated Attacks: Detecting Exploitable Reentrancy Vulnerabilities by Identifying Attacker Contracts
by: Yang, Shuo, et al.
Published: (2024)

VulInstruct: Teaching LLMs Root-Cause Reasoning for Vulnerability Detection via Security Specifications
by: Zhu, Hao, et al.
Published: (2025)

How Effective Are Neural Networks for Fixing Security Vulnerabilities
by: Wu, Yi, et al.
Published: (2023)

TPSQLi: Test Prioritization for SQL Injection Vulnerability Detection in Web Applications
by: Yang, Guan-Yan, et al.
Published: (2025)

SCALE: Constructing Structured Natural Language Comment Trees for Software Vulnerability Detection
by: Wen, Xin-Cheng, et al.
Published: (2024)

Impact of Code Transformation on Detection of Smart Contract Vulnerabilities
by: Manh, Cuong Tran, et al.
Published: (2024)

Multi-Agent Taint Specification Extraction for Vulnerability Detection
by: Ghebremichael, Jonah, et al.
Published: (2026)

Vulnerability Detection in Popular Programming Languages with Language Models
by: Atiiq, Syafiq Al, et al.
Published: (2024)

Explainable Vulnerability Detection in C/C++ Using Edge-Aware Graph Attention Networks
by: Haque, Radowanul, et al.
Published: (2025)

How Code Representation Shapes False-Positive Dynamics in Cross-Language LLM Vulnerability Detection
by: Chen, Maofei, et al.
Published: (2026)

SAGA: Detecting Security Vulnerabilities Using Static Aspect Analysis
by: Marquer, Yoann, et al.
Published: (2026)

Deep Learning Aided Software Vulnerability Detection: A Survey
by: Uddin, Md Nizam, et al.
Published: (2025)

SHERLOCK: A Deep Learning Approach To Detect Software Vulnerabilities
by: Jawwadh, Saadh, et al.
Published: (2025)

Lightweight Vulnerability Detection from Code Metrics and Token Features
by: Chiu, Chun Yin
Published: (2026)

From Generalist to Specialist: Exploring CWE-Specific Vulnerability Detection
by: Atiiq, Syafiq Al, et al.
Published: (2024)

Smart-LLaMA: Two-Stage Post-Training of Large Language Models for Smart Contract Vulnerability Detection and Explanation
by: Yu, Lei, et al.
Published: (2024)

Beyond Function-Level Analysis: Context-Aware Reasoning for Inter-Procedural Vulnerability Detection
by: Li, Yikun, et al.
Published: (2026)

CleanVul: Automatic Function-Level Vulnerability Detection in Code Commits Using LLM Heuristics
by: Li, Yikun, et al.
Published: (2024)

AI-Based Software Vulnerability Detection: A Systematic Literature Review
by: Shimmi, Samiha, et al.
Published: (2025)

A Slicing-Based Approach for Detecting and Patching Vulnerable Code Clones
by: Alomari, Hakam, et al.
Published: (2025)

Improving Smart Contract Security with Contrastive Learning-based Vulnerability Detection
by: Chen, Yizhou, et al.
Published: (2024)

VulEval: Towards Repository-Level Evaluation of Software Vulnerability Detection
by: Wen, Xin-Cheng, et al.
Published: (2024)

Generating Proof-of-Vulnerability Tests to Help Enhance the Security of Complex Software
by: Kanchi, Shravya, et al.
Published: (2026)

A Ground-Truth-Based Evaluation of Vulnerability Detection Across Multiple Ecosystems
by: Mandl, Peter, et al.
Published: (2026)