Copertina

Explainable Vulnerability Detection in C/C++ Using Edge-Aware Graph Attention Networks

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Haque, Radowanul, Ali, Aftab, McClean, Sally, Khan, Naveed
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Cryptography and Security Artificial Intelligence Software Engineering
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Graph Neural Networks for Vulnerability Detection: A Counterfactual Explanation
di: Chu, Zhaoyang, et al.
Pubblicazione: (2024)

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

Evaluating LLMs for One-Shot Patching of Real and Artificial Vulnerabilities
di: Garg, Aayush, et al.
Pubblicazione: (2025)

Smart-LLaMA-DPO: Reinforced Large Language Model for Explainable Smart Contract Vulnerability Detection
di: Yu, Lei, et al.
Pubblicazione: (2025)

VULPO: Context-Aware Vulnerability Detection via On-Policy LLM Optimization
di: Li, Youpeng, et al.
Pubblicazione: (2025)

LLbezpeky: Leveraging Large Language Models for Vulnerability Detection
di: Mathews, Noble Saji, et al.
Pubblicazione: (2024)

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

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

Bridging Semantics & Structure for Software Vulnerability Detection using Hybrid Network Models
di: Gajjar, Jugal, et al.
Pubblicazione: (2025)

Data and Context Matter: Towards Generalizing AI-based Software Vulnerability Detection
di: Safdar, Rijha, et al.
Pubblicazione: (2025)

Taint-Style Vulnerability Detection and Confirmation for Node.js Packages Using LLM Agent Reasoning
di: Ni, Ronghao, et al.
Pubblicazione: (2026)

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

An Empirical Study of Vulnerabilities in Python Packages and Their Detection
di: Quan, Haowei, et al.
Pubblicazione: (2025)

An Empirical Study of Vulnerability Detection using Federated Learning
di: Zhou, Peiheng, et al.
Pubblicazione: (2024)

Harnessing the Power of LLMs in Source Code Vulnerability Detection
di: Mahyari, Andrew A
Pubblicazione: (2024)

Detecting Vulnerabilities from Issue Reports for Internet-of-Things
di: Masoumzadeh, Sogol
Pubblicazione: (2025)

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

MegaVul: A C/C++ Vulnerability Dataset with Comprehensive Code Representation
di: Ni, Chao, et al.
Pubblicazione: (2024)

VulDetectBench: Evaluating the Deep Capability of Vulnerability Detection with Large Language Models
di: Liu, Yu, et al.
Pubblicazione: (2024)

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

From Detection to Prevention: Explaining Security-Critical Code to Avoid Vulnerabilities
di: Krishnamurthy, Ranjith, et al.
Pubblicazione: (2026)

Knowdit: Agentic Smart Contract Vulnerability Detection with Auditing Knowledge Summarization
di: Kong, Ziqiao, et al.
Pubblicazione: (2026)

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

Focus on What Matters: Fisher-Guided Adaptive Multimodal Fusion for Vulnerability Detection
di: Bian, Yun, et al.
Pubblicazione: (2026)

MAVUL: Multi-Agent Vulnerability Detection via Contextual Reasoning and Interactive Refinement
di: Li, Youpeng, et al.
Pubblicazione: (2025)

GPTScan: Detecting Logic Vulnerabilities in Smart Contracts by Combining GPT with Program Analysis
di: Sun, Yuqiang, et al.
Pubblicazione: (2023)

Towards Secure and Explainable Smart Contract Generation with Security-Aware Group Relative Policy Optimization
di: Yu, Lei, et al.
Pubblicazione: (2025)

Code Security Vulnerability Repair Using Reinforcement Learning with Large Language Models
di: Islam, Nafis Tanveer, et al.
Pubblicazione: (2024)

Harnessing Large Language Models for Software Vulnerability Detection: A Comprehensive Benchmarking Study
di: Tamberg, Karl, et al.
Pubblicazione: (2024)

From SFT to RL: Demystifying the Post-Training Pipeline for LLM-based Vulnerability Detection
di: Li, Youpeng, et al.
Pubblicazione: (2026)

EaTVul: ChatGPT-based Evasion Attack Against Software Vulnerability Detection
di: Liu, Shigang, et al.
Pubblicazione: (2024)

CodeHacker: Automated Test Case Generation for Detecting Vulnerabilities in Competitive Programming Solutions
di: Shi, Jingwei, et al.
Pubblicazione: (2026)

AEGIS: From Clues to Verdicts -- Graph-Guided Deep Vulnerability Reasoning via Dialectics and Meta-Auditing
di: Fang, Sen, et al.
Pubblicazione: (2026)

MalCodeAI: Autonomous Vulnerability Detection and Remediation via Language Agnostic Code Reasoning
di: Gajjar, Jugal, et al.
Pubblicazione: (2025)

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection
di: Yu, Lei, et al.
Pubblicazione: (2025)

Detecting Data Poisoning in Code Generation LLMs via Black-Box, Vulnerability-Oriented Scanning
di: Yan, Shenao, et al.
Pubblicazione: (2026)

Retrieval-Augmented Few-Shot Prompting Versus Fine-Tuning for Code Vulnerability Detection
di: Trad, Fouad, et al.
Pubblicazione: (2025)

MulVuln: Enhancing Pre-trained LMs with Shared and Language-Specific Knowledge for Multilingual Vulnerability Detection
di: Nguyen, Van, et al.
Pubblicazione: (2025)

VulReaD: Knowledge-Graph-guided Software Vulnerability Reasoning and Detection
di: Mukhtar, Samal, et al.
Pubblicazione: (2026)

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