Cover Image

An Empirical Study of Vulnerabilities in Python Packages and Their Detection

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Quan, Haowei, Wang, Junjie, Li, Xinzhe, Zhuo, Terry Yue, Chen, Xiao, Du, Xiaoning
Format:	Preprint
Published:	2025
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

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

Leveraging Large Language Models for Command Injection Vulnerability Analysis in Python: An Empirical Study on Popular Open-Source Projects
by: Wang, Yuxuan, et al.
Published: (2025)

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

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

An Empirical Study of Vulnerable Package Dependencies in LLM Repositories
by: Liu, Shuhan, et al.
Published: (2025)

Empirical Study of Code Large Language Models for Binary Security Patch Detection
by: Li, Qingyuan, et al.
Published: (2025)

Are Latent Vulnerabilities Hidden Gems for Software Vulnerability Prediction? An Empirical Study
by: Le, Triet H. M., et al.
Published: (2024)

SecureFixAgent: A Hybrid LLM Agent for Automated Python Static Vulnerability Repair
by: Gajjar, Jugal, et al.
Published: (2025)

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

Agent Skills in the Wild: An Empirical Study of Security Vulnerabilities at Scale
by: Liu, Yi, et al.
Published: (2026)

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

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

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

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

AutoEG: Exploiting Known Third-Party Vulnerabilities in Black-Box Web Applications
by: Yang, Ruozhao, et al.
Published: (2026)

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

Towards Agentic Runtime Healing
by: Sun, Zhensu, et al.
Published: (2024)

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

An LLM-Assisted Easy-to-Trigger Backdoor Attack on Code Completion Models: Injecting Disguised Vulnerabilities against Strong Detection
by: Yan, Shenao, et al.
Published: (2024)

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

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

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

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

Unveiling the Landscape of LLM Deployment in the Wild: An Empirical Study
by: Hou, Xinyi, et al.
Published: (2025)

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

A Comprehensive Study of Exploitable Patterns in Smart Contracts: From Vulnerability to Defense
by: Ding, Yuchen, et al.
Published: (2025)

SPDZCoder: Combining Expert Knowledge with LLMs for Generating Privacy-Computing Code
by: Dong, Xiaoning, et al.
Published: (2024)

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

Automatically Generating Rules of Malicious Software Packages via Large Language Model
by: Zhang, XiangRui, et al.
Published: (2025)

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

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

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

QLPro: Automated Code Vulnerability Discovery via LLM and Static Code Analysis Integration
by: Hu, Junze, et al.
Published: (2025)

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

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

LLM4Vuln: A Unified Evaluation Framework for Decoupling and Enhancing LLMs' Vulnerability Reasoning
by: Sun, Yuqiang, et al.
Published: (2024)

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

Toward Patch Robustness Certification and Detection for Deep Learning Systems Beyond Consistent Samples
by: Zhou, Qilin, et al.
Published: (2025)

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

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