CHASE: LLM Agents for Dissecting Malicious PyPI Packages
Fuente:
arXiv
Saved in:
| Main Authors: | Toda, Takaaki, Mori, Tatsuya |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Cutting the Gordian Knot: Detecting Malicious PyPI Packages via a Knowledge-Mining Framework
by: Guo, Wenbo, et al.
Published: (2026)
by: Guo, Wenbo, et al.
Published: (2026)
DySec: A Machine Learning-based Dynamic Analysis for Detecting Malicious Packages in PyPI Ecosystem
by: Mehedi, Sk Tanzir, et al.
Published: (2025)
by: Mehedi, Sk Tanzir, et al.
Published: (2025)
Killing Two Birds with One Stone: Malicious Package Detection in NPM and PyPI using a Single Model of Malicious Behavior Sequence
by: Zhang, Junan, et al.
Published: (2023)
by: Zhang, Junan, et al.
Published: (2023)
SourceBroken: A large-scale analysis on the (un)reliability of SourceRank in the PyPI ecosystem
by: Montaruli, Biagio, et al.
Published: (2025)
by: Montaruli, Biagio, et al.
Published: (2025)
Bridging Expert Reasoning and LLM Detection: A Knowledge-Driven Framework for Malicious Packages
by: Guo, Wenbo, et al.
Published: (2026)
by: Guo, Wenbo, et al.
Published: (2026)
An Analysis of Malicious Packages in Open-Source Software in the Wild
by: Zhou, Xiaoyan, et al.
Published: (2024)
by: Zhou, Xiaoyan, et al.
Published: (2024)
A Machine Learning-Based Approach For Detecting Malicious PyPI Packages
by: Samaana, Haya, et al.
Published: (2024)
by: Samaana, Haya, et al.
Published: (2024)
Mind the Gap: Evaluating LLMs for High-Level Malicious Package Detection vs. Fine-Grained Indicator Identification
by: Ryan, Ahmed, et al.
Published: (2026)
by: Ryan, Ahmed, et al.
Published: (2026)
Many Hands Make Light Work: An LLM-based Multi-Agent System for Detecting Malicious PyPI Packages
by: Zeshan, Muhammad Umar, et al.
Published: (2026)
by: Zeshan, Muhammad Umar, et al.
Published: (2026)
MCGMark: An Encodable and Robust Online Watermark for Tracing LLM-Generated Malicious Code
by: Ning, Kaiwen, et al.
Published: (2024)
by: Ning, Kaiwen, et al.
Published: (2024)
Detecting Malicious Source Code in PyPI Packages with LLMs: Does RAG Come in Handy?
by: Ibiyo, Motunrayo, et al.
Published: (2025)
by: Ibiyo, Motunrayo, et al.
Published: (2025)
MalGuard: Towards Real-Time, Accurate, and Actionable Detection of Malicious Packages in PyPI Ecosystem
by: Gao, Xingan, et al.
Published: (2025)
by: Gao, Xingan, et al.
Published: (2025)
Automatically Generating Rules of Malicious Software Packages via Large Language Model
by: Zhang, XiangRui, et al.
Published: (2025)
by: Zhang, XiangRui, et al.
Published: (2025)
An Empirical Study of Vulnerable Package Dependencies in LLM Repositories
by: Liu, Shuhan, et al.
Published: (2025)
by: Liu, Shuhan, et al.
Published: (2025)
Malicious ML Model Detection by Learning Dynamic Behaviors
by: Nambiar, Sarang, et al.
Published: (2026)
by: Nambiar, Sarang, et al.
Published: (2026)
One Detector Fits All: Robust and Adaptive Detection of Malicious Packages from PyPI to Enterprises
by: Montaruli, Biagio, et al.
Published: (2025)
by: Montaruli, Biagio, et al.
Published: (2025)
AgentGuard: A Multi-Agent Framework for Robust Package Confusion Detection via Hybrid Search and Metadata-Content Fusion
by: Li, Yu, et al.
Published: (2026)
by: Li, Yu, et al.
Published: (2026)
Dissecting Payload-based Transaction Phishing on Ethereum
by: Chen, Zhuo, et al.
Published: (2024)
by: Chen, Zhuo, et al.
Published: (2024)
From Component Manipulation to System Compromise: Understanding and Detecting Malicious MCP Servers
by: Huang, Yiheng, et al.
Published: (2026)
by: Huang, Yiheng, et al.
Published: (2026)
Detecting Malicious Intents in Smart Contracts with Pre-trained Programming Language Models
by: Huang, Youwei, et al.
Published: (2025)
by: Huang, Youwei, et al.
Published: (2025)
Unveiling A Hidden Risk: Exposing Educational but Malicious Repositories in GitHub
by: Masud, Md Rayhanul, et al.
Published: (2024)
by: Masud, Md Rayhanul, et al.
Published: (2024)
MalLoc: Toward Fine-grained Android Malicious Payload Localization via LLMs
by: Sun, Tiezhu, et al.
Published: (2025)
by: Sun, Tiezhu, et al.
Published: (2025)
Models Are Codes: Towards Measuring Malicious Code Poisoning Attacks on Pre-trained Model Hubs
by: Zhao, Jian, et al.
Published: (2024)
by: Zhao, Jian, et al.
Published: (2024)
Taint-Style Vulnerability Detection and Confirmation for Node.js Packages Using LLM Agent Reasoning
by: Ni, Ronghao, et al.
Published: (2026)
by: Ni, Ronghao, et al.
Published: (2026)
Cross-ecosystem categorization: A manual-curation protocol for the categorization of Java Maven libraries along Python PyPI Topics
by: Paramitha, Ranindya, et al.
Published: (2024)
by: Paramitha, Ranindya, et al.
Published: (2024)
"Elementary, My Dear Watson." Detecting Malicious Skills via Neuro-Symbolic Reasoning across Heterogeneous Artifacts
by: Wang, Shenao, et al.
Published: (2026)
by: Wang, Shenao, et al.
Published: (2026)
Securing the Software Package Supply Chain for Critical Systems
by: Murali, Ritwik, et al.
Published: (2025)
by: Murali, Ritwik, et al.
Published: (2025)
A Static Analysis of Popular C Packages in Linux
by: Ruohonen, Jukka, et al.
Published: (2024)
by: Ruohonen, Jukka, et al.
Published: (2024)
Identifying Adversary Tactics and Techniques in Malware Binaries with an LLM Agent
by: Xuan, Zhou, et al.
Published: (2026)
by: Xuan, Zhou, et al.
Published: (2026)
LLM Agents for Automated Web Vulnerability Reproduction: Are We There Yet?
by: Liu, Bin, et al.
Published: (2025)
by: Liu, Bin, et al.
Published: (2025)
From LLMs to Agents: A Comparative Evaluation of LLMs and LLM-based Agents in Security Patch Detection
by: Han, Junxiao, et al.
Published: (2025)
by: Han, Junxiao, et al.
Published: (2025)
Maven-Hijack: Software Supply Chain Attack Exploiting Packaging Order
by: Reyes, Frank, et al.
Published: (2024)
by: Reyes, Frank, et al.
Published: (2024)
SoK: Towards Reproducibility for Software Packages in Scripting Language Ecosystems
by: Pohl, Timo, et al.
Published: (2025)
by: Pohl, Timo, et al.
Published: (2025)
PoCGen: Generating Proof-of-Concept Exploits for Vulnerabilities in Npm Packages
by: Simsek, Deniz, et al.
Published: (2025)
by: Simsek, Deniz, et al.
Published: (2025)
ARGUS: Defending LLM Agents Against Context-Aware Prompt Injection
by: Weng, Shihao, et al.
Published: (2026)
by: Weng, Shihao, et al.
Published: (2026)
Exploiting LLM Agent Supply Chains via Payload-less Skills
by: Liu, Xinyu, et al.
Published: (2026)
by: Liu, Xinyu, et al.
Published: (2026)
PackMonitor: Enabling Zero Package Hallucinations Through Decoding-Time Monitoring
by: Liu, Xiting, et al.
Published: (2026)
by: Liu, Xiting, et al.
Published: (2026)
Signing in Four Public Software Package Registries: Quantity, Quality, and Influencing Factors
by: Schorlemmer, Taylor R, et al.
Published: (2024)
by: Schorlemmer, Taylor R, et al.
Published: (2024)
The Popularity Hypothesis in Software Security: A Large-Scale Replication with PHP Packages
by: Ruohonen, Jukka, et al.
Published: (2025)
by: Ruohonen, Jukka, et al.
Published: (2025)
SABER: Benchmarking Operational Safety of LLM Coding Agents in Stateful Project Workspaces
by: Hu, Qi, et al.
Published: (2026)
by: Hu, Qi, et al.
Published: (2026)
Similar Items
-
Cutting the Gordian Knot: Detecting Malicious PyPI Packages via a Knowledge-Mining Framework
by: Guo, Wenbo, et al.
Published: (2026) -
DySec: A Machine Learning-based Dynamic Analysis for Detecting Malicious Packages in PyPI Ecosystem
by: Mehedi, Sk Tanzir, et al.
Published: (2025) -
Killing Two Birds with One Stone: Malicious Package Detection in NPM and PyPI using a Single Model of Malicious Behavior Sequence
by: Zhang, Junan, et al.
Published: (2023) -
SourceBroken: A large-scale analysis on the (un)reliability of SourceRank in the PyPI ecosystem
by: Montaruli, Biagio, et al.
Published: (2025) -
Bridging Expert Reasoning and LLM Detection: A Knowledge-Driven Framework for Malicious Packages
by: Guo, Wenbo, et al.
Published: (2026)