OSS Malicious Package Analysis in the Wild

• URL: http://arxiv.org/abs/2404.04991v2
• Date: Sun, 21 Apr 2024 04:44:17 GMT
• Title: OSS Malicious Package Analysis in the Wild
• Authors: Xiaoyan Zhou, Ying Zhang, Wenjia Niu, Jiqiang Liu, Haining Wang, Qiang Li,
• Abstract summary: This paper builds and curates the largest dataset of 23,425 malicious packages from scattered online sources. We then propose a knowledge graph to represent the OSS malware corpus and conduct malicious package analysis in the wild.
• Score: 17.028240712650486
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The open-source software (OSS) ecosystem suffers from various security threats and risks, and malicious packages play a central role in software supply chain (SSC) attacks. Although malware research has a history of over thirty years, less attention has been paid to OSS malware. Its existing research has three limitations: a lack of high-quality datasets, malware diversity, and attack campaign context. In this paper, we first build and curate the largest dataset of 23,425 malicious packages from scattered online sources. We then propose a knowledge graph to represent the OSS malware corpus and conduct malicious package analysis in the wild. Our main findings include (1) it is essential to collect malicious packages from various online sources because there is little data overlap between different sources; (2) despite the sheer volume of SSC attack campaigns, many malicious packages are similar, and unknown/sophisticated attack behaviors have yet to emerge or be detected; (3) OSS malicious package has its distinct life cycle, denoted as {changing->release->detection->removal}, and slightly changing the package (different name) is a widespread attack manner; (4) while malicious packages often lack context about how and who released them, security reports disclose the information about corresponding SSC attack campaigns.

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