揭示隐藏风险：曝光GitHub中具有教育属性但实质恶意的代码仓库
Unveiling A Hidden Risk: Exposing Educational but Malicious Repositories in GitHub
AI总结：
本研究利用ChatGPT对3.52万个GitHub教育类代码仓库开展恶意性标注研究，发现其中9294个为恶意且分属14个恶意软件家族，揭示了教育类仓库的隐藏风险，为软件平台的安全分析敲响警钟。
摘要：
恶意代码仓库是否正打着教育的旗号隐藏在GitHub中？近期研究已发现，GitHub上存在大量托管恶意软件源代码的代码仓库，且开发者之间存在显著的协作行为。由于GitHub的开源特性使得恶意软件代码与制品极易获取，因此对GitHub代码仓库的分析理应受到必要重视。本研究在一项定性研究中利用ChatGPT的能力，基于元数据内容的恶意性对标注为教育类的GitHub代码仓库进行标注。我们的贡献分为两方面：其一，我们展示了利用ChatGPT理解并标注软件仓库中发布内容的可行性；其二，我们提供了教育类代码仓库存在隐藏风险的证据，这类仓库可能为潜在威胁与恶意意图提供可乘之机。我们对3.52万个声称仅用于教育目的的GitHub代码仓库开展了系统性研究。研究发现，每年发布的此类仓库数量呈上升趋势；其中有9294个被ChatGPT标注为恶意，对这些恶意仓库的进一步分类检测出14个不同的恶意软件家族，包括DDoS、键盘记录器、勒索软件等。总体而言，这项探索性研究为业界敲响了警钟，呼吁更好地理解和分析软件平台。
英文摘要：
Are malicious repositories hiding under the educational label in GitHub? Recent studies have identified collections of GitHub repositories hosting malware source code with notable collaboration among the developers. Thus, analyzing GitHub repositories deserves inevitable attention due to its open-source nature providing easy access to malicious software code and artifacts. Here we leverage the capabilities of ChatGPT in a qualitative study to annotate an educational GitHub repository based on maliciousness of its metadata contents. Our contribution is twofold. First, we demonstrate the employment of ChatGPT to understand and annotate the content published in software repositories. Second, we provide evidence of hidden risk in educational repositories contributing to the opportunities of potential threats and malicious intents. We carry out a systematic study on a collection of 35.2K GitHub repositories claimed to be created for educational purposes only. First, our study finds an increasing trend in the number of such repositories published every year. Second, 9294 of them are labeled by ChatGPT as malicious, and further categorization of the malicious ones detects 14 different malware families including DDoS, keylogger, ransomware and so on. Overall, this exploratory study flags a wake-up call for the community for better understanding and analysis of software platforms.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
