Unveiling A Hidden Risk: Exposing Educational but Malicious Repositories in GitHub

Fuente: arXiv
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Autori principali: Masud, Md Rayhanul, Faloutsos, Michalis
Natura: Preprint
Pubblicazione: 2024
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author Masud, Md Rayhanul
Faloutsos, Michalis
author_facet Masud, Md Rayhanul
Faloutsos, Michalis
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2403_04419
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Unveiling A Hidden Risk: Exposing Educational but Malicious Repositories in GitHub
Masud, Md Rayhanul
Faloutsos, Michalis
Software Engineering
Cryptography and Security
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.
title Unveiling A Hidden Risk: Exposing Educational but Malicious Repositories in GitHub
topic Software Engineering
Cryptography and Security
url https://arxiv.org/abs/2403.04419