A Time Series Analysis of Malware Uploads to Programming Language Ecosystems
Fuente:
arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866909756490252288 |
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| author | Ruohonen, Jukka Saddiqa, Mubashrah |
| author_facet | Ruohonen, Jukka Saddiqa, Mubashrah |
| contents | Software ecosystems built around programming languages have greatly facilitated software development. At the same time, their security has increasingly been acknowledged as a problem. To this end, the paper examines the previously overlooked longitudinal aspects of software ecosystem security, focusing on malware uploaded to six popular programming language ecosystems. The dataset examined is based on the new Open Source Vulnerabilities (OSV) database. According to the results, records about detected malware uploads in the database have recently surpassed those addressing vulnerabilities in packages distributed in the ecosystems. In the early 2025 even up to 80% of all entries in the OSV have been about malware. Regarding time series analysis of malware frequencies and their shares to all database entries, good predictions are available already by relatively simple autoregressive models using the numbers of ecosystems, security advisories, and media and other articles as predictors. With these results and the accompanying discussion, the paper improves and advances the understanding of the thus far overlooked longitudinal aspects of ecosystems and malware. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_15695 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Time Series Analysis of Malware Uploads to Programming Language Ecosystems Ruohonen, Jukka Saddiqa, Mubashrah Cryptography and Security Software Engineering Software ecosystems built around programming languages have greatly facilitated software development. At the same time, their security has increasingly been acknowledged as a problem. To this end, the paper examines the previously overlooked longitudinal aspects of software ecosystem security, focusing on malware uploaded to six popular programming language ecosystems. The dataset examined is based on the new Open Source Vulnerabilities (OSV) database. According to the results, records about detected malware uploads in the database have recently surpassed those addressing vulnerabilities in packages distributed in the ecosystems. In the early 2025 even up to 80% of all entries in the OSV have been about malware. Regarding time series analysis of malware frequencies and their shares to all database entries, good predictions are available already by relatively simple autoregressive models using the numbers of ecosystems, security advisories, and media and other articles as predictors. With these results and the accompanying discussion, the paper improves and advances the understanding of the thus far overlooked longitudinal aspects of ecosystems and malware. |
| title | A Time Series Analysis of Malware Uploads to Programming Language Ecosystems |
| topic | Cryptography and Security Software Engineering |
| url | https://arxiv.org/abs/2504.15695 |