PyPitfall: Dependency Chaos and Software Supply Chain Vulnerabilities in Python
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866908876804194304 |
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| author | Mahon, Jacob Hou, Chenxi Yao, Zhihao |
| author_facet | Mahon, Jacob Hou, Chenxi Yao, Zhihao |
| contents | Python software development heavily relies on third-party packages. Direct and transitive dependencies create a labyrinth of software supply chains. While it is convenient to reuse code, vulnerabilities within these dependency chains can propagate through dependencies, potentially affecting down-stream packages and applications. PyPI, the official Python package repository, hosts many packages and lacks a comprehensive analysis of the prevalence of vulnerable dependencies. This paper introduces PyPitfall, a quantitative analysis of vulnerable dependencies across the PyPI ecosystem. We analyzed the dependency structures of 378,573 PyPI packages and identified 4,655 packages that explicitly require at least one known-vulnerable version and 141,044 packages that permit vulnerable versions within specified ranges. By characterizing the ecosystem-wide dependency landscape and the security impact of transitive dependencies, we aim to raise awareness of Python software supply chain security. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_18075 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | PyPitfall: Dependency Chaos and Software Supply Chain Vulnerabilities in Python Mahon, Jacob Hou, Chenxi Yao, Zhihao Cryptography and Security Python software development heavily relies on third-party packages. Direct and transitive dependencies create a labyrinth of software supply chains. While it is convenient to reuse code, vulnerabilities within these dependency chains can propagate through dependencies, potentially affecting down-stream packages and applications. PyPI, the official Python package repository, hosts many packages and lacks a comprehensive analysis of the prevalence of vulnerable dependencies. This paper introduces PyPitfall, a quantitative analysis of vulnerable dependencies across the PyPI ecosystem. We analyzed the dependency structures of 378,573 PyPI packages and identified 4,655 packages that explicitly require at least one known-vulnerable version and 141,044 packages that permit vulnerable versions within specified ranges. By characterizing the ecosystem-wide dependency landscape and the security impact of transitive dependencies, we aim to raise awareness of Python software supply chain security. |
| title | PyPitfall: Dependency Chaos and Software Supply Chain Vulnerabilities in Python |
| topic | Cryptography and Security |
| url | https://arxiv.org/abs/2507.18075 |