Uncovering Similar but Different Packages in PyPI and Potential Security Threats

In this study, we present a large-scale, in-depth study of package replication in PyPI. As a vital platform, PyPI streamlines Python package distribution for developers. However, beyond small-scale code cloning, we observe that many replicated packages exist on PyPI, which duplicate most of the codebase from existing packages. Such replication not only confuses developers but also propagates known vulnerabilities and enables the creation of new malicious packages. To address this issue, we comprehensively examine the characteristics and potential threats of replicated packages. Using one-third of the entire PyPI repository (200K packages), we investigate replication from three perspectives: replication of popular packages, vulnerable packages, and malicious packages. Our experiments reveal three critical findings about package replication in PyPI: (1) by identifying 1,361 replicated packages of the top 3K popular projects, we show that replication frequently redistributes substantial portions of existing packages under different maintainers; (2) by uncovering 256 previously unknown replicated vulnerable packages, we demonstrate that replication creates vulnerability blind spots that current detection tools rarely catch; (3) by analyzing 3,883 known malicious packages, we found that 186 (4.79%) replicated popular ones, and this pattern further led us to identify seven previously unknown replicated malicious packages, highlighting its role as an attack vector for malware distribution through minor modifications and code injection.

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Publication Details

Journal
Proceedings of the ACM on software engineering.
Published
2026-06-30
DOI
https://doi.org/10.1145/3808217
Primary Topic
Advanced Malware Detection Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Uncovering Similar but Different Packages in PyPI and Potential Security Threats

Seunghoon Woo, Sunha Park, Soojin Han
Proceedings of the ACM on software engineering.
Advanced Malware Detection Techniques
article

Uncovering Similar but Different Packages in PyPI and Potential Security Threats

Seunghoon Woo, Sunha Park, Soojin Han
article en

Abstract

In this study, we present a large-scale, in-depth study of package replication in PyPI. As a vital platform, PyPI streamlines Python package distribution for developers. However, beyond small-scale code cloning, we observe that many replicated packages exist on PyPI, which duplicate most of the codebase from existing packages. Such replication not only confuses developers but also propagates known vulnerabilities and enables the creation of new malicious packages. To address this issue, we comprehensively examine the characteristics and potential threats of replicated packages. Using one-third of the entire PyPI repository (200K packages), we investigate replication from three perspectives: replication of popular packages, vulnerable packages, and malicious packages. Our experiments reveal three critical findings about package replication in PyPI: (1) by identifying 1,361 replicated packages of the top 3K popular projects, we show that replication frequently redistributes substantial portions of existing packages under different maintainers; (2) by uncovering 256 previously unknown replicated vulnerable packages, we demonstrate that replication creates vulnerability blind spots that current detection tools rarely catch; (3) by analyzing 3,883 known malicious packages, we found that 186 (4.79%) replicated popular ones, and this pattern further led us to identify seven previously unknown replicated malicious packages, highlighting its role as an attack vector for malware distribution through minor modifications and code injection.

Proceedings of the ACM on software engineering.Vol. 3(FSE)
Dongduk Women's University (KR), Korea University (KR)
National Research Foundation of Korea, Korea Creative Content Agency
Openalex Percentile: Top 6%
Advanced Malware Detection Techniques
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