Decoding Dependency Risks: A Quantitative Study of Vulnerabilities in the Maven Ecosystem

2025-03-28

AI Summary

This study addresses security risks arising from dependency chains in the Maven ecosystem. It systematically identifies critical vulnerabilities—including insufficient input validation, improper resource management, overly short J2EE session IDs, authentication flaws, and unencrypted sensitive data—and discovers Maven-specific risk patterns, such as unthrottled resource allocation, for the first time. Leveraging a large-scale dependency graph encompassing 14.45 million artifact versions, the work combines static weakness pattern matching with transitive dependency path tracing. Results show that 31.39% of latest artifact versions contain direct vulnerabilities, while 62.89% harbor transitive ones. The study proposes a risk-prioritization framework grounded in vulnerability evolution dynamics and propagation pathways, enabling precise identification of high-risk weaknesses and informed security governance decisions. This provides a scalable methodology and empirical foundation for open-source dependency risk management.

Technology Category

• Data Mining & Knowledge Management: Representing, Reasoning, and Using Provenance, Trust
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Computer Vision: Adversarial Attacks & Robustness

Application Category

• Security and Privacy: Large-scale security measurements
• Web Mining and Content Analysis: Web data provenance, reliability, and authenticity
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

This study investigates vulnerabilities within the Maven ecosystem by analyzing a comprehensive dataset of 14,459,139 releases. Our analysis reveals the most critical weaknesses that pose significant threats to developers and their projects as they look to streamline their development tasks through code reuse. We show risky weaknesses, those unique to Maven, and emphasize those becoming increasingly dangerous over time. Furthermore, we reveal how vulnerabilities subtly propagate, impacting 31.39% of the 635,003 latest releases through direct dependencies and 62.89% through transitive dependencies. Our findings suggest that improper handling of input and mismanagement of resources pose the most risk. Additionally, Insufficient session-ID length in J2EE configuration and no throttling while allocating resources uniquely threaten the Maven ecosystem. We also find that weaknesses related to improper authentication and managing sensitive data without encryption have quickly gained prominence in recent years. These findings emphasize the need for proactive strategies to mitigate security risks in the Maven ecosystem.

Problem

• Identifying critical vulnerabilities in Maven ecosystem dependencies
• Analyzing propagation of vulnerabilities through direct and transitive dependencies
• Highlighting emerging risks like improper authentication and unencrypted data

Innovation

• Analyzing 14M Maven releases for vulnerabilities
• Identifying direct and transitive dependency risks
• Highlighting improper input and resource mismanagement threats