Demystifying the Vulnerability Propagation and Its Evolution via Dependency Trees in the NPM Ecosystem
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Abstract (arXiv)
Third-party libraries with rich functionalities facilitate the fast development of Node.js software, but also bring new security threats that vulnerabilities could be introduced through dependencies. In particular, the threats could be excessively amplified by transitive dependencies. Existing research either considers direct dependencies or reasoning transitive dependencies based on reachability analysis, which neglects the NPM-specific dependency resolution rules, resulting in wrongly resolved dependencies. Consequently, further fine-grained analysis, such as vulnerability propagation and their evolution in dependencies, cannot be carried out precisely at a large scale, as well as deriving ecosystem-wide solutions for vulnerabilities in dependencies. To fill this gap, we propose a knowledge graph-based dependency resolution, which resolves the dependency relations of dependencies as trees (i.e., dependency trees), and investigates the security threats from vulnerabilities in dependency trees at a large scale. We first construct a complete dependency-vulnerability knowledge graph (DVGraph) that captures the whole NPM ecosystem (over 10 million library versions and 60 million well-resolved dependency relations). Based on it, we propose DTResolver to statically and precisely resolve dependency trees, as well as transitive vulnerability propagation paths, by considering the official dependency resolution rules. Based on that, we carry out an ecosystem-wide empirical study on vulnerability propagation and its evolution in dependency trees. Our study unveils lots of useful findings, and we further discuss the lessons learned and solutions for different stakeholders to mitigate the vulnerability impact in NPM. For example, we implement a dependency tree based vulnerability remediation method (DTReme) for NPM packages, and receive much better performance than the official tool (npm audit fix).
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 Jan 2022.
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Citing papers per year: 2023: 1; 2024: 2; 2025: 0; 2026: 5.
8 papers.
- 2024What do we know about Hugging Face? A systematic literature review and quantitative validation of qualitative claimscited by 8
- 2023Multi-Granularity Detector for Vulnerability Fixescited by 4
- 2024PatchFinder: A Two-Phase Approach to Security Patch Tracing for Disclosed Vulnerabilities in Open-Source Softwarecited by 2
- 2026ADK Arena: Evaluating Agent Development Kits via LLM-as-a-Developercited by 2
- 2026Correct Code, Vulnerable Dependencies: A Large Scale Measurement Study of LLM-Specified Library Versionscited by 1
- 2026RepoRescue: An Empirical Study of LLM Agents on Whole-Repository Compatibility Rescuecited by 1
- 2026DepRadar: Agentic Coordination for Context Aware Defect Impact Analysis in Deep Learning Librariescited by 0
- 2026Code That Works, Environments That Don't: Measuring Environment Reproducibility in AI-Generated Softwarecited by 0
- 2026Code That Works, Environments That Don't: Measuring Environment Reproducibility in AI-Generated Software30 Sep 2026
- 2026RepoRescue: An Empirical Study of LLM Agents on Whole-Repository Compatibility Rescue1 Jul 2026
- 2026ADK Arena: Evaluating Agent Development Kits via LLM-as-a-Developer4 Jun 2026
- 2026Correct Code, Vulnerable Dependencies: A Large Scale Measurement Study of LLM-Specified Library Versions7 May 2026
- 2026DepRadar: Agentic Coordination for Context Aware Defect Impact Analysis in Deep Learning Libraries14 Jan 2026
- 2024PatchFinder: A Two-Phase Approach to Security Patch Tracing for Disclosed Vulnerabilities in Open-Source Software24 Jul 2024
- 2024What do we know about Hugging Face? A systematic literature review and quantitative validation of qualitative claims12 Jun 2024
- 2023Multi-Granularity Detector for Vulnerability Fixes23 May 2023