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A Mixed-Methods Study of Open-Source Software Maintainers On Vulnerability Management and Platform Security Features

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arxiv 2409.07669 v2 pith:KB7CZLSU submitted 2024-09-12 cs.SE cs.CR

classification cs.SEcs.CR
keywords vulnerabilitymaintainersmanagementsecurityfeaturesperspectivesplatformsoftware
verification ladder T0 review T1 audit T2 compute T3 formal
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abstract

In open-source software (OSS), software vulnerabilities have significantly increased. Although researchers have investigated the perspectives of vulnerability reporters and OSS contributor security practices, understanding the perspectives of OSS maintainers on vulnerability management and platform security features is currently understudied. In this paper, we investigate the perspectives of OSS maintainers who maintain projects listed in the GitHub Advisory Database. We explore this area by conducting two studies: identifying aspects through a listing survey ($n_1=80$) and gathering insights from semi-structured interviews ($n_2=22$). Of the 37 identified aspects, we find that supply chain mistrust and lack of automation for vulnerability management are the most challenging, and barriers to adopting platform security features include a lack of awareness and the perception that they are not necessary. Surprisingly, we find that despite being previously vulnerable, some maintainers still allow public vulnerability reporting, or ignore reports altogether. Based on our findings, we discuss implications for OSS platforms and how the research community can better support OSS vulnerability management efforts.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Eradicating the Unseen: Detecting, Exploiting, and Remediating a Path Traversal Vulnerability across GitHub

    cs.CR 2025-05 conditional novelty 6.0 of 10

    A single vulnerable Node.js path traversal pattern was found in 1,756 GitHub projects, most rated critical, and the authors' automated pipeline produced patches, disclosures, and evidence that LLMs have learned the pattern.

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