An Empirical Study of Vulnerability Handling Times in CPython

The paper examines the handling times of software vulnerabilities in CPython, the reference implementation and interpreter for the today's likely most popular programming language, Python. The background comes from the so-called vulnerability life cycle analysis, the literature on bug fixing times, and the recent research on security of Python software. Based on regression analysis, the associated vulnerability fixing times can be explained very well merely by knowing who have reported the vulnerabilities. Severity, proof-of-concept code, commits made to a version control system, comments posted on a bug tracker, and references to other sources do not explain the vulnerability fixing times. With these results, the paper contributes to the recent effort to better understand security of the Python ecosystem.

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Publication Details

Published
2025-03-04
DOI
https://doi.org/10.1109/saner64311.2025.00097
Primary Topic
Network Security and Intrusion Detection
Type
article
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article

An Empirical Study of Vulnerability Handling Times in CPython

Jukka Ruohonen
Network Security and Intrusion Detection
article

An Empirical Study of Vulnerability Handling Times in CPython

Jukka Ruohonen
article en

Abstract

The paper examines the handling times of software vulnerabilities in CPython, the reference implementation and interpreter for the today's likely most popular programming language, Python. The background comes from the so-called vulnerability life cycle analysis, the literature on bug fixing times, and the recent research on security of Python software. Based on regression analysis, the associated vulnerability fixing times can be explained very well merely by knowing who have reported the vulnerabilities. Severity, proof-of-concept code, commits made to a version control system, comments posted on a bug tracker, and references to other sources do not explain the vulnerability fixing times. With these results, the paper contributes to the recent effort to better understand security of the Python ecosystem.

University of Southern Denmark (DK)
Openalex Percentile: Top 89%
Network Security and Intrusion Detection
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