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An historical examination of open source releases and their vulnerabilities

Published: 16 October 2012 Publication History

Abstract

This paper examines historical releases of Sendmail, Postfix, Apache httpd and OpenSSL by using static source code analysis and the entry-rate in the Common Vulnerabilities and Exposures dictionary (CVE) for a release, which we take as a measure of the rate of discovery of exploitable bugs. We show that the change in number and density of issues reported by the source code analyzer is indicative of the change in rate of discovery of exploitable bugs for new releases --- formally we demonstrate a statistically significant correlation of moderate strength. The strength of the correlation is an artifact of other factors such as the degree of scrutiny: the number of security analysts investigating the software. This also demonstrates that static source code analysis can be used to make some assessment of risk even when constraints do not permit human review of the issues identified by the analysis.
We find only a weak correlation between absolute values measured by the source code analyzer and rate of discovery of exploitable bugs, so in general it is unsafe to use absolute values of number of issues or issue densities to compare different applications or software. Our results demonstrate that software quality, as measured by the number of issues, issue density or number of exploitable bugs, does not always improve with each new release. However, generally the rate of discovery of exploitable bugs begins to drop three to five years after the initial release.

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      cover image ACM Conferences
      CCS '12: Proceedings of the 2012 ACM conference on Computer and communications security
      October 2012
      1088 pages
      ISBN:9781450316514
      DOI:10.1145/2382196
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Published: 16 October 2012

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      Author Tags

      1. open source software
      2. risk analysis
      3. static analysis

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      October 16 - 18, 2012
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      • (2024)Towards Measuring Vulnerabilities and Exposures in Open-Source PackagesData Science—Analytics and Applications10.1007/978-3-031-42171-6_2(13-19)Online publication date: 4-Jan-2024
      • (2023)It’s like flossing your teeth: On the Importance and Challenges of Reproducible Builds for Software Supply Chain Security2023 IEEE Symposium on Security and Privacy (SP)10.1109/SP46215.2023.10179320(1527-1544)Online publication date: May-2023
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      • (2019)Employing different program analysis methods to study bug evolutionProceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering10.1145/3338906.3342489(1202-1204)Online publication date: 12-Aug-2019
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