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    Publications

Journal Article

Measuring the Exploitation of Weaknesses in the Wild

Documentation Topics

Published: June 26, 2024
Citation: IT Professional vol. 26, no. 3, (May/June 2024) pp. 14-21

Author(s)

Peter Mell (NIST), Irena Bojanova (NIST), Carlos Cardoso Galhardo (Instituto Nacional de Metrologia)

Abstract

Identifying the software weaknesses exploited by attacks supports efforts to reduce developer introduction of vulnerabilities and to guide security code review efforts. A weakness is a bug or fault type that can be exploited through an operation that results in a security-relevant error. Ideally, the security community would measure the prevalence of the software weaknesses used in actual exploitation. This work advances that goal by introducing a simple metric that utilizes public data feeds to determine the probability of a weakness being exploited in the wild for any 30-day window. The metric is evaluated on a set of 130 weaknesses that were commonly found in vulnerabilities between April 2021 and March 2024. Our analysis reveals that 92 % of the weaknesses are not being constantly exploited.

Identifying the software weaknesses exploited by attacks supports efforts to reduce developer introduction of vulnerabilities and to guide security code review efforts. A weakness is a bug or fault type that can be exploited through an operation that results in a security-relevant error. Ideally,... See full abstract

Identifying the software weaknesses exploited by attacks supports efforts to reduce developer introduction of vulnerabilities and to guide security code review efforts. A weakness is a bug or fault type that can be exploited through an operation that results in a security-relevant error. Ideally, the security community would measure the prevalence of the software weaknesses used in actual exploitation. This work advances that goal by introducing a simple metric that utilizes public data feeds to determine the probability of a weakness being exploited in the wild for any 30-day window. The metric is evaluated on a set of 130 weaknesses that were commonly found in vulnerabilities between April 2021 and March 2024. Our analysis reveals that 92 % of the weaknesses are not being constantly exploited.


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Keywords

attack; exploit; machine learning; weakness; vulnerability; security
Control Families

None selected

Documentation

Publication:
https://doi.org/10.1109/MITP.2024.3399485
arXiv Preprint

Supplemental Material:
None available

Document History:
06/26/24: Journal Article (Final)

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