Open AccessComputer Science

Jay Jacobs, Sasha Romanosky, Benjamin Edwards, Michael Roytman, Idris Adjerid

2019.8.13Digital Threats: Research and Practice

DOI: 10.1145/3436242

tlooto Summary

This article describes the first open, data-driven framework for assessing vulnerability threat, that is, the probability that a vulnerability will be exploited in the wild within the first 12 months after public disclosure.

Abstract

Despite the large investments in information security technologies and research over the past decades, the information security industry is still immature when it comes to vulnerability management. In particular, the prioritization of remediation efforts within vulnerability management programs predominantly relies on a mixture of subjective expert opinion and severity scores. Compounding the need for prioritization is the increase in the number of vulnerabilities the average enterprise has to remediate. This article describes the first open, data-driven framework for assessing vulnerability threat, that is, the probability that a vulnerability will be exploited in the wild within the first 12 months after public disclosure. This scoring system has been designed to be simple enough to be implemented by practitioners without specialized tools or software yet provides accurate estimates (ROC AUC = 0.838) of exploitation. Moreover, the implementation is flexible enough that it can be updated as more, and better, data becomes available. We call this system the Exploit Prediction Scoring System (EPSS).

Citation format

JACOBS, Jay, et al. Exploit prediction scoring system (EPSS) [preprint]. arXiv, 2019. arXiv:1908.04856.