Improving CVSS-based vulnerability prioritization and response with context information

The growing number of software security vulnerabilities is an ever-increasing challenge for organizations. As security managers in the industry have to operate within limited budgets they also have to prioritize their vulnerability responses. The Common Vulnerability Scoring System (CVSS) aids in such prioritization by providing a metric for the severity of vulnerabilities. In its most prominent application, as the severity metric in the U.S. National Vulnerability Database (NVD), CVSS scores omit information pertaining the potential exploit victims´ context. Researchers and managers in the industry have long understood that the severity of vulnerabilities varies greatly among different organizational contexts. Therefore the CVSS scores provided by the NVD alone are of limited use for vulnerability prioritization in practice. Security managers could address this limitation by adding the missing context information themselves to improve the quality of their CVSS-based vulnerability prioritization. It is unclear for them, however, whether the potential improvements are worth the additional effort. We present a method that enables practitioners to estimate these improvements. Our method is of particular use to practitioners who do not have the resources to gather large amounts of empirical data, because it allows them to simulate the improvement potential using only publicly available data in the NVD and distribution models from the literature. We applied the method on a sample set of 720 vulnerability announcements from the NVD and found that adding context information significantly improved the prioritization and selection of vulnerability response process. Our findings contribute to the discourse on returns on security investment, measurement of security processes and quantitative security management.