Exploit Prediction Scoring System (EPSS)
This addresses the need for better prioritization in vulnerability management for enterprises facing increasing numbers of vulnerabilities, offering a more objective and data-driven approach compared to current methods.
The paper tackles the problem of prioritizing vulnerability remediation by developing the Exploit Prediction Scoring System (EPSS), an open, data-driven framework that predicts the probability a vulnerability will be exploited within twelve months after disclosure, providing accurate estimates for practical use.
Despite the massive investments in information security technologies and research over the past decades, the information security industry is still immature. In particular, the prioritization of remediation efforts within vulnerability management programs predominantly relies on a mixture of subjective expert opinion, severity scores, and incomplete data. Compounding the need for prioritization is the increase in the number of vulnerabilities the average enterprise has to remediate. This paper produces 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 twelve 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 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.