Delve delivers a comprehensive vulnerability management solution that includes our exclusive, AI-driven Contextual Vulnerability Prioritization. Contextual Prioritization uses over 40 factors to risk-rank all vulnerabilities from 1 to n on a given network through continuous machine learning analysis of the internal and external context around every single vulnerability. A few of those factors fall into our external threat intelligence category. The data below is an excerpt of the Delve solution’s external threat intelligence prioritization category.
Delve’s Vulnerability Threat Intelligence feed provides two scores for newly-published vulnerabilities.
The first score is the vulnerability's Exploit Publication Prediction Score (EPPS), which leverages multiple public feeds, historical CVE and exploit data to predict, through the DelveAI engine, the likelihood that an exploit will be developed for the vulnerability in the coming days, weeks, or months. Moreover, our prioritization engine will appropriately raise the priority of a vulnerability likely to have an exploit published.
The second score is the Vulnerability Trend Score (VTS)
This score uses advanced natural language processing techniques to identify topics being discussed most prominently on chat boards, social media feeds, and in dark web groups, and then identifies the vulnerabilities most closely matching those topics. The machine-learning-based VTS provides IT and security teams an indication of that vulnerability's growing or declining importance in the wild, and is also built into Delve's Contextual Prioritization score. The VTS is scored 0 to 100, with 100 indicating the vulnerability is most closely associated with topics that have been most frequently-discussed over the previous month.