Tenable introduces Predictive Prioritization, a groundbreaking, data science-based process that re-prioritizes each vulnerability based on the likelihood it will be leveraged in an attack.
Are you feeling overloaded by the number of vulnerabilities facing your organization daily? You’re not alone.
There were 16,500 new vulnerabilities in 2018. The ‘good’ news is that only 7% of these vulnerabilities had a public exploit available and an even smaller subset is ever weaponized by threat actors. The Tenable data science team estimates only 3% of vulnerabilities will be exploited. The ‘bad’ news is that it hasn’t been easy to figure out which of the 3% you need to worry about. Until now.
Today, Tenable introduces Predictive Prioritization, a groundbreaking new process that uses advanced data science techniques to solve the vulnerability overload problem. It’s included as a core functionality within Tenable.sc and Tenable.io, so you don’t need to buy an add-on prioritization platform. And it’s way more than just a list of vulnerabilities with known active exploits. Predictive Prioritization re-prioritizes each vulnerability based on the likelihood it will be leveraged in an attack. Over 150 data sources, including Tenable vulnerability data and third-party vulnerability and threat intelligence, are utilized by a proprietary machine learning algorithm to identify the vulnerabilities with the highest likelihood of exploitation.
Predictive Prioritization is used to calculate a Vulnerability Priority Rating, which automatically indicates the remediation priority for each vulnerability. For example, a vulnerability currently being exploited on a widely deployed service would have a significantly higher rating than a vulnerability for which no working exploit has been observed. The Vulnerability Priority Rating is a dynamic value and changes with the threat landscape. Updated daily, it allows you to take advantage of the latest threat intelligence as you prioritize your remediation efforts.
What about CVSS?
Predictive Prioritization augments existing Common Vulnerability Scoring System (CVSS) scores. CVSS has the following significant limitations:
- It lacks the granularity needed to provide an accurate measure of criticality. For example, to derive a score CVSS only looks at if the vulnerability could be exploited - not if it actually is being exploited.
- CVSS is a relatively static number and does not change in response to changes in the threat landscape as vulnerabilities are weaponized.
- The majority of vulnerabilities are scored through CVSS as ‘high’ or ‘critical.’ Common sense dictates that if everything is important than nothing is, creating an overload of vulnerabilities to remediate.