Effectively prioritizing vulnerabilities is critical to reducing cyber risk, and enterprises must triage and manage more than 100 critical vulnerabilities on average daily, as rated by the common vulnerability scoring system (CVSS). But basic CVSS ratings alone are failing the industry and leaving organizations unable to effectively and confidently focus on which vulnerabilities require immediate action. Moreover, the industry is on track to disclose up to 19,000 new vulnerabilities in 2018, an increase of 27 percent over 2017. Yet in 2017, public exploits were available for just 7 percent of all vulnerabilities, meaning that 93 percent of all vulnerabilities posed only theoretical risk. For most vulnerabilities, a working exploit is never developed. Of those, an even smaller subset is actively weaponized by threat actors, making it difficult to understand which vulnerabilities to remediate first, if at all. This new tool combines vulnerability data collected by the company with third-party vulnerability and threat data and analyzes them together with an advanced data science algorithm. The algorithm analyzes more than 100,000 vulnerabilities using machine learning to anticipate the probability of a vulnerability being leveraged by threat actors and to differentiate between real and theoretical risks.
>>For more information on this product, click here