Flashpoint’s ransomware prediction model enables security teams to remediate vulnerabilities
Flashpoint announced a ransomware prediction model that allows vulnerability management teams to improve remediation efforts that could prevent cyber extortion events with VulnDB.
According to the U.S. Treasury Department, financial institutions filed $1.2B in ransomware-related costs in 2021, nearly double the amount reported by banks in 2020. In order to help organizations proactively prevent a ransomware attack, Flashpoint’s latest capability enables vulnerability management teams to identify the likelihood that a particular vulnerability could be used in a future ransomware attack.
“The risk of falling victim to a ransomware attack can be radically reduced with the right intelligence,” says Flashpoint General Manager Jake Kouns. “Our ransomware prediction algorithm, coupled with our vulnerability intelligence, is a must-have for security teams that want to remediate vulnerabilities that could help them get in front of a potentially destructive ransomware attack.”
VulnDB covers over 300,000 known vulnerabilities found in end-user software and third-party libraries and dependencies, including over 96,000 vulnerabilities missed by CVE and NVD. For each of those vulnerabilities, including newly disclosed issues, Flashpoint’s ransomware prediction model determines a Ransomware Likelihood rating that’s derived from a combination of factors, including exploit availability, attack type, impact, disclosure patterns, and other characteristics captured by VulnDB.
This intelligence is critical to vulnerability management teams who often lack the resources and context they need to efficiently prioritize and patch tens of thousands of vulnerabilities disclosed every year.