Vulnerability Exploit Scoring uses AI to predict the likelihood of active exploitation for identified vulnerabilities, enabling risk-prioritised patch management, by analysing CVSS scores, exploit availability, asset exposure, and threat intelligence signals, across vulnerability management and patch prioritisation workflows.
Security teams face backlogs of thousands of open vulnerabilities and cannot remediate all within patching windows, applying equal priority to high-volume low-risk findings while critically exploited vulnerabilities remain unpatched.
A predictive model scores each open vulnerability on exploitation likelihood within 30 days, combining CVSS severity, exploit-in-the-wild signals, asset business criticality, and network exposure, producing a risk-prioritised patching queue.
Reduction in mean time to remediate actively exploited vulnerabilities and reduction in patch backlog for critical-business-risk systems.
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