Over 80,000 CVEs are published this year. Your board does not want the list; it wants to know how exposed the company is, what it will cost to fix, and which risks were accepted on purpose. vulneraibility.com turns the global feed into that answer, application by application, and keeps the evidence.
The executive report opens with a posture rating, a three-line narrative, the noise-to-action funnel and the five priorities that matter, each with a plain-language action.
Known-exploited vulnerabilities (CISA KEV) first, then those that affect the versions you declared, then exploit probability (EPSS), and only then CVSS.
Vulnerabilities are grouped by the component upgrade that closes them, so the plan reads like projects a manager can fund and schedule.
Every status change keeps who made it, when, why and from where (dashboard, API or an AI assistant). Acceptances without a justification are flagged as audit gaps.
Teams list each application and the versions it runs. No agent to deploy.
Every new CVE is compared with what each application runs.
Exploited first, then affecting your versions, then likely, then severe.
Fix, accept with a written reason, or defer. Recorded with an audit trail.
A one-click executive report for the risk committee and the board.
A scanner inspects machines and images you point it at. vulneraibility.com starts from what you declare you run, matches every new CVE against it as soon as it is published, checks your version against the published affected range and ranks the result by exploitation. It needs no agent and covers SaaS-hosted and third-party components a scanner never sees. Many teams use both.
A one-page executive summary (posture, narrative, key figures, funnel, top five priorities), the remediation plan grouped by upgrade, exposure by application, the risk decisions register, programme health metrics, and an appendix with only the actionable CVEs, the technology inventory and the methodology.
Yes. Everything in the dashboard is available through a REST API and an MCP server, so findings can flow into ticketing, pipelines or AI coding assistants, and status changes made there are recorded in the same history.