Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Let me be direct about something the industry keeps dancing around: the vulnerability problem isn’t getting better. It’s getting structurally worse. The wave of AI-generated code and compression of time to exploit thanks to frontier AI models like Mythos is about to make “worse” look quaint. If your vulnerability and exposure management program is still built around scanner cycles, ticket queues, and CVSS scores, you’re not running a security program.

Security teams didn’t need a headline to tell them that vulnerability volumes continue to be problematic. The CVE database now contains over 354,000 records. Annual disclosure rates have climbed steadily for more than a decade. And remediation backlogs have long been recognized not as an aberration, but as a fixture of the job.

Security teams can’t remediate every vulnerability the moment it appears, so prioritization must separate urgent, business-critical risks from noise. This is complicated by the fact that traditional scoring methods like CVSS often lack the context needed to decide what should be fixed first. The Stakeholder-Specific Vulnerability Categorization (SSVC) framework is one option many organizations use to fill this gap as part of automating vulnerability prioritization.