CVSS, EPSS and KEV: How to Prioritize Vulnerabilities

Every single week, automated dependency scanners identify dozens of software flaws. Most developers routinely ignore these alerts simply because there is never enough time to fix two hundred separate issues or any obvious way to determine which three actually matter. The solution relies on three distinct metrics: CVSS, EPSS, and KEV. Comprehending what each indicator measures and overlooks represents the crucial difference between an endlessly growing security backlog and a manageable remediation workflow.

The Common Vulnerability Scoring System assigns every published CVE a rating from 0 to 10 based entirely on potential severity in a worst-case scenario. A CVSS score of 9.8 sounds terrifying, yet the fundamental flaw is that these ratings remain strictly theoretical, describing vulnerabilities abstractly without accounting for real-world exploitation frequency or attacker interest.

In practice, fewer than five percent of published CVEs experience active exploitation in the wild. A high CVSS score in an unused library feature requiring local access presents a lower risk than a moderate vulnerability actively deployed in ransomware operations. Sorting solely by CVSS means organizing by worst-case theory rather than genuine operational risk, proving that CVSS serves merely as a starting point rather than a complete answer.

Stock photo for illustration only, not from the actual event

Meanwhile, the Exploit Prediction Scoring System maintained by FIRST takes an entirely different path by utilizing machine learning models trained on actual threat intelligence, honeypot telemetry, proof-of-concept activity, and CISA data. It generates a daily probability score ranging from 0 to 1 regarding the likelihood of exploitation within the next thirty days. The figures remain remarkable, as the top one percent of CVEs ranked by EPSS account for approximately seventy-five percent of all observed exploitation attempts.