Exploit Prediction Scoring Systems (EPSS): Should You Trust It?

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Introduction

Vulnerability management has always faced a fundamental challenge: which vulnerabilities should be patched first? With thousands of new CVEs published annually, security teams cannot fix everything at once.
Traditionally, organizations relied on the Common Vulnerability Scoring System (CVSS), which rates vulnerabilities from 0 to 10. However, CVSS doesn’t measure how likely a vulnerability is to be exploited in the wild. Enter the Exploit Prediction Scoring System (EPSS) — a machine learning–driven model designed to predict the probability that a given vulnerability will be exploited within the next 30 days.
But how reliable is EPSS? And should organizations base their remediation priorities on it?

How EPSS Works

Developed by the Forum of Incident Response and Security Teams (FIRST), EPSS uses real-world data — including threat intelligence feeds, historical exploit data, and attacker behavior — to assign a probability score (0 to 1) to each CVE.
  • EPSS vs CVSS
    • CVSS = measures severity.
    • EPSS = measures likelihood of exploitation.
    • Together, they provide a richer picture of risk.
  • Dynamic Model Unlike CVSS, which is static, EPSS updates regularly based on fresh data. This allows it to capture emerging exploitation trends.

Benefits of Using EPSS

  1. Prioritization with Context Instead of patching thousands of CVEs blindly, security teams can focus on the ones most likely to be exploited.
  2. Efficiency Reduces patching workload, helping organizations use resources more effectively.
  3. Integration with Vulnerability Management Tools Platforms like Tenable.io already incorporate EPSS scoring to help organizations prioritize remediation.

Limitations of EPSS

  1. Probability, Not Certainty EPSS predicts likelihood but cannot guarantee exploitation.
  2. Data Dependency Predictions are only as good as the data feeding the model. Bias or gaps in threat intelligence could affect accuracy.
  3. Business Impact Missing EPSS doesn’t consider the context of your environment — for example, a vulnerability in a public-facing payment app vs. an internal test server.

Malaysian Cybersecurity Context

For Malaysian organizations, especially those in regulated industries like banking, healthcare, and government, patch prioritization is critical. Bank Negara Malaysia’s RMiT framework emphasizes timely vulnerability remediation.
EPSS can help Malaysian SOCs and GRC teams move from compliance-driven patching to risk-driven patching. By combining EPSS predictions with business impact assessments and continuous scanning through Tenable.io, organizations can balance regulatory requirements with practical, risk-based security.

Final Thoughts

The Exploit Prediction Scoring System (EPSS) represents a powerful step forward in vulnerability management, bridging the gap between theoretical severity and real-world exploitation. However, it should not be used in isolation.
By combining EPSS probability scores, CVSS severity ratings, and business impact analysis, organizations can prioritize vulnerabilities more effectively. Integrated with Tenable.io, Stellar Cyber XDR, and SentinelOne endpoint protection, Exabytes delivers a holistic approach to vulnerability management that balances compliance, efficiency, and real-world risk.
👉 Don’t let patch overload paralyze your SOC. Start with Exabytes eSecure to leverage EPSS and intelligent vulnerability prioritization that keeps you one step ahead of attackers.

References

  • FIRST. (2025). Exploit Prediction Scoring System (EPSS). Retrieved from https://www.first.org/epss/
  • Mell, P., Scarfone, K., & Romanosky, S. (2023). Understanding CVSS and Its Limitations. NIST. Retrieved from https://csrc.nist.gov/publications/detail/white-paper/2023/understanding-cvss
  • Tenable. (2025). Prioritizing Vulnerabilities with EPSS. Retrieved from https://www.tenable.com/blog/prioritizing-vulnerabilities-with-epss
  • Stellar Cyber. (2025). XDR Security Operations Platform. Retrieved from https://stellarcyber.ai/platform/xdr-security-operations/
  • SentinelOne. (2025). Endpoint Security for Advanced Threats. Retrieved from https://www.sentinelone.com/platform/edr/
  • Bank Negara Malaysia. (2020). Risk Management in Technology (RMiT). Retrieved from https://www.bnm.gov.my/documents/20124/938039/rmit2020.pdf