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Top Concerns With Vulnerability Data
Top Concerns With Vulnerability Data
Who it's for:
  • Cybersecurity professionals
  • Security researchers and analysts 
  • Developers and project managers 
  • CISOs and security executives 
  • Policy makers and regulatory bodies 

Top Concerns With Vulnerability Data

Release Date: 11/11/2024

The top vulnerability management frameworks used today include the Common Vulnerabilities and Exposures (CVE) program and the Common Vulnerability Scoring System (CVSS). The CVE program assigns an identifier to every discovered security vulnerability, standardizing the vulnerability documentation process. CVSS introduces a way to prioritize vulnerabilities by giving each CVE a CVSS score.

Despite their widespread use, CVE and CVSS remain stagnant in comparison to the growing threat landscape and scope of cybersecurity. Security teams have increasingly large, diverse, and complex technology stacks to secure. CVE and CVSS are simply not sufficient for managing the threat intelligence of multiple modern systems on a rolling basis.

This publication highlights the critical shortcomings of current vulnerability management programs, such as outdated information, limited context, and inefficient scoring. It also explores potential solutions that could improve the tracking, scoring, and prioritization of vulnerabilities. Readers will come to appreciate the top concerns related to vulnerability data. By the end of the document, they will also see how to fix these issues in the future.

Key Takeaways:
  • The current challenges with vulnerability data
  • Why CVE and CVSS are outdated and cannot keep up with the rapidly growing cybersecurity scene
  • Why the National Vulnerability Database (NVD) cannot scale at the necessary rate
  • The fragmentation of vulnerability data
  • Real-life examples of the issues with vulnerability data and their repercussions
  • Alternative frameworks to CVSS, including EPSS, SSVC, and VPR
  • Threat modeling frameworks to follow, including STRIDE, LINDDUN, PASTA, VAST, TRIKE, and DREAD
  • How AI and machine learning could help address the growing volume of vulnerabilities

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Acknowledgements

Abhineeth Pasam
Abhineeth Pasam

Abhineeth Pasam

Prateek Mittal
Prateek Mittal

Prateek Mittal

Ahaan Sinha
Ahaan Sinha

Ahaan Sinha

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