Chainguard Report Finds 97% of Observed Vulnerability Instances Outside Top 20 Projects

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Summary

Chainguard analyzed 2,400+ container image projects and found 18,016 vulnerability instances across 886 CVEs from March–May 2026. It reports that 97% of instances were outside the top 20 projects.

Key points

  • The report covers Chainguard’s customer-portfolio data from March 1 to May 31, 2026, including more than 2,400 container image projects.
  • Chainguard observed 18,016 vulnerability instances across 886 distinct CVEs; 63.1% of instances were high severity.
  • Of the observed instances, 17,471—97%—were outside the 20 most-used projects.
  • Python, Node, and NGINX were the most commonly used container images in the analyzed environments, appearing in 65.6%, 60.6%, and 44.2%, respectively.
  • The report says widely used libraries and transitive dependencies underpin many applications, and argues that supply-chain risk extends beyond top-level dependencies.
  • Chainguard attributes increased vulnerability findings partly to improved scanning, security research, and AI-assisted discovery; the figures come from its own customer data.

Article Details

Publisher
Chainguard
Report Period
2026-03-01 to 2026-05-31
Scope
Anonymous customer-portfolio usage and vulnerability data covering container images and libraries; over 2,400 unique container image projects.
Sample Size
18,016 vulnerability instances across 886 distinct CVEs; usage environments analyzed across Chainguard customer data.
Key Statistics
  • 886 distinct CVEs were remediated from March through May 2026, compared with 377 in the prior quarter and 154 in December 2025.
  • High-severity vulnerabilities accounted for 11,368 of 18,016 vulnerability instances (63.1%), a 13.1% increase quarter-over-quarter.
  • 17,471 of 18,016 vulnerability instances (97%) occurred outside the top 20 projects; 545 occurred within the top 20.
  • Python appeared in 65.6% of analyzed customer environments, Node in 60.6%, and NGINX in 44.2%.
  • In analyzed FIPS customer environments, Python FIPS appeared in 54.5%, Node FIPS in 49.6%, and NGINX FIPS in 45.5%.
Recommendations
  • Maintain visibility across the full dependency graph, including transitive and long-tail dependencies, rather than focusing only on top-level or most-used projects.
  • Prioritize and remediate vulnerability findings according to their significance, given the growing volume of discovered vulnerabilities.
  • Standardize trusted foundations and apply consistent security and compliance requirements across environments.

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