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AISLE Discovers 38 CVEs in OpenEMR Healthcare Software

AISLE Discovers 38 CVEs in Healthcare Software Used by 100,000 Medical Providers

aisle.com

April 28, 2026

9 min read

🔥🔥🔥🔥🔥

56/100

Summary

AISLE has identified 38 critical vulnerabilities (CVEs) in healthcare software utilized by 100,000 medical providers. The rapid digitization of healthcare is outpacing the implementation of adequate security measures.

Key Takeaways

  • AISLE discovered 38 critical security vulnerabilities (CVEs) in OpenEMR, a widely used healthcare software, during Q1 2026.
  • The vulnerabilities identified could allow for SQL injection attacks, potentially leading to full database compromise and unauthorized access to sensitive patient data.
  • The findings represent more than half of all OpenEMR security advisories published on GitHub during the same period, highlighting a significant security gap.
  • AISLE's AI analyzer identified these vulnerabilities in a single quarter, surpassing the previous independent audit from 2018, which found 23 vulnerabilities over a longer research period.
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Coverage & discussions

Hacker News · aisle.com

AISLE Discovers 38 CVEs in OpenEMR Healthcare Software ↗

Community discussions

Hacker News discussion ↗

Historical count: 5 · 5 saved in sample · Historical sample

Analysis ready

Community Sentiment

Mixed

Positives

  • AI security scanners can effectively identify vulnerabilities that even experienced development teams might overlook, highlighting their value in enhancing software security.
  • The potential for AI to fill gaps in human expertise for security analysis is significant, especially in the context of neglected areas like PHP security tools.

Concerns

  • Many believe that basic security checks could have prevented these vulnerabilities, suggesting that reliance on AI may not be necessary if proper practices were followed.
  • Concerns arise that adversaries could exploit AI's capabilities to discover and exploit vulnerabilities in open-source projects, raising questions about the security of closed-source software.

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