AI-driven security testing identified 38 vulnerabilities in OpenEMR, an electronic health record platform deployed by over 100,000 healthcare providers. The flaws expose attackers to multiple attack vectors: database compromise, remote code execution, and unauthorized data theft. OpenEMR's widespread adoption across the healthcare sector amplifies the risk surface. The vulnerabilities span different severity levels and attack methodologies, requiring prioritized patching across the provider ecosystem. Healthcare organizations running OpenEMR should immediately audit patch status and apply updates. The discovery underscores how legacy healthcare software, built before modern threat modeling, concentrates risk when adopted at scale. Specific CVE numbers and technical details determine remediation urgency for defenders. Healthcare IT teams lack flexibility that enterprise environments possess; patching delays in clinical settings risk patient safety alongside data breaches. The incident demonstrates automated security testing's effectiveness at finding flaws in complex applications, though manual verification remains essential for validating AI-identified issues before deployment.