An automated analysis of the OpenEMR electronic medical records platform identified 38 previously unknown vulnerabilities, including two highest severity vulnerabilities rated CVSS 10.0, with potential impact on patient data integrity, system access, and server-level compromise.
Vulnerability Findings
The analysis identified 39 vulnerabilities that are included in the GitHub Security Advisory vulnerabilities for Q1, 2026. The findings included multiple severity levels across the set of issues. Two vulnerabilities received the highest severity rating of 10.0 under the CVSS scoring system.
The most severe vulnerabilities were assessed as capable of enabling unauthorized access to patient and provider data, modification of stored records, and full database compromise. A remote attacker could exploit one vulnerability to execute code on the server and another vulnerability to access an internet-accessible OpenEMR instance without authentication.
AISLE conducted the automated analysis as part of a collaboration with OpenEMR. OpenEMR is an open source platform of electronic medical records system certified for use in the United States.
Impact Scope and System Usage
OpenEMR is used by more than 100,000 HIPAA-covered healthcare providers globally and supports more than 200 million patients. The system is widely deployed in the United States and is used by organizations seeking lower-cost electronic medical records solutions due to the absence of licensing fees and lower operational costs.
The vulnerabilities identified by AISLE represented more than half of all OpenEMR Security vulnerabilities published through GitHub in Q1, 2026.
Response and Remediation Actions
The collaboration between AISLE and OpenEMR included vulnerability disclosure and remediation activities. AISLE generated repository-native fix proposals aligned with OpenEMR abstractions, authorization patterns, and sanitization components for each of the 38 CVE-designated vulnerabilities.
AISLE produced a fix for one of the highest severity vulnerabilities. OpenEMR maintainers incorporated AISLE-proposed remediation approaches into final fixes for additional vulnerabilities. The identified issues were addressed prior to exploitation.
OpenEMR maintainers now use AISLE’s AI-native application security platform to detect, triage, and remediate vulnerabilities. The platform supports analysis of production code and pre-production code to identify security issues before deployment.
Security Collaboration and AI-Assisted Analysis
AISLE and OpenEMR expanded their collaboration following the analysis. The partnership includes continued use of AI-assisted vulnerability detection and remediation workflows.
AISLE co-founder and chief scientist Stanislav Fort stated that disclosures reflect increasing security threats affecting healthcare systems in environments where automated tools are used to analyze code for weaknesses. The statement emphasized collaboration between AI-based analysis systems and engineering teams working on medical software security.
Threat activity patterns include the use of automated tools to identify exploitable weaknesses in software systems. The OpenEMR collaboration included preventive remediation before exploitation of identified vulnerabilities.
Image credit: Furkan, Adobestock / logo©OpenEMR
