Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:C/C:H/I:L/A:NSummary
CVE-2025-43860 is a high-severity Cross-site Scripting (CWE-79) vulnerability in Open-Emr Openemr. Its CVSS base score is 7.6 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Browser Session Hijacking (T1185); ranked in the top 6% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
The strongest mitigations our analysis identified map to SA-11 (Developer Testing and Evaluation) and SI-10 (Information Input Validation) — see the control section below for these in your framework.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
OpenEMR is a free and open source electronic health records and medical practice management application. A stored cross-site scripting vulnerability tracked as CVE-2025-43860 affects versions prior to 7.0.3.4 and resides in the Additional Addresses section of the Contact tab within Patient Demographics. Authenticated users can store arbitrary JavaScript in the Text Box fields for Address, Address Line 2, Postal Code, and City as well as the Drop Down options for Address Use, State, and Country; the payload executes either dynamically on form input or when the record is later reloaded for editing.
Any authenticated user granted patient creation or editing rights can exploit the flaw. Successful injection allows the attacker to run scripts in the context of other users who view or edit the same patient record, potentially resulting in theft of sensitive session tokens or other high-impact actions within the application.
The referenced GitHub Security Advisory states that version 7.0.3.4 contains a patch addressing the stored XSS issue. The EPSS score remains flat at 0.0209 with no material increase after disclosure.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-28018
Vulnerability Data
OpenEMR is a free and open source electronic health records and medical practice management application. A stored cross-site scripting (XSS) vulnerability in versions prior to 7.0.3.4 allows any authenticated user with patient creation and editing privileges to inject arbitrary JavaScript…
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code into the system by entering malicious payloads in the (1) Text Box fields of Address, Address Line 2, Postal Code and City fields and (2) Drop Down menu options of Address Use, State and Country of the Additional Addresses section of the Contact tab in Patient Demographics. The injected script can execute in two scenarios: (1) dynamically during form input, and (2) when the form data is later loaded for editing. Version 7.0.3.4 contains a patch for the issue.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.1.2V1.3.2
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation can discover missing or incorrect input neutralization through targeted web-application tests.
Input validation directly enforces neutralization of untrusted data before it reaches web output generation.
Output filtering can catch or sanitize unneutralized script content before it is served to users.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Secure SDLC practices directly target introduction of XSS via coding standards/testing (mostly), yet the single broad outcome leaves many specific neutralization vectors unaddressed (partial).
Patching and EOL replacement can remediate known XSS instances in libraries or frameworks (partial) but do nothing to enforce input neutralization in application code (none).
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Secure-coding testing and automated code-analysis tools are applied to detect improper neutralization of script-related content during web-page generation.
Knowledge exchange on emerging attack techniques and patches reduces the likelihood that cross-site scripting flaws remain unaddressed in deployed applications.
Operational indicators of compromise for web-application attacks can be incorporated into WAF or input-filtering rules, lowering the likelihood that unsanitized data reaches the browser.
Requiring language-specific secure-coding standards and automated scanning during the SDLC catches missing output encoding or improper neutralization of untrusted data before the software reaches production.
Secure-coding standards, SAST scans and removal of insecure code samples together eliminate the failure to neutralize script content that produces cross-site scripting flaws.
Webpage malware scanning and block-listing of known malicious sites reduce the likelihood that reflected or stored script payloads reach a user’s browser.