CVE-2025-43860

May 23, 2025, 4:15 p.m.

7.6
High

Description

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 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.

Product(s) Impacted

Vendor Product Versions
Openemr
  • Openemr
  • <7.0.3.4

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-79
Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')
The product does not neutralize or incorrectly neutralizes user-controllable input before it is placed in output that is used as a web page that is served to other users.

*CPE(s)

Affected systems and software identified for this CVE.

Type Vendor Product Version Update Edition Language Software Edition Target Software Target Hardware Other Information
a openemr openemr <7.0.3.4 / / / / / / /

CVSS Score

7.6 / 10

CVSS Data - 3.1

  • Attack Vector: NETWORK
  • Attack Complexity: LOW
  • Privileges Required: LOW
  • Scope: CHANGED
  • Confidentiality Impact: HIGH
  • Integrity Impact: LOW
  • Availability Impact: NONE
  • CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:C/C:H/I:L/A:N

    View Vector String

Timeline

Published: May 23, 2025, 4:15 p.m.
Last Modified: May 23, 2025, 4:15 p.m.

Status : Received

CVE has been recently published to the CVE List and has been received by the NVD.

More info

Source

security-advisories@github.com

*Disclaimer: Some vulnerabilities do not have an associated CPE. To enhance the data, we use AI to infer CPEs based on CVE details. This is an automated process and might not always be accurate.