CVE-2026-124458
Summary
by MITRE • 11/08/2026
OpenEMR before 8.4.0 contains an authorization bypass vulnerability in the FHIR GET /fhir/Person/:uuid route that allows patient-portal users to read any staff member's demographics by bypassing compartment enforcement. Attackers holding a patient SMART token with patient/Person.read can harvest staff Person UUIDs from Appointment references to retrieve names, home addresses, phone numbers, and personal emails.
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Analysis
by VulDB Data Team • 11/08/2026
The vulnerability identified in OpenEMR versions prior to 8.4.0 represents a critical authorization bypass within the Fast Healthcare Interoperability Resources (FHIR) API implementation. Specifically, this flaw resides in the GET /fhir/Person/:uuid endpoint, which is designed to retrieve demographic information for individuals associated with the healthcare system. The core technical failure involves a breakdown in compartment enforcement mechanisms that are intended to restrict data access based on user roles and patient relationships. In a properly secured FHIR environment, requests for Person resources should be validated against strict contextual boundaries, ensuring that users can only access data relevant to their assigned patients or administrative scope. However, the flawed implementation fails to adequately verify whether the requesting SMART-on-FHIR token possesses sufficient privileges relative to the specific Person UUID being requested. This allows authenticated patient-portal users with a standard patient/Person.read permission set to circumvent these restrictions and query arbitrary staff member records by supplying valid but unauthorized Universal Unique Identifiers (UUIDs).
The operational impact of this vulnerability is severe, as it enables attackers to harvest sensitive personally identifiable information belonging to healthcare staff. By leveraging the Appointment resource references within their accessible patient data, adversaries can extract the UUIDs associated with doctors, nurses, and administrative personnel who have interacted with those patients. Once these identifiers are obtained, they can be directly injected into the vulnerable Person endpoint API calls. This process facilitates the unauthorized retrieval of comprehensive demographic profiles for staff members, including full names, home addresses, personal phone numbers, and private email addresses. Such data exposure not only violates patient privacy expectations regarding who has access to their records but also poses significant risks to employee safety through potential stalking or harassment, while simultaneously compromising organizational integrity by exposing internal contact details that could be leveraged for further social engineering attacks.
From a classification perspective, this vulnerability aligns with CWE-285 Improper Authorization, as the application fails to enforce proper access controls on sensitive resources. It also maps directly to MITRE ATT&CK technique T1078 Valid Accounts, where an attacker uses legitimate credentials and permissions that have been improperly expanded or bypassed to gain unauthorized access to system information. The exploitation path relies heavily on the enumeration of valid identifiers through related resources, which corresponds to data discovery techniques often seen in reconnaissance phases of cyber attacks. This incident highlights a common pitfall in FHIR implementations where compartmentalization rules are not rigorously applied across all resource types and endpoints, particularly when dealing with cross-referenced entities like appointments linking patients to providers.
To mitigate this vulnerability, organizations running OpenEMR must immediately upgrade to version 8.4.0 or later, which includes the necessary patches for strict compartment enforcement on the Person endpoint. In addition to upgrading, administrators should implement robust input validation and access control checks that verify the relationship between the authenticated user’s patient scope and the target resource identifier before returning any data. It is also advisable to audit existing API logs for signs of exploitation, such as unusual patterns of UUID enumeration or repeated failed attempts followed by successful retrievals of staff information. Furthermore, implementing rate limiting on FHIR endpoints can help detect and prevent automated harvesting attacks that rely on iterating through multiple identifiers to build a comprehensive database of compromised personnel records.