HAPI FHIR <6.9.4 unauth /loadIG allows token theft
CVE-2026-34361 Published on March 31, 2026
HAPI FHIR: Unauthenticated SSRF via /loadIG Chains with startsWith() Credential Leak for Authentication Token Theft
HAPI FHIR is a complete implementation of the HL7 FHIR standard for healthcare interoperability in Java. Prior to version 6.9.4, the FHIR Validator HTTP service exposes an unauthenticated "/loadIG" endpoint that makes outbound HTTP requests to attacker-controlled URLs. Combined with a startsWith() URL prefix matching flaw in the credential provider (ManagedWebAccessUtils.getServer()), an attacker can steal authentication tokens (Bearer, Basic, API keys) configured for legitimate FHIR servers by registering a domain that prefix-matches a configured server URL. This issue has been patched in version 6.9.4.
Vulnerability Analysis
CVE-2026-34361 can be exploited with network access, and does not require authorization privileges or user interaction. This vulnerability is considered to have a low attack complexity. An automatable proof of concept (POC) exploit exists. The potential impact of an exploit of this vulnerability is considered to have a high impact on confidentiality, with no impact on integrity, and no impact on availability.
Weakness Type
Files or Directories Accessible to External Parties
The product makes files or directories accessible to unauthorized actors, even though they should not be. Web servers, FTP servers, and similar servers may store a set of files underneath a "root" directory that is accessible to the server's users. Applications may store sensitive files underneath this root without also using access control to limit which users may request those files, if any. Alternately, an application might package multiple files or directories into an archive file (e.g., ZIP or tar), but the application might not exclude sensitive files that are underneath those directories.
Affected Versions
hapifhir org.hl7.fhir.core Version < 6.9.4 is affected by CVE-2026-34361Exploit Probability
EPSS (Exploit Prediction Scoring System) scores estimate the probability that a vulnerability will be exploited in the wild within the next 30 days. The percentile shows you how this score compares to all other vulnerabilities.