PatchSiren

PatchSiren cyber security CVE debrief

CVE-2026-50630 Apache Software Foundation CVE debrief

A CRLF injection vulnerability exists in the OAuth2 AuthorizationUtils class of Apache CXF. When constructing the WWW-Authenticate response header, the 'realm' parameter is concatenated without sanitizing Carriage Return (CR) and Line Feed (LF) characters. If an attacker can control the realm value, they can inject arbitrary HTTP headers or split the HTTP response entirely.

Vendor
Apache Software Foundation
Product
Apache CXF
CVSS
MEDIUM 6.5
CISA KEV
Not listed in stored evidence
Original CVE published
2026-06-12
Original CVE updated
2026-08-07
Advisory published
2026-06-12
Advisory updated
2026-08-07

Who should care

Users of Apache CXF versions prior to 4.2.2 or 4.1.7 should upgrade to a fixed version to prevent potential CRLF injection attacks.

Technical summary

The vulnerability exists in the OAuth2 AuthorizationUtils class of Apache CXF. The 'realm' parameter in the WWW-Authenticate response header is not sanitized for CR and LF characters, allowing for potential injection of arbitrary HTTP headers or splitting of the HTTP response.

Defensive priority

MEDIUM

Recommended defensive actions

  • Upgrade to Apache CXF version 4.2.2 or 4.1.7 to fix the CRLF injection vulnerability.

Evidence notes

The vulnerability has a CVSS score of 6.5 and is classified as MEDIUM severity.

Sources and references

Verified primary and authoritative sources

  • CVE-2026-50630 CVE Program record

    Publisher, destination, and source semantics verified

    URL: https://www.cve.org/CVERecord?id=CVE-2026-50630

    CVE Program - Official CVE Program record with source-provided CVE metadata.

  • CVE-2026-50630 NVD vulnerability detail

    Publisher, destination, and source semantics verified

    URL: https://nvd.nist.gov/vuln/detail/CVE-2026-50630

    NIST National Vulnerability Database - Official NIST NVD detail page and source-specific vulnerability assessment.

Supplemental references

Methodology and review provenance

AI-assisted synthesis based on stored public vulnerability evidence. System validation, approval state, and publication status do not by themselves establish human review of this revision. PatchSiren helps prioritize defensive review and does not prove exposure or remediation on any system.