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PatchSiren cyber security CVE debrief

CVE-2026-42946 F5 CVE debrief

A vulnerability exists in the ngx_http_scgi_module and ngx_http_uwsgi_module modules of NGINX that may result in excessive memory allocation or an over-read of data. When scgi_pass or uwsgi_pass is configured, an unauthenticated attacker with man-in-the-middle (MITM) ability to control responses from an upstream server may be able to read the memory of the NGINX worker process or restart it.

Vendor
F5
Product
NGINX Plus
CVSS
HIGH 8.3
CISA KEV
Not listed in stored evidence
Original CVE published
2026-05-13
Original CVE updated
2026-06-18
Advisory published
2026-05-13
Advisory updated
2026-06-18

Who should care

Users of NGINX who have configured scgi_pass or uwsgi_pass are potentially affected by this vulnerability.

Technical summary

The vulnerability exists in the ngx_http_scgi_module and ngx_http_uwsgi_module modules of NGINX. An unauthenticated attacker with MITM ability to control responses from an upstream server may be able to read the memory of the NGINX worker process or restart it.

Defensive priority

HIGH

Recommended defensive actions

  • Apply patches or updates provided by the vendor to address the vulnerability.
  • Configure NGINX to use secure communication protocols to prevent MITM attacks.
  • Monitor NGINX worker process memory usage and restart the process if necessary.

Evidence notes

The vulnerability has a CVSS score of 8.3 and is considered HIGH severity.

Sources and references

Verified primary and authoritative sources

  • CVE-2026-42946 CVE Program record

    Publisher, destination, and source semantics verified

    URL: https://www.cve.org/CVERecord?id=CVE-2026-42946

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

  • CVE-2026-42946 NVD vulnerability detail

    Publisher, destination, and source semantics verified

    URL: https://nvd.nist.gov/vuln/detail/CVE-2026-42946

    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.