CVE-2026-27589

Feb. 25, 2026, 5:08 p.m.

6.9
Medium

Description

Caddy is an extensible server platform that uses TLS by default. Prior to version 2.11.1, the local caddy admin API (default listen `127.0.0.1:2019`) exposes a state-changing `POST /load` endpoint that replaces the entire running configuration. When origin enforcement is not enabled (`enforce_origin` not configured), the admin endpoint accepts cross-origin requests (e.g., from attacker-controlled web content in a victim browser) and applies an attacker-supplied JSON config. This can change the admin listener settings and alter HTTP server behavior without user intent. Version 2.11.1 contains a fix for the issue.

Product(s) Impacted

Vendor Product Versions
Caddyserver
  • Caddy
  • *

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-352
Cross-Site Request Forgery (CSRF)
The web application does not, or can not, sufficiently verify whether a well-formed, valid, consistent request was intentionally provided by the user who submitted the request.

*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 caddyserver caddy / / / / / / / /

CVSS Score

6.9 / 10

CVSS Data - 4.0

  • Attack Vector: NETWORK
  • Attack Complexity: LOW
  • Attack Requirements: PRESENT
  • Privileges Required: NONE
  • User Interaction: NONE
  • Scope:
  • Confidentiality Impact: NONE
  • Integrity Impact: HIGH
  • Availability Impact: NONE
  • Exploit Maturity: PROOF_OF_CONCEPT
  • CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:N/VC:N/VI:H/VA:N/SC:N/SI:N/SA:N/E:P/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X

    View Vector String

Timeline

Published: Feb. 24, 2026, 5:29 p.m.
Last Modified: Feb. 25, 2026, 5:08 p.m.

Status : Analyzed

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

More info

*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.