CVE-2025-62797

Oct. 29, 2025, 7:15 p.m.

8.6
High

Description

FluxCP is a web-based Control Panel for rAthena servers written in PHP. A critical Cross-Site Request Forgery (CSRF) vulnerability exists in the FluxCP-based website template used by multiple rAthena/Ragnarok servers. State-changing POST endpoints accept browser-initiated requests that are authorized solely by the session cookie without per-request anti-CSRF tokens or robust Origin/Referer validation. An attacker who can lure a logged-in user to an attacker-controlled page can cause that user to perform sensitive actions without their intent. This vulnerability is fixed with commit e3f130c.

Product(s) Impacted

Vendor Product Versions
Rathena
  • Fluxcp
  • *

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 rathena fluxcp / / / / / / / /

CVSS Score

8.6 / 10

CVSS Data - 4.0

  • Attack Vector: NETWORK
  • Attack Complexity: LOW
  • Attack Requirements: NONE
  • Privileges Required: NONE
  • User Interaction: PASSIVE
  • Scope:
  • Confidentiality Impact: HIGH
  • Integrity Impact: HIGH
  • Availability Impact: NONE
  • Exploit Maturity: NOT_DEFINED
  • CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:H/VI:H/VA:N/SC:N/SI:N/SA:N/E:X/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: Oct. 29, 2025, 6:15 p.m.
Last Modified: Oct. 29, 2025, 7:15 p.m.

Status : Received

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

More info

Source

security-advisories@github.com

*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.