CVE-2025-66581

Dec. 11, 2025, 12:08 a.m.

1.3
Low

Description

Frappe Learning Management System (LMS) is a learning system that helps users structure their content. Prior to 2.41.0, a flaw in the server-side authorization logic allowed authenticated users to perform actions beyond their assigned roles across multiple features. Because the affected endpoints relied on client-side or UI-level checks instead of enforcing permissions on the server, users with low-privileged roles (such as students) could perform operations intended only for instructors or administrators via directly using the API's. This vulnerability is fixed in 2.41.0.

Product(s) Impacted

Vendor Product Versions
Frappe
  • Learning
  • *

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-863
Incorrect Authorization
The product performs an authorization check when an actor attempts to access a resource or perform an action, but it does not correctly perform the check. This allows attackers to bypass intended access restrictions.

*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 frappe learning / / / / / / / /

CVSS Score

1.3 / 10

CVSS Data - 4.0

  • Attack Vector: NETWORK
  • Attack Complexity: LOW
  • Attack Requirements: NONE
  • Privileges Required: LOW
  • User Interaction: NONE
  • Scope:
  • Confidentiality Impact: NONE
  • Integrity Impact: LOW
  • Availability Impact: LOW
  • Exploit Maturity: UNREPORTED
  • CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:L/VA:L/SC:N/SI:N/SA:N/E:U/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: Dec. 5, 2025, 7:15 p.m.
Last Modified: Dec. 11, 2025, 12:08 a.m.

Status : Analyzed

CVE has had analysis completed and all data associations made.

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.