CVE-2025-1764
March 14, 2025, 6:15 a.m.
7.5
High
Description
The LoginPress | wp-login Custom Login Page Customizer plugin for WordPress is vulnerable to Cross-Site Request Forgery in all versions up to, and including, 3.3.1. This is due to missing or incorrect nonce validation on the 'custom_plugin_set_option' function. This makes it possible for unauthenticated attackers to update arbitrary options on the WordPress site via a forged request granted they can trick a site administrator into performing an action such as clicking on a link. This can be leveraged to update the default role for registration to administrator and enable user registration for attackers to gain administrative user access to a vulnerable site. The 'WPBRIGADE_SDK__DEV_MODE' constant must be set to 'true' to exploit the vulnerability.
Product(s) Impacted
| Product | Versions |
|---|---|
| wordpress |
|
| loginpress |
|
| loginpress |
|
| loginpress |
|
| loginpress |
|
| loginpress |
|
| loginpress |
|
| loginpress_wp-login_custom_login_page_customizer |
|
| wp-login_custom_login_page_customizer |
|
| loginpress |
|
| loginpress |
|
| custom_login_page_customizer |
|
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.
Tags
CVSS Score
CVSS Data - 3.1
- Attack Vector: NETWORK
- Attack Complexity: HIGH
- Privileges Required: NONE
- Scope: UNCHANGED
- Confidentiality Impact: HIGH
- Integrity Impact: HIGH
- Availability Impact: HIGH
CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H
Timeline
Published: March 14, 2025, 6:15 a.m.
Last Modified: March 14, 2025, 6:15 a.m.
Last Modified: March 14, 2025, 6:15 a.m.
Status : Received
CVE has been recently published to the CVE List and has been received by the NVD.
More infoSource
security@wordfence.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.