CVE-2026-4133
April 22, 2026, 8:22 p.m.
4.3
Medium
Description
The TextP2P Texting Widget plugin for WordPress is vulnerable to Cross-Site Request Forgery in all versions up to and including 1.7. This is due to missing nonce validation in the imTextP2POptionPage() function which processes settings updates. The form at line 314 does not include a wp_nonce_field(), and the POST handler at line 7 does not call check_admin_referer() or wp_verify_nonce() before processing settings changes. This makes it possible for unauthenticated attackers to update all plugin settings including chat widget titles, messages, API credentials, colors, and reCAPTCHA configuration via a forged request, granted they can trick a site administrator into performing an action such as clicking a link.
Product(s) Impacted
| Vendor | Product | Versions |
|---|---|---|
| Wordpress |
|
|
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 | wordpress | textp2p_texting_widget | / | / | / | / | / | wordpress | / | / |
References
Tags
CVSS Score
CVSS Data - 3.1
- Attack Vector: NETWORK
- Attack Complexity: LOW
- Privileges Required: NONE
- Scope: UNCHANGED
- Confidentiality Impact: NONE
- Integrity Impact: LOW
- Availability Impact: NONE
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:L/A:N
Timeline
Published: April 22, 2026, 9:16 a.m.
Last Modified: April 22, 2026, 8:22 p.m.
Last Modified: April 22, 2026, 8:22 p.m.
Status : Deferred
CVE has been recently published to the CVE List and has been received by the NVD.
More infoSource
*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.