CVE-2026-11603

June 9, 2026, 1:33 p.m.

6.1
Medium

Description

The Product Filter Widget for Elementor plugin for WordPress is vulnerable to Reflected Cross-Site Scripting via 'args[filterFormArray]' Parameter in all versions up to, and including, 1.0.6 due to insufficient input sanitization and output escaping. This makes it possible for unauthenticated attackers to inject arbitrary web scripts in pages that execute if they can successfully trick a user into performing an action such as clicking on a link. The endpoint is registered via wp_ajax_nopriv_ with no nonce verification or capability check, and exploitation is delivered via a CSRF-style form auto-submission to the admin-ajax.php endpoint, requiring the attacker to trick a victim into visiting an attacker-controlled page.

Product(s) Impacted

Vendor Product Versions
Wordpress
  • Product Filter Widget For Elementor
  • *

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-79
Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')
The product does not neutralize or incorrectly neutralizes user-controllable input before it is placed in output that is used as a web page that is served to other users.

*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 product_filter_widget_for_elementor / / / / / wordpress / /

CVSS Score

6.1 / 10

CVSS Data - 3.1

  • Attack Vector: NETWORK
  • Attack Complexity: LOW
  • Privileges Required: NONE
  • Scope: CHANGED
  • Confidentiality Impact: LOW
  • Integrity Impact: LOW
  • Availability Impact: NONE
  • CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:L/I:L/A:N

    View Vector String

Timeline

Published: June 9, 2026, 5:16 a.m.
Last Modified: June 9, 2026, 1:33 p.m.

Status : Deferred

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.