CVE-2026-7421

June 4, 2026, 1:53 p.m.

4.4
Medium

Description

The Passeum Ticketing plugin for WordPress is vulnerable to Stored Cross-Site Scripting in all versions up to, and including, 1.0. This is due to the `get_shop_url()` method returning the `shop_name` setting value without sanitization when it begins with "http", combined with insufficient validation in the `validate_shop_name()` function which only checks for empty values and string type. This makes it possible for authenticated attackers, with Administrator-level access and above, to inject arbitrary external scripts by setting the `shop_name` to an attacker-controlled URL (e.g., `https://attacker.com`), which causes the plugin to enqueue external JavaScript and CSS from the attacker-controlled domain via `wp_register_script()` and `wp_register_style()`. The injected scripts execute on every frontend page containing any Passeum Ticketing shortcode, affecting all site visitors. Please note that this does not affect single-site installations as administrators already have the `unfiltered_html` capability.

Product(s) Impacted

Vendor Product Versions
Wordpress
  • Passeum Ticketing
  • *

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.

CVSS Score

4.4 / 10

CVSS Data - 3.1

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

    View Vector String

Timeline

Published: June 3, 2026, 12:16 a.m.
Last Modified: June 4, 2026, 1:53 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.