CVE-2026-4895

April 11, 2026, 2:16 a.m.

6.4
Medium

Description

The GreenShift - Animation and Page Builder Blocks plugin for WordPress is vulnerable to Stored Cross-Site Scripting in versions up to, and including, 12.8.9 This is due to insufficient input sanitization and output escaping in the gspb_greenShift_block_script_assets() function. The function uses str_replace() to insert 'fetchpriority="high"' before 'src=' attributes when processing greenshift-blocks/image blocks with the disablelazy attribute enabled. Because this replacement operates on the entire HTML string without parsing, contributors can inject the string 'src=' into HTML attribute values (such as class attributes). When the str_replace executes, the double quotes in the replacement string break out of the attribute context, allowing injection of malicious HTML attributes like onfocus with JavaScript payloads. This makes it possible for authenticated attackers, with contributor-level access and above, to inject arbitrary web scripts in pages that will execute whenever a user accesses an injected page.

Product(s) Impacted

Vendor Product Versions
Wordpress
  • Greenshift
  • *

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

6.4 / 10

CVSS Data - 3.1

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

    View Vector String

Timeline

Published: April 11, 2026, 2:16 a.m.
Last Modified: April 11, 2026, 2:16 a.m.

Status : Received

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.