CVE-2026-2352
March 21, 2026, 12:16 a.m.
6.4
Medium
Description
The Autoptimize plugin for WordPress is vulnerable to Stored Cross-Site Scripting via the 'ao_post_preload' meta value in all versions up to, and including, 3.1.14. This is due to insufficient input sanitization in the `ao_metabox_save()` function and missing output escaping when the value is rendered into a `<link>` tag in `autoptimizeImages.php`. 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, granted the "Image optimization" or "Lazy-load images" setting is enabled in the plugin configuration.
Product(s) Impacted
| Vendor | Product | Versions |
|---|---|---|
| Wordpress |
|
|
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 | autoptimize | <3.1.14 | / | / | / | / | wordpress | / | / |
References
Tags
CVSS Score
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
Timeline
Published: March 21, 2026, 12:16 a.m.
Last Modified: March 21, 2026, 12:16 a.m.
Last Modified: March 21, 2026, 12:16 a.m.
Status : Received
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.