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CVE-2025-22268: Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting') in Uncanny Owl Uncanny Toolkit for LearnDash

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Unknown
VulnerabilityCVE-2025-22268cvecve-2025-22268
Published: Tue Apr 15 2025 (04/15/2025, 21:53:09 UTC)
Source: CVE Database V5
Vendor/Project: Uncanny Owl
Product: Uncanny Toolkit for LearnDash

Description

Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting') vulnerability in Uncanny Owl Uncanny Toolkit for LearnDash uncanny-learndash-toolkit allows Stored XSS.This issue affects Uncanny Toolkit for LearnDash: from n/a through <= 3.7.0.1.

AI-Powered Analysis

Machine-generated threat intelligence

AILast updated: 04/02/2026, 02:43:40 UTC

Technical Analysis

CVE-2025-22268 is a stored cross-site scripting (XSS) vulnerability identified in the Uncanny Owl Uncanny Toolkit for LearnDash plugin, specifically affecting all versions up to 3.7.0.1. The vulnerability stems from improper neutralization of user-supplied input during the generation of web pages, allowing malicious scripts to be injected and stored persistently within the application’s data. When other users access the affected pages, the malicious scripts execute in their browsers, potentially compromising session tokens, cookies, or enabling unauthorized actions under the victim’s privileges. This type of vulnerability is particularly dangerous in multi-user environments such as e-learning platforms where users often have elevated trust and access. The vulnerability does not require prior authentication to exploit, increasing its risk profile, although user interaction is necessary to trigger the payload. Currently, there are no publicly known exploits in the wild, and no official patches or updates have been linked yet. The plugin is widely used in LearnDash-based WordPress e-learning sites, which are popular globally. The absence of a CVSS score necessitates a severity assessment based on impact and exploitability factors. Stored XSS vulnerabilities can lead to significant confidentiality and integrity breaches, including credential theft, session hijacking, and defacement or manipulation of content. The scope of affected systems includes any LearnDash installations using the vulnerable plugin version. Given the nature of the vulnerability and the environment it targets, the threat is substantial and warrants immediate attention from administrators.

Potential Impact

The impact of CVE-2025-22268 is significant for organizations using the Uncanny Toolkit for LearnDash plugin in their e-learning platforms. Successful exploitation can lead to the execution of arbitrary JavaScript in the context of users’ browsers, resulting in session hijacking, theft of sensitive information such as login credentials, and unauthorized actions performed on behalf of users. This can compromise the confidentiality and integrity of user data and potentially disrupt the availability of the e-learning service if attackers deface or manipulate content. Educational institutions, corporate training platforms, and any organization relying on LearnDash for online learning delivery are at risk. The stored nature of the XSS means that once injected, the malicious payload can affect multiple users over time, increasing the attack surface. Additionally, attackers could leverage this vulnerability as a foothold to escalate privileges or deploy further attacks within the network. The absence of known exploits in the wild currently limits immediate widespread impact, but the vulnerability’s presence in a widely used plugin makes it a high-value target for attackers once exploit code becomes available.

Mitigation Recommendations

To mitigate CVE-2025-22268, organizations should prioritize updating the Uncanny Toolkit for LearnDash plugin to a version that addresses this vulnerability as soon as a patch is released by the vendor. Until an official patch is available, administrators should implement strict input validation and output encoding on all user-supplied data fields within the plugin’s scope to neutralize potentially malicious scripts. Employing a Web Application Firewall (WAF) with rules designed to detect and block XSS payloads can provide an additional layer of defense. Regularly audit and sanitize existing stored content to remove any injected scripts. Educate users to be cautious about clicking on suspicious links or interacting with untrusted content within the e-learning environment. Monitoring logs for unusual activity or repeated attempts to inject scripts can help detect exploitation attempts early. Finally, consider isolating the LearnDash environment and applying the principle of least privilege to limit the potential damage from a successful attack.

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Technical Details

Data Version
5.2
Assigner Short Name
Patchstack
Date Reserved
2025-01-02T12:02:05.151Z
Cvss Version
null
State
PUBLISHED

Threat ID: 69cd75d4e6bfc5ba1df07f6f

Added to database: 4/1/2026, 7:45:24 PM

Last enriched: 4/2/2026, 2:43:40 AM

Last updated: 4/4/2026, 8:19:25 AM

Views: 7

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