CVE-2025-67850: Moodle Formula Editor XSS Vulnerability

CVE-2025-67850 Overview

A Cross-Site Scripting (XSS) vulnerability has been discovered in Moodle's formula editor component. This security flaw arises from insufficient validation and sanitization of user-provided data in the arithmetic expression fields of the formula editor. A remote attacker with low-level privileges can exploit this vulnerability by injecting malicious JavaScript code into these expression fields. When other users, including administrators or students, view pages containing the malicious expressions, the injected code executes within their web browsers in the context of the Moodle application.

Critical Impact

Attackers can execute arbitrary JavaScript code in victims' browsers, potentially leading to session hijacking, credential theft, data exfiltration, or unauthorized actions performed on behalf of legitimate users within the Moodle learning management system.

Affected Products

• Moodle LMS (specific versions not disclosed in advisory)
• Systems utilizing the Moodle formula editor component
• Educational institutions and organizations running vulnerable Moodle installations

Discovery Timeline

• 2026-02-03 - CVE-2025-67850 published to NVD
• 2026-02-03 - Last updated in NVD database

Technical Details for CVE-2025-67850

Vulnerability Analysis

This vulnerability is classified as a stored Cross-Site Scripting (XSS) flaw (CWE-79) affecting Moodle's formula editor functionality. The formula editor is designed to allow users to input mathematical and arithmetic expressions, which are then rendered for display to other users within the learning management system.

The security issue stems from the application's failure to properly validate, sanitize, or encode user-supplied input in the arithmetic expression fields before storing and subsequently rendering this content in the browsers of other users. This creates an opportunity for attackers to craft malicious payloads that bypass the existing input validation mechanisms.

When exploited, the attacker's JavaScript code executes with the same origin permissions as the Moodle application, granting access to session cookies, local storage, and the ability to perform actions on behalf of the victim user. In an educational environment, this could compromise student data, grades, course materials, or administrative functions.

Root Cause

The root cause of this vulnerability lies in insufficient input sanitization within Moodle's formula editor component. The arithmetic expression fields accept and store user input without adequately filtering or encoding potentially dangerous characters and script elements. When these expressions are rendered in the browser, the unsanitized content is interpreted as executable code rather than display text.

Specifically, the application fails to implement proper output encoding when displaying formula expressions, allowing HTML and JavaScript elements embedded in the input to be processed by the browser's rendering engine.

Attack Vector

The attack requires network access and can be executed remotely by an authenticated user with low-level privileges (such as a standard student account). User interaction is required as victims must view the page containing the malicious formula expression for the attack to succeed.

The attack flow typically proceeds as follows:

1. An attacker with a valid Moodle account accesses the formula editor
2. Instead of legitimate arithmetic expressions, the attacker injects JavaScript payloads into the expression fields
3. The malicious content is stored in the Moodle database
4. When other users (students, instructors, administrators) navigate to pages displaying the formula, the malicious script executes
5. The attacker can steal session tokens, perform actions as the victim, or redirect users to phishing sites

The vulnerability can be exploited by embedding JavaScript event handlers or script tags within the formula expression input. For example, crafted payloads might leverage techniques such as script injection within mathematical notation or exploitation of HTML entities that are improperly decoded during rendering. For detailed technical information, refer to the Red Hat CVE-2025-67850 Advisory.

Detection Methods for CVE-2025-67850

Indicators of Compromise

• Unusual JavaScript or HTML tags present in database entries for formula expressions
• User-submitted content containing <script>, onerror, onload, or similar event handler attributes
• Unexpected outbound network requests from client browsers when viewing formula content
• Reports of session hijacking or unauthorized account activity following visits to formula-containing pages

Detection Strategies

• Implement web application firewall (WAF) rules to detect XSS payloads in POST requests to formula editor endpoints
• Deploy content security policy (CSP) headers to prevent inline script execution and report violations
• Monitor application logs for patterns indicative of XSS injection attempts in formula-related API calls
• Utilize browser-based XSS auditor features and monitor for triggered alerts

Monitoring Recommendations

• Enable detailed logging for all user input submissions to the formula editor component
• Configure security information and event management (SIEM) systems to alert on XSS signature patterns
• Regularly audit stored formula expressions in the database for anomalous content
• Monitor for CSP violation reports that may indicate attempted exploitation

How to Mitigate CVE-2025-67850

Immediate Actions Required

• Review and apply the latest Moodle security patches addressing this vulnerability
• Audit existing formula expressions in the database for potentially malicious content
• Implement Content Security Policy (CSP) headers to restrict inline script execution
• Consider temporarily restricting access to the formula editor for untrusted users until patches are applied

Patch Information

Organizations should monitor official Moodle security announcements and apply relevant patches as soon as they become available. Additional details can be found in the Red Hat CVE-2025-67850 Advisory and the Red Hat Bug Report #2423838.

Workarounds

• Deploy a web application firewall (WAF) with XSS filtering capabilities in front of Moodle installations
• Implement strict Content Security Policy headers to mitigate the impact of XSS exploitation
• Restrict formula editor permissions to trusted users only until a patch is applied
• Enable Moodle's built-in security features for input sanitization where available

# Example CSP header configuration for Apache
# Add to .htaccess or Apache configuration
Header set Content-Security-Policy "default-src 'self'; script-src 'self'; style-src 'self' 'unsafe-inline'; img-src 'self' data:; object-src 'none'; frame-ancestors 'self';"