CVE-2025-26533: Moodle SQL Injection Vulnerability

CVE-2025-26533 Overview

CVE-2025-26533 is a critical SQL injection vulnerability discovered in the module list filter functionality within Moodle's course search feature. This vulnerability allows unauthenticated remote attackers to inject malicious SQL queries through the course search interface, potentially leading to complete database compromise, unauthorized data access, and system integrity violations.

SQL injection vulnerabilities in learning management systems like Moodle pose significant risks to educational institutions, as they can expose sensitive student records, grades, personal information, and administrative credentials.

Critical Impact

This SQL injection vulnerability allows unauthenticated attackers to manipulate database queries through the course search module filter, potentially enabling complete database access, data exfiltration, and system compromise.

Affected Products

• Moodle (multiple versions)
• Moodle Learning Management System with course search functionality enabled
• Self-hosted and managed Moodle installations with vulnerable module list filter components

Discovery Timeline

• 2025-02-24 - CVE-2025-26533 published to NVD
• 2025-08-06 - Last updated in NVD database

Technical Details for CVE-2025-26533

Vulnerability Analysis

The vulnerability exists within the module list filter component of Moodle's course search functionality. This SQL injection flaw (CWE-89) occurs due to improper sanitization of user-supplied input in the module list filter parameters. When users interact with the course search feature, the filter values are incorporated into SQL queries without adequate validation or parameterization.

The vulnerability is particularly severe because it does not require authentication to exploit. An attacker with network access to a vulnerable Moodle installation can craft malicious requests to the course search endpoint, injecting arbitrary SQL commands that execute with the database user's privileges.

Successful exploitation could allow an attacker to read sensitive data from the database including user credentials, student records, and grade information. Beyond data theft, attackers could modify or delete database contents, potentially disrupting educational operations or manipulating academic records.

Root Cause

The root cause of CVE-2025-26533 is inadequate input validation and improper use of database query construction in the module list filter component. Instead of using parameterized queries or prepared statements, the vulnerable code directly incorporates user input into SQL query strings, creating a classic SQL injection attack surface. The filter parameters intended for narrowing course search results are processed without proper escaping or type validation.

Attack Vector

The attack vector is network-based and requires no authentication or user interaction. An attacker can exploit this vulnerability by sending specially crafted HTTP requests to the Moodle course search functionality with malicious SQL payloads embedded in the module list filter parameters.

The exploitation process involves identifying the vulnerable endpoint, crafting SQL injection payloads that manipulate the query logic, and extracting database information through techniques such as UNION-based injection, blind injection, or error-based extraction depending on the database configuration and error handling.

Detection Methods for CVE-2025-26533

Indicators of Compromise

• Unusual or malformed requests to course search endpoints containing SQL syntax characters (', ", ;, --, UNION, SELECT)
• Database error messages appearing in application logs or responses related to course search queries
• Unexpected database queries or access patterns originating from the Moodle web application
• Evidence of data exfiltration or unauthorized database reads in database audit logs

Detection Strategies

• Deploy web application firewall (WAF) rules to detect and block SQL injection patterns targeting course search functionality
• Monitor application logs for SQL error messages, particularly those referencing the module list filter or course search components
• Implement database activity monitoring to detect anomalous query patterns including UNION statements, subqueries, or time-delay functions
• Configure intrusion detection systems (IDS) with signatures for common SQL injection payloads

Monitoring Recommendations

• Enable verbose logging on Moodle application servers to capture detailed request parameters for course search operations
• Implement real-time alerting for database query anomalies and elevated privilege usage
• Review Moodle access logs regularly for suspicious patterns in course search requests
• Monitor for outbound data transfers that could indicate successful data exfiltration

How to Mitigate CVE-2025-26533

Immediate Actions Required

• Update Moodle to the latest patched version that addresses MDL-84271
• If immediate patching is not possible, consider temporarily disabling or restricting access to the course search functionality
• Review database access logs for evidence of prior exploitation attempts
• Implement WAF rules to block SQL injection attempts targeting the vulnerable endpoint

Patch Information

Moodle has released patches addressing this vulnerability under the tracking identifier MDL-84271. Administrators should apply the security update immediately by updating to the latest stable version of Moodle. Detailed patch information and commit history can be found in the Moodle Commit Log Entry. Additional discussion and guidance is available in the Moodle Forum Discussion Thread.

Workarounds

• Implement network-level access controls to restrict access to course search functionality to authenticated internal users only
• Deploy a web application firewall with SQL injection detection rules in front of Moodle installations
• Use database connection accounts with minimal required privileges to limit the impact of successful SQL injection
• Consider disabling the module list filter in course search until patches can be applied

# Configuration example - Restrict access to course search at web server level
# Apache example - Add to .htaccess or virtual host configuration
<Location "/course/search.php">
    Require valid-user
    # Or restrict to specific IP ranges
    # Require ip 192.168.1.0/24
</Location>

# Nginx example - Add to server block
location /course/search.php {
    auth_basic "Restricted Access";
    auth_basic_user_file /etc/nginx/.htpasswd;
    # Or restrict by IP
    # allow 192.168.1.0/24;
    # deny all;
}