CVE-2026-30876 in LMS
Summary
by MITRE • 03/16/2026
Chamilo LMS is a learning management system. Prior to version 1.11.36, Chamilo is vulnerable to user enumeration with valid/invalid username. This issue has been patched in version 1.11.36.
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Analysis
by VulDB Data Team • 03/21/2026
The vulnerability identified as CVE-2026-30876 affects Chamilo LMS, a widely used learning management system that serves educational institutions worldwide. This security flaw represents a significant concern for organizations relying on the platform for their digital learning infrastructure. The vulnerability specifically manifests as user enumeration, a technique that allows attackers to determine the existence of valid user accounts within the system. This issue impacts versions prior to 1.11.36, indicating that the developers have acknowledged and addressed the problem in their subsequent releases. The vulnerability's classification aligns with CWE-203, which describes "Information Exposure Through Discrepancy in List of Available Resources," as it reveals information about user accounts through inconsistent responses to authentication attempts.
The technical implementation of this vulnerability stems from improper handling of authentication requests within the Chamilo LMS platform. When users attempt to log in with different credentials, the system provides varying responses that inadvertently disclose whether a username exists in the database. This behavior occurs because the application does not implement consistent error messaging for both valid and invalid usernames, creating a distinguishable pattern that attackers can exploit. The flaw essentially creates a side-channel attack vector where the timing or content of error responses provides sufficient information to enumerate valid user accounts. This vulnerability directly relates to the ATT&CK technique T1078.004, which covers "Valid Accounts: Cloud Accounts," as it enables unauthorized access to legitimate user credentials through systematic enumeration.
The operational impact of this vulnerability extends beyond simple information disclosure, as it significantly weakens the overall security posture of organizations using Chamilo LMS. Attackers can systematically test usernames to identify valid accounts, which then enables them to launch targeted password spraying or brute force attacks against those specific accounts. This enumeration capability dramatically reduces the time and effort required to compromise user accounts, making the system more vulnerable to unauthorized access. The vulnerability particularly affects educational institutions that may have hundreds or thousands of user accounts, as attackers can efficiently identify high-value targets such as administrators, instructors, or students with privileged access. Organizations using older versions of Chamilo LMS face increased risk of credential compromise, potential data breaches, and unauthorized access to sensitive educational content and user information.
Organizations should immediately implement mitigation strategies to address this vulnerability while planning for the necessary software updates. The most effective immediate solution involves updating to Chamilo LMS version 1.11.36 or later, which contains the necessary patches to resolve the user enumeration issue. System administrators should also implement additional protective measures such as rate limiting for authentication attempts, account lockout mechanisms, and monitoring for suspicious login patterns. The implementation of consistent error messaging for all authentication attempts, regardless of whether the username exists, prevents attackers from distinguishing between valid and invalid accounts. Security teams should conduct comprehensive audits of their Chamilo LMS installations to identify any systems still running vulnerable versions and ensure that all user accounts are properly secured through multi-factor authentication and strong password policies. Additionally, network-level controls such as intrusion detection systems can help monitor for patterns consistent with user enumeration attacks, providing early warning capabilities for potential security incidents.