CVE-2026-30881 in LMS
Summary
by MITRE • 03/16/2026
Chamilo LMS is a learning management system. Version 1.11.34 and prior contains a SQL Injection vulnerability in the statistics AJAX endpoint. The parameters date_start and date_end from $_REQUEST are embedded directly into a raw SQL string without proper sanitization. Although Database::escape_string() is called downstream, its output is immediately neutralized by str_replace("\'", "'", ...), which restores any injected single quotes — effectively bypassing the escaping mechanism entirely. This allows an authenticated attacker to inject arbitrary SQL statements into the database query, enabling blind time-based and conditional data extraction. This issue has been patched in version 1.11.36.
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Analysis
by VulDB Data Team • 03/17/2026
The vulnerability identified as CVE-2026-30881 affects Chamilo LMS version 1.11.34 and earlier, representing a critical SQL injection flaw within the system's statistics AJAX endpoint. This vulnerability stems from improper input validation and sanitization practices that allow malicious actors to manipulate database queries through specifically crafted parameters. The flaw manifests in the handling of date_start and date_end parameters sourced from the $_REQUEST superglobal, which are directly incorporated into raw SQL strings without adequate protection mechanisms. The attack vector requires authentication, meaning that only users with valid credentials can exploit this vulnerability, though this does not diminish its potential impact on system integrity and data confidentiality.
The technical implementation of this vulnerability demonstrates a sophisticated bypass of intended security measures. While the code does invoke Database::escape_string() as a defensive mechanism, this protection is subsequently neutralized through a deliberate str_replace operation that restores single quotes in the escaped output. This design flaw creates a false sense of security while simultaneously providing an open pathway for SQL injection attacks. The vulnerability enables attackers to construct malicious SQL statements that can be executed within the database context, allowing for blind time-based SQL injection techniques and conditional data extraction methods. These attack patterns typically involve inferring database contents through response timing variations or conditional logic execution, making the exploitation particularly insidious and difficult to detect through standard monitoring systems.
The operational impact of this vulnerability extends beyond simple data theft, encompassing potential system compromise and unauthorized access to sensitive educational information. Given that Chamilo LMS serves as a learning management system, the exposed data could include student records, course materials, assessment results, and other confidential academic information. Attackers could leverage this vulnerability to extract database schema information, escalate privileges, or even modify system data, potentially disrupting educational operations and violating privacy regulations. The time-based blind injection techniques commonly employed in such scenarios can be particularly challenging to defend against since they do not produce immediate error messages or obvious data leakage patterns, making them difficult to detect through traditional security monitoring approaches.
Organizations utilizing affected versions of Chamilo LMS should prioritize immediate remediation through the upgrade to version 1.11.36, which contains the necessary patches to address this vulnerability. The fix implemented in the newer version likely involves proper parameterized queries or enhanced input sanitization that prevents the bypass of escaping mechanisms. Security teams should also implement comprehensive monitoring for unusual database query patterns and consider conducting penetration testing to identify any potential exploitation attempts. Additionally, implementing network-based intrusion detection systems and database activity monitoring solutions can provide early warning capabilities for detecting SQL injection attempts. The vulnerability aligns with CWE-89, which specifically addresses SQL injection flaws, and represents a typical example of how improper input validation can lead to severe security consequences. This issue also maps to ATT&CK technique T1071.004, which covers application layer protocol manipulation, specifically targeting web application interfaces for data exfiltration and system compromise.