CVE-2026-63229 in Koollab LMS
Summary
by MITRE • 07/29/2026
A pre-authentication blind SQL injection vulnerability in Koollab LMS allowed an unauthenticated attacker to use a time-based SQL oracle via the SSO OAuth endpoint to read sensitive database contents, including personally identifiable information, credentials, and valid JWT tokens that may enable account takeover.
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Analysis
by VulDB Data Team • 07/29/2026
This vulnerability represents a critical pre-authentication blind sql injection flaw within the koollab lms application that fundamentally undermines the system's security posture by allowing unauthenticated attackers to extract sensitive data through a time-based sql oracle technique. The vulnerability specifically manifests within the sso oauth endpoint, which serves as a primary authentication pathway for users connecting to the learning management system. Attackers can exploit this weakness without requiring any valid credentials or prior authentication, making the attack surface particularly dangerous as it bypasses all initial access controls and security mechanisms.
The technical implementation of this vulnerability leverages time-based sql injection techniques where attackers manipulate input parameters within the oauth endpoint to cause the database to delay its response times. This timing characteristic allows attackers to infer information through differential analysis, where each bit of data is extracted by observing the database's response delays. The attack chain begins with an unauthenticated attacker sending crafted requests containing malicious sql payloads through the sso oauth authentication flow, which then triggers database operations that reveal sensitive information through these timing variations.
The operational impact of this vulnerability extends far beyond simple data exposure, as it provides attackers with access to personally identifiable information including user names, email addresses, and other personal details stored within the database. More critically, the vulnerability enables attackers to extract valid jwt tokens which serve as the primary authentication mechanism for accessing user accounts and system resources. These stolen tokens can be used for immediate account takeover, allowing unauthorized users to assume legitimate identities and access restricted content, modify user permissions, or even escalate privileges within the system.
The security implications of this vulnerability align with common weakness enumeration cwe-89 which specifically addresses sql injection flaws, and it demonstrates characteristics consistent with attack technique t1213 from the att&ck framework related to external remote exploitation. This vulnerability represents a sophisticated attack vector that exploits the trust placed in the sso oauth endpoint while bypassing all standard authentication mechanisms, making it particularly dangerous for organizations relying on this learning management system for educational or corporate training purposes.
Organizations should implement immediate mitigations including input validation and parameterized queries within the sso oauth endpoint to prevent sql injection exploitation. Database access controls should be strengthened through proper privilege management, ensuring that applications use least-privilege access patterns when interacting with database systems. Additionally, implementing comprehensive monitoring and logging of authentication endpoints can help detect anomalous access patterns indicative of time-based sql injection attacks, while regular security assessments should verify proper implementation of sql injection prevention techniques throughout the application stack.
The vulnerability also highlights the importance of secure coding practices specifically addressing oauth implementation security, as the sso endpoint serves as a critical attack surface for credential theft and account takeover operations. Organizations must ensure that all authentication endpoints properly validate and sanitize input parameters while implementing robust error handling mechanisms that do not expose database internals or timing characteristics to potential attackers. Regular penetration testing and vulnerability assessments should target authentication flows specifically, as these components represent the most valuable targets for unauthorized access attempts within learning management systems and similar web applications.