CVE-2018-16971 in Learning Ecosystem
Summary
by MITRE
Wisetail Learning Ecosystem (LE) through v4.11.6 allows insecure direct object reference (IDOR) attacks to access non-purchased course contents (quiz / test) via a modified id parameter.
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Analysis
by VulDB Data Team • 03/23/2020
The vulnerability identified as CVE-2018-16971 affects the Wisetail Learning Ecosystem platform, specifically versions up to and including v4.11.6. This issue represents a critical insecure direct object reference flaw that undermines the platform's access control mechanisms. The vulnerability manifests when users manipulate the id parameter in URL requests to gain unauthorized access to course materials that they have not purchased or otherwise authorized to view. This type of vulnerability directly violates fundamental security principles by allowing attackers to bypass normal authentication and authorization checks through simple parameter modification.
The technical implementation of this vulnerability stems from improper validation of user input within the platform's content access system. When users request specific course materials such as quizzes or tests, the system relies on an id parameter to identify and retrieve the appropriate content. However, the application fails to properly verify whether the authenticated user has legitimate access rights to the requested resource before serving the content. This lack of proper access control validation creates a direct object reference vulnerability where attackers can simply modify the id parameter to reference different course materials and gain access to restricted content. The vulnerability aligns with CWE-284, which specifically addresses improper access control, and represents a classic case of insufficient authorization checking in web applications.
The operational impact of this vulnerability extends beyond simple unauthorized content access, potentially exposing sensitive educational materials and assessment data to unauthorized users. Attackers could exploit this flaw to access premium course content, including quizzes and tests that contain proprietary questions and answers, thereby compromising the integrity of the learning ecosystem. This vulnerability particularly affects the platform's business model, as it allows users to access paid content without proper payment verification. The exposure of assessment materials could lead to academic dishonesty, compromise test security, and potentially result in significant financial losses for the platform provider. Additionally, the vulnerability could be leveraged to gather competitive intelligence about premium course offerings and content structure.
Mitigation strategies for this vulnerability should focus on implementing robust access control mechanisms throughout the application's architecture. The primary remediation involves strengthening input validation and implementing proper authorization checks before serving any requested content. The platform should employ a comprehensive access control matrix that validates user permissions against requested resources using a combination of session-based authentication, role-based access control, and proper object reference validation. Implementing parameterized queries and ensuring that all content requests are properly authenticated and authorized will prevent attackers from manipulating URL parameters to access unauthorized resources. Organizations should also consider implementing the principle of least privilege, ensuring that users can only access content they have legitimately purchased or been granted access to. Security monitoring and logging should be enhanced to detect suspicious access patterns and parameter manipulation attempts. This vulnerability demonstrates the critical importance of proper access control implementation and aligns with ATT&CK technique T1078 which covers valid accounts and credential manipulation for privilege escalation. Regular security testing including penetration testing and vulnerability assessments should be conducted to identify and remediate similar access control flaws in the platform's architecture.