CVE-2026-64961 in Atutor
Summary
by MITRE • 08/20/2026
ATutor is vulnerable to authentication bypass . Although a token validation check is present in the auto-login functionality, the values required for token validation remain uninitialized in certain code paths. An unauthenticated attacker who can determine a user's identifier and registration timestamp can generate a valid token and authenticate as an existing user, including administrator, without knowing the password.
Product is no longer actively supported and the vulnerabilities have not been fixed. Only version 2.2.4 was tested and confirmed as vulnerable, other versions were not tested but might also be vulnerable.
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Analysis
by VulDB Data Team • 08/20/2026
The vulnerability in ATutor represents a critical authentication bypass flaw rooted in improper initialization of security tokens within the application's auto-login mechanism. Although the software implements a token validation check intended to verify user identity during automatic login processes, this safeguard is rendered ineffective due to uninitialized variables required for the cryptographic or logical verification process. In secure coding practices, any variable involved in generating or validating authentication credentials must be explicitly initialized to prevent undefined behavior that attackers can exploit. Here, the failure to initialize these specific values creates a gap where an attacker can manipulate the token generation logic. This is not merely a configuration error but a fundamental flaw in how the application handles state and security contexts during the auto-login sequence, allowing for the bypass of standard password-based authentication controls.
From a technical perspective, this vulnerability aligns with CWE-287, which describes Improper Authentication, specifically falling under scenarios where input validation or token generation is flawed due to uninitialized data states. The attacker's ability to generate a valid token relies on two pieces of information that are often publicly accessible or easily discoverable: the user identifier and the registration timestamp. By combining these known values with the application's predictable token generation algorithm, an unauthenticated actor can construct a session token that the server accepts as legitimate. This effectively allows the attacker to impersonate any existing user account without possessing their password. The severity of this issue is amplified by its potential impact on administrative accounts; if an administrator's identifier and registration date are known or guessable, full control over the system can be achieved, leading to complete compromise of confidentiality, integrity, and availability.
The operational impact of this vulnerability is severe, particularly in environments where ATutor hosts sensitive educational data or personal information. An attacker gaining administrative access can modify course content, steal student records, inject malicious code into learning materials, or use the server as a pivot point for further network attacks. Furthermore, because the product is no longer actively supported and these vulnerabilities have not been patched by the vendor, there are no official security updates available to remediate this issue. This lack of support means that organizations relying on ATutor must assume they remain exposed indefinitely unless they implement external mitigations or migrate to a maintained alternative platform. The fact that only version 2.2.4 was confirmed vulnerable suggests that while earlier versions might share the same codebase flaws, the risk is pervasive across the legacy product line due to shared architectural patterns in authentication handling.
To mitigate this risk, immediate action is required since patching through vendor updates is not an option. The most effective mitigation involves isolating ATutor from untrusted networks and restricting access via IP whitelisting or firewall rules if possible. Additionally, implementing a Web Application Firewall (WAF) with specific rule sets to detect and block anomalous token generation patterns can provide a layer of defense in depth. Organizations should also enforce strict monitoring for unusual login activities, particularly those originating from unknown IPs but using valid user identifiers. Long-term resolution requires migrating away from ATutor entirely to a modern, actively maintained learning management system that adheres to current security standards such as OWASP Top 10 guidelines regarding authentication and session management. Until migration occurs, treating the application with extreme caution and limiting its exposure is critical to preventing unauthorized access and subsequent data breaches.