CVE-2009-0656 in SmartLogon
Summary
by MITRE
Asus SmartLogon 1.0.0005 allows physically proximate attackers to bypass "security functions" by presenting an image with a modified viewpoint that matches the posture of a stored image of the authorized notebook user.
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Analysis
by VulDB Data Team • 10/29/2018
This vulnerability affects Asus SmartLogon software version 1.0.0005 which implements a biometric authentication system using facial recognition for notebook computers. The flaw resides in the system's inability to properly validate the authenticity of presented facial images, creating a significant security weakness that can be exploited by attackers who are physically near the target device. The vulnerability specifically impacts the system's posture recognition capabilities and demonstrates a critical failure in implementing proper anti-spoofing measures.
The technical implementation of this vulnerability stems from the system's reliance on static posture matching without adequate verification mechanisms. When an authorized user's facial image is stored in the system's database, the software creates a reference posture that is later used for authentication. Attackers can exploit this by creating or presenting an image that matches the stored posture characteristics while maintaining a different viewpoint, effectively fooling the system into recognizing the unauthorized individual as legitimate. This represents a classic case of insufficient anti-spoofing controls that allows for presentation attacks against biometric systems.
The operational impact of this vulnerability is substantial as it fundamentally undermines the security model of the authentication system. An attacker with physical proximity to the target device can bypass security functions without requiring sophisticated equipment or advanced technical knowledge. This creates a risk where unauthorized individuals can gain access to systems that should be protected by biometric authentication, potentially leading to data breaches, unauthorized system access, and compromise of sensitive information. The vulnerability essentially renders the biometric authentication mechanism ineffective against determined attackers who can simply present a matching image.
This vulnerability aligns with CWE-327, which addresses weak cryptographic algorithms and improper implementation of security functions. The flaw demonstrates a failure in implementing proper anti-spoofing measures and secure biometric authentication protocols. From an ATT&CK perspective, this vulnerability maps to T1078.004, which covers valid accounts used for unauthorized access, and T1566, which involves social engineering attacks through physical proximity. The attack vector specifically relates to physical access and presentation attacks that exploit weaknesses in biometric systems.
Organizations should implement immediate mitigations including disabling the vulnerable SmartLogon feature until a patched version is available, implementing additional authentication layers such as password requirements, and establishing physical security controls to prevent unauthorized proximity access. The system should be updated with proper anti-spoofing mechanisms that validate image authenticity through multiple factors including depth sensing, liveness detection, and dynamic posture analysis. Security administrators should also consider implementing monitoring and alerting for unusual authentication patterns and establish incident response procedures for potential unauthorized access attempts. The vulnerability highlights the importance of comprehensive security testing for biometric systems and the necessity of implementing robust anti-spoofing measures as outlined in industry standards such as NIST SP 800-64 and ISO/IEC 19795-1.