CVE-2022-22101 in Snapdragon Auto
Summary
by MITRE • 09/02/2022
Denial of service in multimedia due to uncontrolled resource consumption while parsing an incoming HAB message in Snapdragon Auto
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Analysis
by VulDB Data Team • 10/11/2022
This vulnerability represents a critical denial of service condition affecting multimedia processing capabilities within automotive systems utilizing Qualcomm Snapdragon Auto platforms. The flaw manifests during the parsing of HAB (Hardware Abstraction Bundle) messages, which are essential components for managing hardware interactions and multimedia operations in vehicle infotainment and telematics systems. The vulnerability stems from insufficient resource management controls during message processing, allowing malicious or malformed HAB messages to trigger uncontrolled consumption of system resources such as memory, CPU cycles, and processing threads. This uncontrolled resource utilization ultimately leads to system instability and complete service disruption, effectively rendering the affected multimedia functionality inaccessible to legitimate users.
The technical implementation of this vulnerability aligns with CWE-400, which categorizes uncontrolled resource consumption as a fundamental weakness in software design. The flaw demonstrates characteristics of resource exhaustion attacks where an attacker can manipulate incoming HAB messages to cause the system to allocate excessive resources without proper bounds checking or resource limits. The Snapdragon Auto platform's multimedia processing pipeline becomes overwhelmed when encountering specially crafted HAB messages that trigger recursive parsing operations or infinite loops in the message handling code. This represents a classic example of insufficient resource management controls that can be exploited through input validation failures. The vulnerability is particularly concerning in automotive environments where multimedia systems are critical for driver information, entertainment, and safety-related communications.
The operational impact of this vulnerability extends beyond simple service disruption to potentially compromising vehicle safety systems and user experience. When the multimedia processing subsystem becomes unresponsive due to resource exhaustion, drivers may lose access to navigation, communication, and entertainment features that are increasingly integrated into modern vehicle operations. The vulnerability affects automotive systems that rely on Snapdragon Auto for multimedia processing, including infotainment systems, digital instrument clusters, and connected vehicle services. Attackers could exploit this vulnerability to create persistent denial of service conditions that require system reboot or manual intervention to resolve, potentially leaving vehicles inoperable during critical driving situations. The automotive industry's increasing reliance on connected systems makes this vulnerability particularly dangerous as it could be exploited to disrupt vehicle functionality in ways that compromise driver safety and vehicle operation.
Mitigation strategies for this vulnerability should focus on implementing robust input validation and resource consumption limits within the HAB message parsing framework. System architects should deploy defensive programming practices including maximum message size limits, parsing timeouts, and resource allocation quotas to prevent uncontrolled consumption. The implementation of proper error handling and graceful degradation mechanisms can help maintain system stability even when malformed messages are received. Organizations should also consider network segmentation and message filtering approaches to prevent potentially malicious HAB messages from reaching vulnerable systems. Additionally, regular firmware updates and security patches should be implemented to address known vulnerabilities in Snapdragon Auto platforms. The mitigation approach should align with automotive cybersecurity frameworks such as ISO/SAE 21434 and NIST Cybersecurity Framework to ensure comprehensive protection against resource exhaustion attacks. System monitoring and anomaly detection capabilities should be enhanced to identify unusual resource consumption patterns that may indicate exploitation attempts.