CVE-2020-11182 in Snapdragon Auto
Summary
by MITRE • 06/09/2021
Possible heap overflow while parsing NAL header due to lack of check of length of data received from user in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile
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Analysis
by VulDB Data Team • 06/11/2021
This vulnerability represents a critical heap overflow condition that occurs during the parsing of Network Abstraction Layer (NAL) headers within Qualcomm Snapdragon automotive and mobile platform components. The flaw stems from insufficient validation of input data length parameters received from external sources, creating a potential exploitation vector that could allow remote code execution or system compromise. The vulnerability affects multiple Snapdragon product lines including automotive systems, compute platforms, connectivity solutions, consumer IoT devices, industrial IoT applications, and mobile processors, indicating a widespread impact across Qualcomm's embedded system portfolio. The root cause aligns with CWE-122, Heap-based Buffer Overflow, where inadequate bounds checking allows maliciously crafted data to overwrite adjacent heap memory regions, potentially leading to arbitrary code execution or denial of service conditions.
The technical implementation of this vulnerability occurs during the NAL header parsing routine where the system fails to validate the length field contained within the received data stream before proceeding with memory allocation or data processing operations. When parsing video or multimedia streams, the system expects specific length values that define the size of subsequent data segments, but without proper validation, an attacker can manipulate these length fields to trigger buffer overflow conditions. This parsing behavior creates a direct pathway for memory corruption attacks, particularly when the system attempts to allocate heap memory based on user-supplied length parameters that exceed expected boundaries or when the system processes data segments that are larger than allocated buffer space. The vulnerability is particularly concerning in automotive contexts where real-time processing of multimedia data streams is common, as it could potentially affect vehicle infotainment systems, telematics units, or advanced driver assistance systems.
The operational impact of this vulnerability extends across multiple domains within Qualcomm's automotive and mobile ecosystems, affecting systems that process real-time multimedia data streams including video codecs, audio processing units, and communication protocols. Attackers could potentially exploit this vulnerability through maliciously crafted multimedia content delivered via network connections, USB devices, or wireless communication channels, leading to unauthorized system access, data exfiltration, or complete system compromise. The widespread nature of affected platforms suggests that both consumer and industrial applications could be at risk, with automotive systems potentially facing critical safety implications if the vulnerability leads to unauthorized control of vehicle functions. This type of vulnerability is categorized under ATT&CK technique T1059.007 for Command and Scripting Interpreter, as exploitation could enable attackers to execute arbitrary code on affected systems, and T1203 for Exploitation for Client Execution, since the vulnerability can be triggered through legitimate system interfaces used for multimedia processing.
Mitigation strategies for this vulnerability should include immediate firmware updates from Qualcomm that implement proper input validation and bounds checking for NAL header length fields, alongside runtime protections such as stack canaries, address space layout randomization, and heap memory protection mechanisms. System architects should implement defensive programming practices including comprehensive input validation, proper memory allocation routines, and robust error handling procedures that prevent malformed data from causing buffer overflow conditions. Organizations deploying affected Snapdragon platforms should conduct thorough vulnerability assessments to identify potential attack vectors and implement network segmentation to limit exposure to untrusted data sources. Additionally, monitoring systems should be deployed to detect anomalous behavior patterns that may indicate exploitation attempts, particularly around multimedia processing interfaces and network communication channels. The remediation approach should align with industry best practices for secure coding standards and should be complemented by regular security audits to ensure proper implementation of input validation mechanisms across all affected system components.