CVE-2020-11126 in Snapdragon Auto
Summary
by MITRE • 06/09/2021
Possible out of bound read while WLAN frame parsing due to lack of check for body and header length in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer Electronics Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wired Infrastructure and Networking
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Analysis
by VulDB Data Team • 06/11/2021
This vulnerability represents a critical buffer overread condition in Qualcomm's Snapdragon chipset family that affects multiple automotive and consumer connectivity platforms. The flaw occurs during wireless local area network frame processing where insufficient validation of frame header and body lengths leads to potential memory access violations. The vulnerability manifests when the system attempts to parse incoming wlan frames without proper bounds checking, creating opportunities for attackers to manipulate frame structures to trigger out-of-bounds memory reads. This issue impacts a broad range of Qualcomm's automotive and IoT product lines including Snapdragon Auto, Compute, Connectivity, Consumer Electronics Connectivity, Consumer IOT, Industrial IOT, Mobile, Voice & Music, and Wired Infrastructure and Networking platforms.
The technical implementation of this vulnerability stems from inadequate input validation within the wlan frame parsing routine. When processing incoming wireless frames, the system fails to verify that the frame body length matches expected parameters before attempting to read data from memory locations. This lack of boundary checking creates a scenario where maliciously crafted wlan frames can cause the parser to read beyond allocated memory boundaries, potentially exposing sensitive data or causing system instability. The vulnerability is particularly concerning as it operates at a low level within the network stack processing, making detection and exploitation relatively straightforward for attackers with network access. This flaw aligns with CWE-129 Input Validation and CWE-787 Out-of-bounds Write/Read patterns, representing a classic buffer overflow condition that can be leveraged for information disclosure or system compromise.
The operational impact of this vulnerability extends across multiple deployment scenarios within the automotive and IoT ecosystems where Snapdragon chipsets are prevalent. In automotive applications, this vulnerability could potentially affect vehicle connectivity systems, infotainment networks, and telematics platforms, creating risks for data interception or system disruption. The vulnerability's presence in both consumer and industrial IoT deployments means that connected devices across various sectors could be compromised, potentially exposing sensitive operational data or enabling denial of service conditions. Attackers could exploit this weakness by crafting specially formatted wlan frames that trigger the out-of-bounds read condition, potentially leading to memory corruption, system crashes, or even privilege escalation depending on the execution environment. This vulnerability directly maps to attack techniques described in the MITRE ATT&CK framework under T1059 Command and Scripting Interpreter and T1068 Exploitation for Privilege Escalation.
Mitigation strategies for this vulnerability require immediate firmware and software updates from device manufacturers to patch the frame parsing routines with proper length validation. Organizations should implement network segmentation and monitoring to detect anomalous wlan frame patterns that could indicate exploitation attempts. System administrators should consider disabling unnecessary wlan functionality on affected devices until patches are applied, and implement intrusion detection systems to monitor for suspicious network traffic patterns. The vulnerability highlights the importance of proper input validation in embedded systems and the need for comprehensive security testing of network protocol implementations. Device manufacturers must ensure that all network parsing routines include robust boundary checking and length validation to prevent similar issues in future deployments, particularly in safety-critical automotive applications where such vulnerabilities could pose significant risks to vehicle operation and passenger safety.