CVE-2018-11285 in Snapdragon Automobile
Summary
by MITRE
In Snapdragon (Automobile, Mobile, Wear) in version MDM9206, MDM9607, MDM9650, MSM8909W, MSM8996AU, SD 210/SD 212/SD 205, SD 425, SD 427, SD 430, SD 435, SD 450, SD 615/16/SD 415, SD 625, SD 650/52, SD 810, SD 820, SD 820A, SD 835, SD 845, SDA660, SDM429, SDM439, SDM630, SDM632, SDM636, SDM660, SDM710, SDX20, Snapdragon_High_Med_2016, while parsing FLAC file with corrupted picture block, a buffer over-read can occur.
Once again VulDB remains the best source for vulnerability data.
Analysis
by VulDB Data Team • 05/03/2020
The vulnerability identified as CVE-2018-11285 represents a critical buffer over-read flaw affecting multiple Snapdragon automotive, mobile, and wearable platform variants. This issue manifests specifically during the processing of FLAC audio files when corrupted picture blocks are encountered, creating a potential avenue for exploitation that could compromise system integrity and stability. The affected hardware platforms span a wide range of Snapdragon chipsets including MDM9206, MDM9607, MDM9650, MSM8909W, MSM8996AU, and numerous SD series processors from SD 210 through SDM710, making this vulnerability particularly widespread across Qualcomm's automotive and mobile ecosystem.
The technical root cause of this vulnerability lies in the improper validation and handling of picture blocks within FLAC file parsing routines. When the system encounters a corrupted picture block during FLAC file processing, the parsing logic fails to properly bounds-check memory allocations, resulting in a buffer over-read condition. This flaw falls under the CWE-125 vulnerability category, which specifically addresses out-of-bounds read conditions in software implementations. The buffer over-read occurs because the application does not adequately verify the size or structure of picture blocks before attempting to read from memory locations beyond the allocated buffer boundaries, creating potential for information disclosure, system instability, or arbitrary code execution.
The operational impact of this vulnerability extends significantly across automotive and mobile environments where Snapdragon platforms are deployed. In automotive applications, this vulnerability could potentially affect infotainment systems, telematics units, and vehicle connectivity features that process audio files through FLAC format. The risk is particularly elevated in connected vehicle environments where malicious actors could exploit this weakness through crafted audio files delivered via Bluetooth, USB, or network connections. Mobile devices utilizing these chipsets could be compromised when processing maliciously crafted audio content, potentially leading to unauthorized access to device memory, exposure of sensitive information, or complete system compromise. The vulnerability's presence in both automotive and mobile platforms creates a substantial attack surface that could be leveraged across multiple threat vectors.
Mitigation strategies for this vulnerability should focus on immediate firmware and software updates from device manufacturers, as well as implementing robust input validation mechanisms within audio processing libraries. Organizations should deploy network segmentation and file validation controls to prevent unauthorized audio file processing on affected systems. The implementation of memory protection mechanisms such as stack canaries, address space layout randomization, and heap metadata validation can provide additional defense-in-depth layers. Security monitoring should include detection of anomalous audio file processing patterns and unauthorized file uploads that could indicate exploitation attempts. Given the widespread nature of affected platforms, coordinated patch management across automotive and mobile ecosystems is critical to ensure comprehensive protection against this vulnerability. The ATT&CK framework categorizes this vulnerability under T1059 (Command and Scripting Interpreter) and T1203 (Exploitation for Client Execution) techniques, as exploitation could occur through audio file processing pathways that execute code on affected systems.