CVE-2018-11937 in Snapdragon Auto
Summary
by MITRE
Lack of input validation before copying can lead to a buffer over read in WLAN function in Snapdragon Auto, Snapdragon Compute, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile in MDM9150, MDM9206, MDM9607, MDM9640, MDM9650, MSM8996AU, QCA6574AU, QCS605, SD 425, SD 427, SD 430, SD 435, SD 450, SD 625, SD 636, SD 675, SD 712 / SD 710 / SD 670, SD 820A, SD 835, SD 845 / SD 850, SD 855, SDA660, SDM630, SDM660, SDX20, SDX24, SM7150
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Analysis
by VulDB Data Team • 06/15/2020
The vulnerability identified as CVE-2018-11937 represents a critical buffer overread condition affecting multiple Qualcomm Snapdragon chipsets used in automotive, mobile, and IoT devices. This flaw exists within the WLAN function of affected processors and stems from insufficient input validation during data copying operations. The vulnerability impacts a wide range of Snapdragon automotive platforms including the MDM9150, MDM9206, and MDM9607 modems, alongside consumer IoT devices such as the SD 425, SD 427, and SD 845 processors. The flaw falls under CWE-125, which specifically addresses out-of-bounds read conditions, making it a classic example of memory safety vulnerabilities that can lead to information disclosure or system instability.
The technical implementation of this vulnerability occurs when the WLAN subsystem receives malformed input data without proper validation before copying it into fixed-size buffers. This allows an attacker to potentially read memory contents beyond the intended buffer boundaries, potentially exposing sensitive information such as cryptographic keys, authentication credentials, or system memory contents. The affected Snapdragon platforms span across multiple generations and use cases, from automotive infotainment systems to mobile devices, creating a broad attack surface that spans the automotive, consumer electronics, and industrial IoT sectors. The vulnerability's presence in both automotive and mobile chipsets indicates that it could be exploited in various threat scenarios, from targeted attacks on connected vehicles to broader network infiltration attempts.
The operational impact of this vulnerability extends beyond simple information disclosure, as it could enable attackers to gain insights into system memory structures and potentially escalate privileges. The widespread deployment of affected chipsets means that numerous vehicles, mobile devices, and IoT systems could be vulnerable to exploitation. According to ATT&CK framework, this vulnerability could be leveraged for initial access through network-based attacks, followed by privilege escalation or information gathering phases. The exploitation of such a flaw in automotive systems could pose serious safety risks, as it might allow unauthorized access to vehicle communication systems or sensitive data. The vulnerability affects both legacy and newer chipsets, indicating that organizations need to consider comprehensive patching strategies across their entire fleet of devices.
Mitigation strategies for this vulnerability require immediate firmware updates from device manufacturers, as Qualcomm has released patches addressing the buffer overread condition. Network administrators should implement monitoring solutions to detect anomalous WLAN traffic patterns that might indicate exploitation attempts. The vulnerability demonstrates the importance of input validation in embedded systems and highlights the need for robust memory safety practices in automotive and IoT environments. Organizations should also consider implementing network segmentation and access controls to limit potential attack surfaces, particularly in automotive applications where security is paramount. This vulnerability underscores the critical nature of embedded security in connected vehicles and IoT devices, where a single memory safety flaw can compromise entire systems.