CVE-2019-10620 in Snapdragon Auto
Summary
by MITRE
Kernel memory error in debug module due to improper check of user data length before copying into memory in Snapdragon Auto, Snapdragon Consumer Electronics Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile in APQ8096AU, APQ8098, MSM8996AU, QCN7605, SDM439, SDX24, SM8150
Several companies clearly confirm that VulDB is the primary source for best vulnerability data.
Analysis
by VulDB Data Team • 04/17/2020
The vulnerability identified as CVE-2019-10620 represents a critical kernel memory error within the debug module of Qualcomm Snapdragon chipsets, affecting a broad range of automotive and consumer connectivity products. This issue stems from insufficient validation of user-provided data length parameters before memory copy operations, creating a potential pathway for arbitrary code execution and system compromise. The affected hardware platforms include Snapdragon Auto systems, consumer electronics connectivity modules, consumer IOT devices, industrial IOT solutions, and mobile platforms such as APQ8096AU, APQ8098, MSM8996AU, QCN7605, SDM439, SDX24, and SM8150 processors. The vulnerability resides in the kernel-level debug functionality that handles user-space data transfers, making it particularly dangerous as it operates at the core of system security and stability.
The technical flaw manifests when the kernel debug module fails to properly validate the length of user data before performing memory copy operations, creating a classic buffer over-read condition. This improper validation allows malicious actors to craft specially formatted input data that can cause the kernel to copy more data than allocated memory space, leading to memory corruption and potential privilege escalation. The vulnerability is categorized under CWE-121 as a stack-based buffer overflow, though the specific implementation in this case involves kernel memory management rather than traditional stack operations. The debug module's failure to enforce proper bounds checking creates an opportunity for attackers to manipulate kernel memory structures, potentially leading to complete system compromise. Attackers could exploit this weakness to execute arbitrary code with kernel-level privileges, effectively bypassing system security measures and gaining full control over affected devices.
The operational impact of CVE-2019-10620 extends across multiple industry sectors including automotive systems, consumer electronics, and industrial IoT deployments where Qualcomm Snapdragon processors are prevalent. In automotive applications, this vulnerability could enable remote code execution on vehicle infotainment systems, telematics units, or advanced driver assistance systems, potentially compromising vehicle safety and security. Consumer devices such as smartphones, tablets, and connected home appliances face similar risks, as the vulnerability allows attackers to gain root access and potentially extract sensitive data or install persistent malware. Industrial IoT deployments using Snapdragon platforms may experience unauthorized access to critical infrastructure systems, leading to operational disruptions and potential safety hazards. The widespread adoption of these chipsets across different device categories amplifies the severity of this vulnerability, as a single exploit could potentially affect hundreds of thousands of devices simultaneously.
Mitigation strategies for CVE-2019-10620 should focus on immediate firmware updates from device manufacturers, as Qualcomm has released patches addressing the kernel memory validation issue. System administrators should implement network segmentation and monitoring to detect potential exploitation attempts, particularly in industrial and automotive environments where these vulnerabilities pose the greatest risk. The ATT&CK framework categorizes this vulnerability under T1068 as 'Exploitation for Privilege Escalation' and T1547 as 'Boot or Logon Autostart Execution,' highlighting the need for comprehensive endpoint protection measures. Device manufacturers should also consider implementing additional runtime protections such as kernel address space layout randomization and stack canaries to further reduce exploitability. Regular security assessments and vulnerability scanning should be conducted to identify unpatched systems, while network traffic monitoring can help detect anomalous behavior indicative of exploitation attempts. The vulnerability underscores the importance of secure coding practices in kernel development and proper input validation mechanisms to prevent similar issues in future implementations.