CVE-2019-2302 in Snapdragon Auto
Summary
by MITRE
While processing vendor command which contains corrupted channel count, an integer overflow occurs and finally will lead to heap overflow. in Snapdragon Auto, Snapdragon Consumer Electronics Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wearables in APQ8017, APQ8053, APQ8096AU, MDM9206, MDM9207C, MDM9607, MDM9640, MDM9650, MSM8905, MSM8909, MSM8909W, MSM8976, MSM8996AU, QCA6174A, QCA6574AU, QCA9377, QCA9379, QCN7605, QCS405, QCS605, SDA845, SDM636, SDM660, SDM670, SDM710, SDM845, SDX20, SDX24, SM6150, SM8150
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Analysis
by VulDB Data Team • 02/05/2024
This vulnerability represents a critical integer overflow condition that can lead to heap corruption within Qualcomm's Snapdragon chipset family, affecting a wide range of automotive, consumer electronics, and IoT devices. The flaw manifests when processing vendor commands containing corrupted channel count values, where the system fails to properly validate input parameters before performing arithmetic operations. The integer overflow occurs during the channel count processing phase, ultimately resulting in a heap overflow that can compromise the integrity of the system's memory management. This vulnerability impacts multiple generations of Qualcomm's mobile, automotive, and IoT processors including the APQ8017, APQ8053, APQ8096AU, MDM9206, MDM9207C, MDM9607, MDM9640, MDM9650, MSM8905, MSM8909, MSM8909W, MSM8976, MSM8996AU, QCA6174A, QCA6574AU, QCA9377, QCA9379, QCN7605, QCS405, QCS605, SDA845, SDM636, SDM660, SDM670, SDM710, SDM845, SDX20, SDX24, SM6150, and SM8150 chipsets.
The technical exploitation of this vulnerability follows a well-defined attack pattern that aligns with CWE-190, which specifically addresses integer overflow conditions. The flaw occurs in the command processing subsystem where vendor-specific commands are handled, and the system's failure to validate channel count inputs creates an opportunity for attackers to manipulate memory layout through controlled integer arithmetic. When the corrupted channel count value is processed, it triggers an arithmetic overflow that propagates through the memory management system, eventually leading to heap corruption. This heap overflow condition provides attackers with potential means to execute arbitrary code or cause system instability, making it particularly dangerous in embedded systems where memory corruption can lead to complete system compromise.
The operational impact of this vulnerability extends across multiple device categories including automotive systems, mobile devices, consumer electronics, and industrial IoT deployments. Attackers could potentially exploit this condition to gain unauthorized access to sensitive data, disrupt device functionality, or execute malicious code within the affected systems. The widespread deployment of these Qualcomm chipsets across various industries means that the potential attack surface is extensive, affecting everything from smartphones and tablets to automotive infotainment systems and industrial control devices. The vulnerability's presence in both mobile and automotive processors raises particular concerns given the safety-critical nature of many automotive applications where such memory corruption could lead to dangerous system failures.
Mitigation strategies for this vulnerability require comprehensive firmware updates from device manufacturers, as the issue resides within the hardware-level processing capabilities of the Qualcomm chipsets. Organizations should implement immediate firmware patching procedures across all affected devices, particularly those in automotive and industrial environments where the risk of exploitation is highest. Network segmentation and monitoring should be enhanced to detect potential exploitation attempts, while security teams should closely monitor for any reported incidents or attack patterns targeting this specific vulnerability. The mitigation approach should also include implementing runtime protection mechanisms that can detect and prevent integer overflow conditions, leveraging techniques such as stack canaries, address space layout randomization, and heap metadata validation to reduce the attack surface. Given the complexity of the underlying hardware architecture, the remediation process requires careful coordination between chipset vendors, device manufacturers, and end users to ensure complete protection across the entire ecosystem.