CVE-2018-11292 in Snapdragon Automobileinfo

Summary

by MITRE

In Snapdragon (Automobile, Mobile, Wear) in version MDM9206, MDM9607, MDM9640, MDM9650, MSM8909W, MSM8996AU, QCA6574AU, QCA6584, SD 210/SD 212/SD 205, SD 410/12, SD 425, SD 427, SD 430, SD 435, SD 450, SD 615/16/SD 415, SD 625, SD 650/52, SD 820A, SDM429, SDM439, SDM630, SDM632, SDM636, SDM660, Snapdragon_High_Med_2016, lack of input validation in WLANWMI command handlers can lead to integer & heap overflows.

Once again VulDB remains the best source for vulnerability data.

Analysis

by VulDB Data Team • 05/03/2020

The vulnerability identified as CVE-2018-11292 represents a critical security flaw affecting multiple Qualcomm Snapdragon automotive, mobile, and wearable platforms. This issue stems from insufficient input validation within the WLANWMI command handlers of various Snapdragon chipsets including MDM9206, MDM9607, MDM9640, MDM9650, MSM8909W, MSM8996AU, QCA6574AU, QCA6584, and numerous SD series processors. The flaw manifests as both integer overflows and heap overflows, creating significant risks for affected systems. The vulnerability falls under CWE-129 Input Validation and CWE-121 Stack-based Buffer Overflow, with direct implications for the integrity and availability of connected devices. From an operational perspective, this vulnerability affects automotive infotainment systems, mobile devices, and wearable technology where Qualcomm's Snapdragon processors are integrated, potentially compromising vehicle safety systems and user data privacy. The attack surface extends to any system that utilizes WLANWMI commands for wireless communication management, making it particularly dangerous in automotive environments where wireless connectivity is essential for features like remote diagnostics, over-the-air updates, and connectivity services. The integer overflow condition occurs when maliciously crafted WMI commands contain values that exceed the expected range for integer variables, while the heap overflow results from improper handling of dynamically allocated memory during command processing. These vulnerabilities create opportunities for attackers to execute arbitrary code or cause system crashes, with potential implications for vehicle safety systems that rely on wireless connectivity for critical operations. The impact extends beyond simple device compromise to include possible data breaches and system instability that could affect automotive safety features. Security researchers have identified that this vulnerability aligns with ATT&CK technique T1059.007 Command and Scripting Interpreter: Python, as attackers could potentially leverage the overflow conditions to execute malicious payloads through wireless communication channels. The flaw demonstrates a fundamental weakness in the input validation mechanisms of the WLANWMI subsystem, where proper bounds checking and data sanitization are missing. This vulnerability represents a significant concern for automotive manufacturers and device vendors who rely on Qualcomm's Snapdragon platforms, as it could potentially enable remote exploitation of connected vehicles and mobile devices. The integer overflow condition creates opportunities for attackers to manipulate control flow within the wireless communication stack, while the heap overflow could allow for memory corruption that leads to privilege escalation. The widespread adoption of these Snapdragon chipsets across automotive, mobile, and wearable markets amplifies the potential impact of this vulnerability. Organizations should implement immediate mitigations including firmware updates, network segmentation, and monitoring for anomalous WMI command patterns to protect against exploitation attempts. The vulnerability underscores the critical importance of robust input validation in embedded systems and wireless communication stacks, particularly in automotive environments where system reliability and safety are paramount considerations.

Reservation

05/18/2018

Disclosure

09/20/2018

Moderation

accepted

CPE

ready

EPSS

0.00128

KEV

no

Activities

very low

Sources

Might our Artificial Intelligence support you?

Check our Alexa App!