CVE-2019-14083 in Snapdragon Auto
Summary
by MITRE
While parsing Service Descriptor Extended Attribute received as part of SDF frame, there is a possibility that incorrect length is specified in the attribute length field of extended SSI which can lead to integer underflow in Snapdragon Auto, Snapdragon Compute, Snapdragon Connectivity, Snapdragon Consumer Electronics Connectivity, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon IoT, Snapdragon Mobile, Snapdragon Voice & Music, Snapdragon Wired Infrastructure and Networking in APQ8009, APQ8053, APQ8096, APQ8098, IPQ6018, IPQ8074, MSM8996AU, MSM8998, Nicobar, QCA6174A, QCA6390, QCA6574AU, QCA8081, QCA9377, QCA9379, QCN7605, QCS404, QCS405, QCS605, Rennell, SC8180X, SDA660, SDA845, SDM630, SDM636, SDM660, SDM670, SDM710, SDM845, SDM850, SDX20, SDX24, SM6150, SM7150, SM8150, SXR1130, SXR2130
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Analysis
by VulDB Data Team • 03/06/2020
This vulnerability involves a critical integer underflow condition that occurs during the parsing of Service Descriptor Extended Attribute within SDF (Service Discovery Framework) frames. The flaw manifests when the attribute length field in the extended SSI (Service Specific Information) contains an incorrect value that, when processed, results in an underflow condition. This type of vulnerability falls under the category of integer underflow as classified by CWE-191, which specifically addresses unsigned integer underflows that can lead to unexpected behavior and potential exploitation. The vulnerability affects a wide range of Qualcomm Snapdragon chipsets across multiple product categories including automotive, mobile, connectivity, and industrial IoT platforms.
The technical implementation of this vulnerability stems from improper validation of attribute length fields during SDF frame processing. When the system attempts to parse the extended attribute data structure, it uses the specified length field to determine memory allocation or buffer boundaries. An incorrect length value that underflows during arithmetic operations can cause the system to process memory regions incorrectly, potentially leading to buffer overflows, memory corruption, or arbitrary code execution. This processing occurs within the Snapdragon chipset's network stack or service discovery components, which are critical for device connectivity and communication functions.
The operational impact of this vulnerability spans across multiple Snapdragon product lines including automotive platforms like the APQ8009 and automotive processors such as the SC8180X, as well as mobile processors like the SDM845 and SDM850. Devices utilizing these chipsets could be vulnerable to remote code execution attacks if an attacker can craft malicious SDF frames with malformed attribute length fields. The vulnerability affects both wired and wireless connectivity components, making it particularly dangerous in environments where devices must process network traffic from untrusted sources. This includes automotive infotainment systems, industrial IoT devices, and mobile devices that rely on Snapdragon's connectivity solutions for various network services.
Mitigation strategies for this vulnerability should focus on implementing robust input validation mechanisms within the SDF frame parsing routines. System designers must ensure that attribute length fields are properly validated before any arithmetic operations are performed, including checking for negative results that would indicate underflow conditions. The implementation should include bounds checking and defensive programming practices to prevent integer underflow scenarios. Organizations should also consider firmware updates from Qualcomm that address this specific vulnerability, as well as network segmentation and traffic filtering to limit exposure to potentially malicious SDF frames. This vulnerability aligns with ATT&CK technique T1059 for execution through command injection and T1203 for exploitation of software vulnerabilities, making it particularly relevant for defensive security operations and threat hunting activities within enterprise environments.