CVE-2016-10480 in Android
Summary
by MITRE
In Android before 2018-04-05 or earlier security patch level on Qualcomm Snapdragon Mobile and Snapdragon Wear MDM9206, MDM9607, MDM9650, MSM8909W, SD 210/SD 212/SD 205, SD 400, SD 410/12, SD 425, SD 430, SD 450, SD 615/16/SD 415, SD 617, SD 625, SD 650/52, SD 800, SD 808, SD 810, SD 820, SD 835, and SDX20, possible memory corruption due to invalid integer overflow checks in exif parsing.
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Analysis
by VulDB Data Team • 01/27/2020
The vulnerability identified as CVE-2016-10480 represents a critical memory corruption flaw affecting Android devices equipped with Qualcomm Snapdragon mobile processors. This issue stems from inadequate integer overflow validation during exif metadata parsing operations, creating a pathway for malicious actors to exploit memory handling mechanisms within the device's image processing subsystem. The vulnerability specifically impacts devices utilizing Qualcomm Snapdragon chipsets including the MDM9206, MDM9607, MDM9650, MSM8909W, and numerous SD series processors spanning from entry-level to high-end mobile platforms.
The technical flaw manifests when the Android system processes exif metadata embedded within image files, particularly those containing malformed or crafted metadata structures. During this parsing operation, the system fails to properly validate integer values that control memory allocation and buffer boundaries, leading to potential integer overflow conditions. When these overflow scenarios occur, they can result in memory corruption that allows attackers to manipulate heap memory structures, potentially enabling arbitrary code execution within the context of the image processing service. This vulnerability falls under the CWE-190 category of integer overflow and under CWE-129 for improper validation of array indices, representing a classic example of how metadata parsing can become a vector for memory corruption attacks.
The operational impact of this vulnerability extends across a broad spectrum of Android devices, affecting millions of users through various smartphone and wearable platforms. Attackers could exploit this weakness by crafting malicious image files containing specially formatted exif metadata that triggers the integer overflow during processing. Once triggered, the memory corruption could allow for privilege escalation, enabling malicious actors to execute arbitrary code with elevated privileges or potentially gain unauthorized access to sensitive device data. The vulnerability's presence in both mobile and wearable platforms creates additional attack surface considerations, particularly given the increasing integration of wearable devices in enterprise and consumer environments where they may contain sensitive information or serve as entry points to broader network infrastructures.
Organizations and device manufacturers should prioritize immediate deployment of security patches addressing this vulnerability, particularly for devices running Android versions prior to the 2018-04-05 security update. The remediation approach should focus on implementing proper integer overflow checks within the exif parsing libraries, ensuring that all buffer allocation calculations properly validate input parameters before execution. Additionally, implementing sandboxing mechanisms for image processing operations and strengthening input validation protocols for metadata handling can provide additional defense layers against similar exploitation vectors. Security teams should monitor for potential exploitation attempts targeting this vulnerability and consider implementing network-based intrusion detection systems to identify malicious image file delivery attempts. The ATT&CK framework categorizes this vulnerability under the T1068 technique of exploit for privilege escalation, while the use of crafted metadata for memory corruption aligns with T1059 for command and scripting interpreter techniques. Device manufacturers should also consider implementing runtime protections and memory corruption detection mechanisms to provide additional resilience against exploitation attempts targeting similar integer overflow vulnerabilities in image processing components.