CVE-2022-25711 in Snapdragon Auto
Summary
by MITRE • 12/13/2022
Memory corruption in camera due to improper validation of array index in Snapdragon Auto, Snapdragon Compute, Snapdragon Consumer IOT, Snapdragon Industrial IOT, Snapdragon Mobile, Snapdragon Wearables
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Analysis
by VulDB Data Team • 05/07/2026
This vulnerability represents a critical memory corruption issue affecting multiple Snapdragon product lines including automotive, mobile, and IoT devices. The flaw stems from inadequate validation of array indices within the camera subsystem, creating potential pathways for arbitrary code execution and system instability. The vulnerability manifests when the camera driver processes array access operations without proper bounds checking, allowing attackers to manipulate memory layout through crafted input sequences. This memory corruption vulnerability directly maps to CWE-129, which addresses insufficient validation of array index values, and specifically relates to CWE-787, which covers out-of-bounds write operations. The impact extends across various Snapdragon product categories including automotive systems, mobile devices, and industrial IoT deployments, indicating a widespread attack surface that could affect millions of devices globally.
The technical implementation of this vulnerability involves array index validation failures within camera processing pipelines where input parameters control array access operations. When legitimate camera operations receive malformed or unexpected indices, the system fails to validate these values against predefined array boundaries, leading to memory corruption that can be exploited to execute arbitrary code. Attackers can leverage this weakness by crafting specific camera input sequences that cause the system to access memory locations outside the intended array boundaries. The exploitation requires understanding of the camera driver internals and memory layout patterns, making it a sophisticated target for advanced persistent threats. This vulnerability aligns with ATT&CK technique T1059.007 for command and scripting interpreter, as successful exploitation could enable attackers to execute malicious code through compromised camera subsystems. The nature of the flaw suggests it could be triggered through various attack vectors including camera input processing, image manipulation, or even network-based camera commands that flow through the affected Snapdragon processors.
The operational impact of this vulnerability spans multiple security domains including device integrity, data confidentiality, and system availability. In automotive applications, compromised camera systems could lead to unauthorized access to vehicle security features, potentially enabling remote vehicle control or data exfiltration from critical automotive systems. Mobile device users face risks of unauthorized access to camera functionality, which could lead to privacy violations, data breaches, or device compromise through privilege escalation. Industrial IoT deployments become vulnerable to supply chain attacks where adversaries could exploit this weakness to gain persistent access to critical infrastructure monitoring systems. The vulnerability's presence across multiple Snapdragon product lines creates cascading security implications, as a single exploitation vector could affect diverse device categories from smartphones to industrial sensors. Organizations deploying affected devices must consider the potential for lateral movement within networks where compromised camera subsystems could serve as entry points for broader attacks, particularly in environments where camera systems interface with other critical components.
Mitigation strategies should focus on immediate firmware updates from device manufacturers and comprehensive security assessments of affected systems. The primary defense involves implementing proper array bounds checking mechanisms within camera driver code, ensuring that all array access operations validate indices against predetermined boundaries before memory access occurs. System administrators should conduct thorough inventory assessments to identify all affected Snapdragon-based devices and prioritize remediation efforts based on risk exposure levels. Network segmentation and access controls should be implemented to limit potential attack surface areas where camera subsystems interface with other network components. Organizations should also consider implementing runtime monitoring solutions that can detect anomalous array access patterns or memory corruption indicators that might signal exploitation attempts. The vulnerability's classification as a memory corruption issue necessitates regular security testing including fuzzing of camera input processing functions to identify potential additional weaknesses. Device manufacturers must enhance their secure coding practices and conduct thorough code reviews focusing on array validation mechanisms, particularly in subsystems handling user input or external data streams. Compliance with security standards such as ISO 27001 and NIST cybersecurity frameworks should include specific controls addressing array bounds checking and memory safety in embedded systems.