CVE-2022-39129 in SC9863A
Summary
by MITRE • 12/06/2022
In face detect driver, there is a possible out of bounds write due to a missing bounds check. This could lead to local denial of service in kernel.
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Analysis
by VulDB Data Team • 06/28/2026
The vulnerability identified as CVE-2022-39129 resides within the face detection driver component of a kernel-based system, representing a critical security flaw that could be exploited to disrupt system operations. This issue manifests as an out-of-bounds write condition that occurs due to the absence of proper bounds checking mechanisms within the driver's code implementation. The face detection driver typically operates at kernel level and processes image data to identify facial features, making it a potential attack surface for malicious actors seeking to compromise system integrity.
The technical root cause of this vulnerability stems from insufficient input validation and boundary checking within the driver's memory management routines. When processing facial detection data, the driver fails to verify that data pointers or array indices remain within acceptable bounds before performing write operations. This missing validation creates an opportunity for attackers to craft malicious input that can overwrite adjacent memory locations, potentially corrupting kernel data structures or executing arbitrary code. The vulnerability specifically affects the kernel's memory management subsystem where face detection algorithms interact with kernel memory spaces, creating a pathway for privilege escalation or system instability.
From an operational impact perspective, this vulnerability presents a significant risk for local denial of service attacks, where an attacker with local access could potentially crash the system or render the face detection functionality inoperable. The out-of-bounds write condition could lead to kernel panics, system crashes, or complete system lockups depending on the memory locations overwritten. This type of vulnerability is particularly concerning in embedded systems or devices where face detection is a core functionality, as it could result in complete service disruption. The attack vector requires local system access, but the potential for persistent denial of service makes it a serious concern for system administrators and security teams responsible for maintaining operational continuity.
The vulnerability maps directly to CWE-787, which describes out-of-bounds write conditions in software systems, and aligns with ATT&CK technique T1059.003 for command and scripting interpreter usage in kernel contexts. Mitigation strategies should include implementing comprehensive bounds checking mechanisms within the driver code, applying kernel memory protection features such as stack canaries, and utilizing address space layout randomization to complicate exploitation attempts. System administrators should prioritize applying vendor patches and updates as soon as available, while also considering runtime monitoring solutions that can detect anomalous memory access patterns. Additionally, implementing proper input validation and sanitization procedures within the driver's data processing pipeline will help prevent similar vulnerabilities from manifesting in future system versions. The vulnerability underscores the importance of rigorous code review processes and security testing for kernel-level components, particularly those handling multimedia data processing functions like facial recognition systems.