CVE-2026-22163 in Graphics DDK
Summary
by MITRE • 03/21/2026
Requires malware code to misuse the DDK kernel module IOCTL interface.
Such code can use the interface in an unsupported way that allows subversion of the GPU to perform writes to arbitrary physical memory pages.
The product utilises a shared resource in a concurrent manner but does not attempt to synchronise access to the resource.
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Analysis
by VulDB Data Team • 03/27/2026
CVE-2026-22163 represents a critical kernel-level vulnerability that exploits improper synchronization mechanisms within a device driver kernel module interface. This vulnerability specifically targets the DDK (Driver Development Kit) kernel module's IOCTL (Input/Output Control) interface, which serves as a communication pathway between user-mode applications and kernel-mode drivers. The flaw enables malicious code to manipulate the GPU subsystem through unsupported interface usage patterns that bypass normal access controls and memory protection mechanisms.
The technical exploitation of this vulnerability stems from the absence of proper concurrency control mechanisms within the kernel module's shared resource management. When multiple threads or processes attempt to access the same GPU memory resource simultaneously, the lack of synchronization primitives such as mutexes, semaphores, or atomic operations creates a race condition scenario. This race condition allows an attacker to orchestrate a sequence of IOCTL calls that manipulate the GPU's memory management unit in ways that were never intended by the original design. The vulnerability specifically enables arbitrary physical memory page writes through GPU subsystem manipulation, which represents a fundamental breach of memory isolation principles that are core to operating system security models.
The operational impact of this vulnerability extends beyond simple privilege escalation to encompass complete system compromise through GPU-based memory manipulation. Attackers can leverage this flaw to write to any physical memory location, potentially allowing them to modify kernel code, inject malicious payloads into protected memory regions, or manipulate system-critical data structures. This capability aligns with attack patterns described in the MITRE ATT&CK framework under the T1059 (Command and Scripting Interpreter) and T1068 (Local Port Forwarding) techniques, as the compromised GPU can serve as a pivot point for further exploitation. The vulnerability's classification as a concurrency flaw places it within CWE-362 (Concurrent Execution using Shared Resource with Improper Synchronization) category, which specifically addresses issues where shared resources are accessed without proper synchronization mechanisms.
The security implications of this vulnerability are particularly severe because it operates at the kernel level and leverages GPU hardware acceleration capabilities that are often overlooked in traditional security assessments. GPU memory manipulation through this interface can bypass standard memory protection mechanisms such as kernel address space layout randomization (KASLR) and control flow integrity (CFI) checks. The vulnerability essentially provides a backdoor pathway that allows attackers to subvert normal GPU memory management protocols, potentially enabling them to perform operations such as kernel code patching, rootkit deployment, or complete system state manipulation. Organizations should consider implementing additional security controls including kernel module signing verification, GPU memory access monitoring, and comprehensive runtime protection systems that can detect anomalous GPU memory access patterns. The lack of proper synchronization in the DDK kernel module interface represents a fundamental design flaw that requires immediate remediation through proper concurrency control implementation and thorough security code reviews of all shared resource access patterns within kernel drivers.
This vulnerability demonstrates the critical importance of proper resource synchronization in kernel-level code and highlights how seemingly minor oversights in concurrency control can lead to catastrophic security implications. The ability to perform arbitrary physical memory writes through GPU subsystem manipulation represents a sophisticated attack vector that can bypass traditional security boundaries and provides attackers with unprecedented control over system memory management. The remediation approach should focus on implementing robust synchronization mechanisms, conducting thorough code reviews for similar concurrency issues, and establishing comprehensive monitoring systems that can detect and prevent unauthorized GPU memory access patterns.