CVE-2026-47574 in Virtual GPU Manager
Summary
by MITRE • 09/30/2026
NVIDIA vGPU Virtual GPU Manager for Linux contains a vulnerability where an attacker could cause incorrect resource transfer between spheres. A successful exploit of this vulnerability might lead to code execution, denial of service, escalation of privileges, information disclosure, and data tampering.
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Analysis
by VulDB Data Team • 09/30/2026
The NVIDIA vGPU Virtual GPU Manager for Linux represents a critical component in virtualized graphics environments, facilitating the allocation and management of graphical processing resources across multiple virtual machines or containers. This software acts as an intermediary between the host operating system's kernel-level drivers and the guest virtual machine instances, ensuring that computational tasks are distributed efficiently while maintaining isolation boundaries between different execution contexts known as spheres. These spheres typically represent distinct security domains or user spaces within the hypervisor environment, where strict separation is required to prevent unauthorized access or interference between tenants. The integrity of this resource transfer mechanism is paramount for both performance optimization and security enforcement in multi-tenant cloud infrastructure and enterprise virtual desktop deployments.
A significant vulnerability has been identified within this management layer, specifically concerning the logic governing how resources are transferred between these isolated spheres. The flaw stems from an incorrect implementation or validation process during the handoff of GPU compute contexts, memory buffers, or execution states. Instead of strictly enforcing boundary checks and permission validations before allowing a sphere to access or modify another's allocated resources, the system permits operations that bypass intended restrictions. This breakdown in isolation logic allows an attacker who has gained initial foothold within one virtual environment to manipulate the resource transfer mechanisms, effectively blurring the lines between separate security domains. The root cause likely involves insufficient input validation or race conditions during context switching, which are common pitfalls in complex systems managing hardware abstraction layers under high concurrency.
The operational impact of exploiting this vulnerability is severe and multifaceted, posing substantial risks to system integrity and availability. An attacker could leverage the incorrect resource transfer to achieve arbitrary code execution within the host kernel space or other guest environments, effectively breaking out of their sandboxed container or virtual machine. This capability facilitates privilege escalation, allowing low-privileged users to gain administrative control over the underlying infrastructure. Furthermore, the vulnerability can be weaponized for denial of service attacks by corrupting GPU state information, leading to system crashes or unresponsive graphical services that disrupt business operations. Information disclosure is also a critical concern, as improper resource handling may expose sensitive data stored in video memory or shared buffers belonging to other tenants. Additionally, attackers could tamper with computational results or application states, compromising the integrity of scientific simulations, financial modeling, or creative rendering processes dependent on accurate GPU output.
From a classification perspective, this vulnerability aligns closely with CWE-284 Improper Access Control and CWE-755 Incorrect Error Handling, as it involves bypassing security boundaries through flawed logic in resource management. In the context of the MITRE ATT&CK framework, such an exploit maps to T1068 Exploitation for Privilege Escalation and potentially T1213 Data from Information Repositories if used for data exfiltration across spheres. The attack vector typically requires local access or network-accessible entry points depending on how the vGPU manager is exposed, making it particularly dangerous in public cloud environments where multi-tenancy is standard practice. Defense-in-depth strategies are essential to mitigate these risks, as no single control can fully address complex hypervisor-level flaws.
To mitigate this vulnerability and reduce the attack surface associated with NVIDIA vGPU management, organizations must prioritize immediate patching of the affected Virtual GPU Manager software versions provided by NVIDIA. Regular updates ensure that known logic errors in resource transfer mechanisms are corrected through vendor-released patches. Beyond patching, administrators should enforce strict least-privilege principles for all users and services interacting with the vGPU infrastructure, ensuring that no single tenant has excessive permissions over shared resources. Network segmentation plays a crucial role by isolating management interfaces from general user traffic, limiting an attacker's ability to reach the vulnerable components remotely. Additionally, enabling comprehensive logging and monitoring of GPU resource allocation events can help detect anomalous behavior indicative of exploitation attempts in real-time. Implementing hardware-assisted isolation features where available further strengthens the boundary between spheres, providing a robust defense against privilege escalation and cross-domain data leakage attacks targeting virtualized graphics environments.