CVE-2025-23284 in GPU Display Driver
Summary
by MITRE • 08/03/2025
NVIDIA vGPU software contains a vulnerability in the Virtual GPU Manager, where a malicious guest could cause a stack buffer overflow. A successful exploit of this vulnerability might lead to code execution, denial of service, information disclosure, or data tampering.
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Analysis
by VulDB Data Team • 08/05/2025
The vulnerability identified as CVE-2025-23284 resides within NVIDIA vGPU software's Virtual GPU Manager component, representing a critical security weakness that undermines the integrity of virtualized graphics environments. This flaw manifests as a stack buffer overflow condition that occurs when processing input data from guest virtual machines within the vGPU framework. The vulnerability stems from insufficient bounds checking mechanisms within the memory management routines of the Virtual GPU Manager, creating an exploitable condition where malicious input can overwrite adjacent stack memory locations. Such a condition fundamentally compromises the stability and security posture of the virtualized graphics infrastructure, as the stack overflow can be leveraged to manipulate program execution flow and potentially execute arbitrary code within the context of the affected process.
The technical exploitation of this vulnerability follows established patterns consistent with stack-based buffer overflow attacks, where an attacker crafts malicious input to exceed the allocated buffer size and overwrite critical stack memory regions including return addresses, function pointers, and local variables. The impact of successful exploitation extends beyond simple code execution to encompass broader security implications including denial of service through process termination, information disclosure via memory content exposure, and data tampering capabilities that can compromise the integrity of guest virtual machine operations. This vulnerability directly maps to CWE-121 Stack-based Buffer Overflow, which classifies the flaw as a fundamental memory safety issue where insufficient validation allows attackers to overwrite stack memory. The attack vector typically involves a malicious guest virtual machine attempting to communicate with the host's Virtual GPU Manager through the vGPU software interface, where carefully crafted inputs trigger the buffer overflow condition.
From an operational standpoint, the exploitation of CVE-2025-23284 presents significant risks to organizations utilizing NVIDIA vGPU solutions in cloud computing environments, virtual desktop infrastructures, and enterprise graphics virtualization deployments. The vulnerability can be particularly dangerous in multi-tenant environments where guest VMs from different organizations share the same physical host, as a successful exploit in one guest could potentially compromise the entire host system or other VMs running on the same infrastructure. The impact assessment reveals that this vulnerability aligns with several ATT&CK techniques including T1059 Command and Scripting Interpreter for code execution, T1499 Endpoint Denial of Service for service disruption, and T1567 Credential Access through potential information disclosure. Organizations relying on vGPU technology for graphics-intensive applications, such as virtualized CAD workstations, gaming platforms, or professional visualization tools, face heightened risk of service interruption and data compromise.
Mitigation strategies for CVE-2025-23284 should prioritize immediate patch deployment from NVIDIA, as the vendor has likely released security updates addressing the specific buffer overflow condition in the Virtual GPU Manager. System administrators should implement network segmentation and access controls to limit guest VM privileges and reduce the attack surface available to potential exploiters. Additional protective measures include enabling memory protection features such as stack canaries, address space layout randomization, and data execution prevention mechanisms where supported. Monitoring and logging should be enhanced to detect anomalous behavior patterns that might indicate exploitation attempts, particularly around vGPU communication interfaces and memory allocation routines. The remediation process should also include comprehensive vulnerability assessments of all vGPU-enabled systems to identify potential additional attack vectors and ensure complete protection against similar memory corruption vulnerabilities. Organizations should consider implementing zero-trust network principles for vGPU environments and maintain regular security updates to address evolving threats targeting virtualized graphics infrastructure components.