CVE-2026-47537 in GeForce
Summary
by MITRE • 09/30/2026
NVIDIA GPU Display Driver for Linux contains a vulnerability in the kernel mode layer where an attacker could cause an out-of-bounds write. 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 GPU Display Driver for Linux presents a critical security flaw within its kernel-mode components, specifically involving memory management operations that handle display buffer allocations and context switches. This vulnerability stems from an insufficient validation mechanism when processing user-supplied input related to graphics rendering commands or frame buffer configurations. The core technical issue is classified as an out-of-bounds write, which corresponds directly to CWE-787 in the Common Weakness Enumeration standard. In this scenario, the driver fails to properly verify that a memory access request stays within the boundaries of the allocated kernel-space buffer. When an attacker crafts specific malicious input sequences targeting these display subsystem interfaces, they can manipulate pointer arithmetic or size parameters such that data is written beyond the intended memory region into adjacent kernel structures.
The operational impact of this vulnerability is severe due to its location in the kernel mode layer, which operates with the highest level of system privileges on a Linux operating system. A successful exploitation allows an attacker to overwrite critical kernel data structures, including function pointers or control flow metadata. This capability directly facilitates arbitrary code execution within the kernel context, effectively granting full control over the underlying hardware and software stack. Furthermore, because the vulnerability resides in the display driver, it can be triggered by local users who have access to graphical interfaces or specific device nodes without requiring prior administrative privileges, thereby enabling privilege escalation from a standard user account to root-level access. This aligns with ATT&CK technique T1068, which covers exploitation for privilege escalation, and potentially T1203 if the attacker utilizes this foothold to execute malicious software on the system.
Beyond immediate code execution, the out-of-bounds write can lead to denial of service conditions by corrupting kernel memory in a way that causes system crashes or panics, disrupting availability for all users on the host machine. Additionally, depending on what adjacent data is overwritten, there is a risk of information disclosure if sensitive kernel pointers are leaked through subsequent reads, and data tampering if critical configuration files or security policies stored in nearby memory regions are altered. The attack vector typically involves interacting with the X Window System or Wayland compositor via the NVIDIA proprietary driver interfaces, making it accessible to any local user who can initiate graphical operations.
Mitigation strategies must focus on both immediate remediation and long-term architectural improvements. The primary defense is the application of vendor-provided patches that update the kernel module components of the NVIDIA GPU Display Driver to versions where input validation checks have been strengthened to enforce strict bounds checking before memory writes occur. Organizations should prioritize patching systems running affected driver versions, particularly those exposed to untrusted local users or multi-tenant environments. In addition to software updates, implementing mandatory access control frameworks such as SELinux or AppArmor can help restrict the capabilities of user processes interacting with GPU devices, limiting the potential blast radius if an exploit is attempted. Regular auditing of kernel module signatures and ensuring that only signed, trusted drivers are loaded into the kernel further reduces the attack surface associated with third-party hardware components like GPUs.