CVE-2026-41155: GPU Kernel Module Secure Memory Isolation Flaw (CVSS 5.5)

Technical summary

The vulnerability resides in GPU kernel module secure memory management (CWE-653: Missing Authorization). The flaw permits cooperative inter-process data transfer through shared secure memory allocations that should remain isolated between GPU secure processes. An attacker with local user privileges can either exfiltrate data across process boundaries or deliberately corrupt shared GPU resources, leading to denial of service conditions and forcing GPU firmware recovery. The CVSS 3.1 vector (CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H) reflects local attack vector, low complexity, and high availability impact with no confidentiality or integrity impact to the host system itself—only to GPU-resident data and operations.

Business impact

Organizations deploying GPU workloads in multi-tenant or privilege-separated environments face operational disruption and potential data isolation violations. While confidentiality of the host system is not directly compromised, GPU memory corruption can degrade or halt graphics processing and ML inference workloads, impacting dependent services. In environments where GPUs process sensitive user or customer data (rendering, AI inference, simulation), isolation failures create compliance and trust concerns, particularly for industries subject to data residency or separation requirements. Recovery requires GPU hardware reset, introducing latency and potential cascading failures in tightly-coupled applications.

Affected systems

The vulnerability is isolated to the GPU kernel module and affects secure GPU processes on systems running vulnerable kernel versions. Without specific vendor and product information in the public data, affected deployments likely include systems with discrete or integrated GPUs using proprietary or open-source kernel drivers that implement secure GPU memory isolation. Organizations should verify their GPU vendor (NVIDIA, AMD, Intel, etc.) and kernel module version against vendor-specific advisories and patch releases.

Exploitability

Exploitation requires local user-level access to the system and does not demand user interaction or complex attack conditions. An attacker with valid credentials can craft GPU workload submissions or memory allocation requests to trigger inter-process data leakage or resource corruption. The attack is readily repeatable and does not require kernel-mode privileges or sophisticated exploitation techniques. However, the attack surface is limited to systems where multiple GPU secure processes operate concurrently—single-user or single-process GPU deployments face lower risk. No public exploit code or active in-the-wild exploitation has been reported.

Remediation

Apply security updates from your GPU vendor that patch the secure memory allocation authorization logic in the kernel module. Verify the patch version or advisory from the vendor through their official security announcements or portal. If immediate patching is not feasible, operational mitigations include restricting GPU workload execution to trusted, non-adversarial processes and implementing resource isolation policies at the container or OS level to prevent concurrent execution of untrusted GPU code. Disable GPU sharing across user boundaries where functionally possible.

Patch guidance

Contact your GPU vendor (NVIDIA, AMD, Intel, or other chipset manufacturer) for kernel module security updates addressing secure memory isolation. Patch releases are typically bundled with GPU driver updates or distributed as kernel-module-only hotfixes depending on the platform. Test patches in a non-production environment first, as GPU driver updates may require system reboot and can affect dependent workloads. Document the baseline kernel module version before patching for regression analysis. Verify that post-patch GPU secure process isolation is restored via vendor-supplied validation utilities if available.

Detection guidance

Monitor system logs for GPU kernel module errors, firmware recovery events, or secure memory allocation failures that correlate with unexpected GPU process termination or image corruption. Examine access patterns to GPU secure memory regions using GPU vendor diagnostic tools or kernel ftrace/eBPF to detect anomalous inter-process memory sharing requests. In containerized environments, alert on GPU device access violations or GPU cgroup memory exhaustion events that suggest resource interference. Correlate GPU process crashes with the timing of other GPU workload submissions to identify deliberate disruption patterns. Review GPU kernel module audit logs if enabled.

Why prioritize this

Although scored MEDIUM (5.5 CVSS), this vulnerability warrants prompt attention in GPU-intensive environments because: (1) GPU resource isolation is often assumed and deprioritized relative to CPU-side mitigations, yet impacts availability and data integrity of accelerated workloads; (2) multi-tenant GPU clusters, AI inference platforms, and rendering farms are increasingly common, expanding the attack surface; (3) recovery from GPU corruption is non-trivial and can cascade to dependent services; (4) patches may require coordinated reboots in production GPU environments. Organizations operating shared or multi-user GPU infrastructure should prioritize this over lower-risk network-only vulnerabilities.

Risk score, explained

CVSS 5.5 (MEDIUM) reflects: Local attack vector (no remote exploitation), low attack complexity (no special conditions), low privilege requirement (standard user access), no user interaction, no scope escalation, and high availability impact (GPU operations disrupted). Confidentiality and integrity scores are zero because the vulnerability does not breach host OS data confidentiality or alter host system integrity—damage is confined to GPU resource state and multi-process GPU memory isolation. A slightly higher base score would be appropriate in environments where GPU data correlates to sensitive business logic; however, the base score conservatively reflects the technical boundaries of the flaw.

Frequently asked questions