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Vulnerability Database/CVE-2026-34194

CVE-2026-34194: GPU Privilege Escalation Vulnerability

CVE-2026-34194 is a privilege escalation vulnerability affecting GPU system calls through improper sparse memory mapping management. Attackers can exploit this to gain elevated privileges. This article covers technical details, impact assessment, affected systems, and mitigation strategies.

Published:

CVE-2026-34194 Overview

CVE-2026-34194 affects Imagination Technologies GPU drivers. A non-privileged local user can issue improper GPU system calls that cause mismanagement of the mapping state maintained for a sparse memory allocation. The root cause is incorrect pointer scaling [CWE-468], where math operations on pointers are implicitly scaled across buffers of different sizes, causing the driver to reference the wrong memory region.

Successful exploitation allows a local attacker with low privileges to corrupt kernel memory, leading to integrity and availability impact on the host system. The flaw is exploitable from user space without user interaction, making it relevant for multi-tenant systems and devices that expose GPU compute APIs to unprivileged applications.

Critical Impact

A local low-privileged user can corrupt GPU driver memory state through crafted system calls, resulting in high integrity and availability impact on affected GPU-equipped systems.

Affected Products

  • Imagination Technologies GPU drivers (see vendor advisory for specific driver versions and DDK releases)
  • Systems and devices integrating affected PowerVR/IMG GPU driver stacks
  • Downstream platforms shipping the impacted GPU kernel components

Discovery Timeline

  • 2026-06-08 - CVE-2026-34194 published to the National Vulnerability Database (NVD)
  • 2026-06-09 - Last updated in NVD database

Technical Details for CVE-2026-34194

Vulnerability Analysis

The vulnerability resides in the GPU driver code path that maintains mapping state for sparse memory allocations. Sparse allocations let applications reserve a large virtual address range while backing only portions of it with physical memory. The driver tracks which subregions are mapped, unmapped, or partially populated.

When unprivileged GPU system calls operate on these sparse allocations, the driver performs pointer arithmetic that is implicitly scaled by the element size of the target buffer. Because the code mixes buffers of different element sizes, the resulting offset points to an unintended location in the mapping metadata. The driver then updates or reads memory at the wrong address, corrupting the tracked mapping state.

Root Cause

The root cause is classified as [CWE-468]: Incorrect Pointer Scaling. In languages such as C and C++, pointer arithmetic is multiplied by the size of the pointed-to type. When developers compute offsets using one buffer's element size and apply them to a buffer of a different element size, the computed address diverges from the intended target. In this driver, that mismatch corrupts sparse allocation bookkeeping rather than the user payload itself.

Attack Vector

The attack vector is local. An attacker must already execute code as a non-privileged user on the affected system. The attacker opens the GPU device node, allocates a sparse buffer, and then issues a sequence of mapping system calls crafted to trigger the scaling mismatch. No user interaction is required. The result is kernel-context memory corruption inside GPU driver structures, which an attacker can chain toward privilege escalation or denial of service. See the Imagination Technologies Security Advisory for technical details.

No public proof-of-concept code has been published for CVE-2026-34194 at the time of writing.

Detection Methods for CVE-2026-34194

Indicators of Compromise

  • Unexpected GPU driver crashes, kernel oops, or watchdog resets on devices running affected Imagination Technologies drivers.
  • Processes running as non-privileged users repeatedly invoking GPU memory mapping ioctls against the GPU device node.
  • System logs showing GPU memory management errors, page faults attributed to the GPU driver, or sparse allocation state inconsistencies.

Detection Strategies

  • Audit which local users and applications have access to the GPU device node and correlate unexpected access patterns with workload baselines.
  • Monitor kernel ring buffer (dmesg) and syslog for GPU driver fault signatures, sparse mapping warnings, or repeated allocation/unmap cycles from a single non-privileged process.
  • Apply behavioral endpoint monitoring to flag low-privileged processes that interact with kernel driver interfaces in patterns inconsistent with normal application usage.

Monitoring Recommendations

  • Forward kernel logs and GPU driver telemetry to a centralized log platform and alert on driver-level memory faults.
  • Track installed driver versions across the fleet and flag hosts running versions listed as vulnerable in the vendor advisory.
  • Establish baselines for GPU ioctl call rates per user and alert on outliers that may indicate exploitation attempts.

How to Mitigate CVE-2026-34194

Immediate Actions Required

  • Identify all systems and devices that ship Imagination Technologies GPU drivers and inventory their driver versions.
  • Apply the vendor-supplied driver update referenced in the Imagination Technologies Security Advisory as soon as it is available for your platform.
  • Restrict execution of untrusted code on affected systems until patches are deployed, since exploitation requires local access.

Patch Information

Imagination Technologies publishes fixed driver versions and integration guidance through its GPU driver vulnerabilities portal. Downstream vendors that ship SoCs or devices based on affected GPU IP must rebuild and redistribute updated kernel modules. Consult the Imagination Technologies Security Advisory for the specific driver and DDK versions that contain the fix for CVE-2026-34194.

Workarounds

  • Limit access to the GPU device node so only trusted user accounts and processes can invoke GPU system calls.
  • Disable or remove GPU compute interfaces for workloads that do not require hardware acceleration on affected systems.
  • Apply standard local-attack hardening: enforce least privilege, restrict shell access for service accounts, and isolate untrusted workloads in dedicated VMs or containers without GPU passthrough.
bash
# Example: restrict access to the GPU device node to a trusted group
# (adjust device path and group to match your platform)
sudo groupadd -r gpuusers
sudo chown root:gpuusers /dev/dri/renderD128
sudo chmod 0660 /dev/dri/renderD128
# Remove non-trusted users from the group
sudo gpasswd -d untrusted_user gpuusers

Disclaimer: This content was generated using AI. While we strive for accuracy, please verify critical information with official sources.

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