WebGPU

1. Introduction

This section is non-normative.

Graphics Processing Units, or GPUs for short, have been essential in enabling rich rendering and computational applications in personal computing. WebGPU is an API that exposes the capabilities of GPU hardware for the Web. The API is designed from the ground up to efficiently map to (post-2014) native GPU APIs. WebGPU is not related to WebGL and does not explicitly target OpenGL ES.

WebGPU sees physical GPU hardware as GPUAdapters. It provides a connection to an adapter via GPUDevice, which manages resources, and the device’s GPUQueues, which execute commands. GPUDevice may have its own memory with high-speed access to the processing units. GPUBuffer and GPUTexture are the physical resources backed by GPU memory. GPUCommandBuffer and GPURenderBundle are containers for user-recorded commands. GPUShaderModule contains shader code. The other resources, such as GPUSampler or GPUBindGroup, configure the way physical resources are used by the GPU.

GPUs execute commands encoded in GPUCommandBuffers by feeding data through a pipeline, which is a mix of fixed-function and programmable stages. Programmable stages execute shaders, which are special programs designed to run on GPU hardware. Most of the state of a pipeline is defined by a GPURenderPipeline or a GPUComputePipeline object. The state not included in these pipeline objects is set during encoding with commands, such as beginRenderPass() or setBlendConstant().

2. Malicious use considerations

This section is non-normative. It describes the risks associated with exposing this API on the Web.

2.1. Security Considerations

The security requirements for WebGPU are the same as ever for the web, and are likewise non-negotiable. The general approach is strictly validating all the commands before they reach GPU, ensuring that a page can only work with its own data.

2.1.1. CPU-based undefined behavior

A WebGPU implementation translates the workloads issued by the user into API commands specific to the target platform. Native APIs specify the valid usage for the commands (for example, see vkCreateDescriptorSetLayout) and generally don’t guarantee any outcome if the valid usage rules are not followed. This is called "undefined behavior", and it can be exploited by an attacker to access memory they don’t own, or force the driver to execute arbitrary code.

In order to disallow insecure usage, the range of allowed WebGPU behaviors is defined for any input. An implementation has to validate all the input from the user and only reach the driver with the valid workloads. This document specifies all the error conditions and handling semantics. For example, specifying the same buffer with intersecting ranges in both "source" and "destination" of copyBufferToBuffer() results in GPUCommandEncoder generating an error, and no other operation occurring.

See § 22 Errors & Debugging for more information about error handling.

2.1.2. GPU-based undefined behavior

WebGPU shaders are executed by the compute units inside GPU hardware. In native APIs, some of the shader instructions may result in undefined behavior on the GPU. In order to address that, the shader instruction set and its defined behaviors are strictly defined by WebGPU. When a shader is provided to createShaderModule(), the WebGPU implementation has to validate it before doing any translation (to platform-specific shaders) or transformation passes.

2.1.3. Uninitialized data

Generally, allocating new memory may expose the leftover data of other applications running on the system. In order to address that, WebGPU conceptually initializes all the resources to zero, although in practice an implementation may skip this step if it sees the developer initializing the contents manually. This includes variables and shared workgroup memory inside shaders.

The precise mechanism of clearing the workgroup memory can differ between platforms. If the native API does not provide facilities to clear it, the WebGPU implementation transforms the compute shader to first do a clear across all invocations, synchronize them, and continue executing developer’s code.

2.1.4. Out-of-bounds access in shaders

Shaders can access physical resources either directly (for example, as a "uniform" GPUBufferBinding), or via texture units, which are fixed-function hardware blocks that handle texture coordinate conversions. Validation in the WebGPU API can only guarantee that all the inputs to the shader are provided and they have the correct usage and types. The WebGPU API can not guarantee that the data is accessed within bounds if the texture units are not involved.

In order to prevent the shaders from accessing GPU memory an application doesn’t own, the WebGPU implementation may enable a special mode (called "robust buffer access") in the driver that guarantees that the access is limited to buffer bounds.

Alternatively, an implementation may transform the shader code by inserting manual bounds checks. When this path is taken, the out-of-bound checks only apply to array indexing. They aren’t needed for plain field access of shader structures due to the minBindingSize validation on the host side.

If the shader attempts to load data outside of physical resource bounds, the implementation is allowed to:

1. return a value at a different location within the resource bounds

2. return a value vector of "(0, 0, 0, X)" with any "X"

3. partially discard the draw or dispatch call

If the shader attempts to write data outside of physical resource bounds, the implementation is allowed to:

1. write the value to a different location within the resource bounds

2. discard the write operation

3. partially discard the draw or dispatch call

2.1.5. Invalid data

When uploading floating-point data from CPU to GPU, or generating it on the GPU, we may end up with a binary representation that doesn’t correspond to a valid number, such as infinity or NaN (not-a-number). The GPU behavior in this case is subject to the accuracy of the GPU hardware implementation of the IEEE-754 standard. WebGPU guarantees that introducing invalid floating-point numbers would only affect the results of arithmetic computations and will not have other side effects.

2.1.6. Driver bugs

GPU drivers are subject to bugs like any other software. If a bug occurs, an attacker could possibly exploit the incorrect behavior of the driver to get access to unprivileged data. In order to reduce the risk, the WebGPU working group will coordinate with GPU vendors to integrate the WebGPU Conformance Test Suite (CTS) as part of their driver testing process, like it was done for WebGL. WebGPU implementations are expected to have workarounds for some of the discovered bugs, and disable WebGPU on drivers with known bugs that can’t be worked around.

2.1.7. Timing attacks

2.1.7.1. Content-timeline timing

WebGPU does not expose new states to JavaScript (the content timeline) which are shared between agents in an agent cluster. Content timeline states such as [[mapping]] only change during explicit content timeline tasks, like in plain JavaScript.

2.1.7.2. Device/queue-timeline timing

Writable storage buffers and other cross-invocation communication may be usable to construct high-precision timers on the queue timeline.

The optional "timestamp-query" feature also provides high precision timing of GPU operations. To mitigate security and privacy concerns, the timing query values are aligned to a lower precision: see current queue timestamp. Note in particular:

• The device timeline typically runs in a process that is shared by multiple origins, so cross-origin isolation (provided by COOP/COEP) does not provide isolation of device/queue-timeline timers.

• Queue timeline work is issued from the device timeline, and may execute on GPU hardware that does not provide the isolation expected of CPU processes (such as Meltdown mitigations).

• GPU hardware is not typically susceptible to Spectre-style attacks, but WebGPU may be implemented in software, and software implementations may run in a shared process, preventing isolation-based mitigations.

2.1.8. Row hammer attacks

Row hammer is a class of attacks that exploit the leaking of states in DRAM cells. It could be used on GPU. WebGPU does not have any specific mitigations in place, and relies on platform-level solutions, such as reduced memory refresh intervals.

2.1.9. Denial of service

WebGPU applications have access to GPU memory and compute units. A WebGPU implementation may limit the available GPU memory to an application, in order to keep other applications responsive. For GPU processing time, a WebGPU implementation may set up "watchdog" timer that makes sure an application doesn’t cause GPU unresponsiveness for more than a few seconds. These measures are similar to those used in WebGL.