Docker Desktop

In Docker Desktop for Windows with the WSL2 backend, an unprivileged Linux container can use 32-bit socketcall to bypass the default seccomp restriction on AF_VSOCK. This can expose host-facing services and Windows files accessible to the logged-in user. The issue affects x86-64 WSL2; LinuxKit-based backends are unaffected. The issue is fully fixed only with Docker Desktop 4.98.0 or later and WSL 3.0.3 or later. Docker Desktop 4.98.0 or later running on an older WSL remains affected.

Published: 2026-11-03T19:08:11.422Z
Updated: 2026-11-04T13:33:36.124Z

Fixed a VM panic caused by unbounded recursion in the grpcfuse kernel module when a container created deeply nested directories on a bind-mounted host folder and triggered a dentry invalidation event. This issue has been fixed in Docker Desktop 4.76.0.

Published: 2026-06-02T21:09:03.375Z
Updated: 2026-06-03T14:08:05.541Z

The Docker CLI --use-api-socket flag bypasses Enhanced Container Isolation (ECI) restrictions in Docker Desktop. When ECI is enabled, Docker socket mounts from containers are denied unless explicitly allowed via the admin-settings configuration. However, the --use-api-socket flag adds the Docker socket mount via the HostConfig.Mounts field rather than the HostConfig.Binds field. The ECI enforcement in the Docker Desktop API proxy only inspected Binds, allowing the mount to pass unchecked. This grants a container full access to the Docker Engine socket and, if the host user has logged in to container registries, their authentication credentials. A local attacker with the ability to run Docker CLI commands can exploit this to escape ECI restrictions, access the Docker Engine, and potentially escalate privileges.

Published: 2026-05-22T18:32:15.959Z
Updated: 2026-05-23T03:56:00.655Z

The MLX inference backend in Docker Model Runner on macOS uses the MLX-LM library, which unconditionally imports and executes arbitrary Python files from model directories via the model_file configuration field in config.json. When a model's config.json specifies a model_file pointing to a Python file, MLX-LM uses importlib to load and execute it with no trust_remote_code gate or equivalent safety check. The MLX backend runs without sandboxing, resulting in arbitrary code execution on the Docker host as the Docker Desktop user. Any container on the Docker network can trigger this by calling the model-runner.docker.internal API to pull a malicious model from an attacker-controlled OCI registry and request inference.

Published: 2026-05-22T19:28:38.857Z
Updated: 2026-05-27T03:55:38.188Z

The vllm-metal inference backend in Docker Model Runner on macOS unconditionally sets trust_remote_code=True when loading model tokenizers, and runs without sandboxing. This causes transformers.AutoTokenizer.from_pretrained() to import and execute arbitrary Python files included in any model pulled from an OCI registry, resulting in arbitrary code execution on the Docker host as the Docker Desktop user when inference is triggered. Any container on the Docker network can trigger this by calling the model-runner.docker.internal API to pull a malicious model and request inference.

Published: 2026-05-22T19:24:15.662Z
Updated: 2026-05-27T03:55:37.087Z