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.
References
| Link | Resource |
|---|---|
| https://docs.docker.com/desktop/release-notes/#4680 | Release Notes |
Configurations
Configuration 1 (hide)
| AND |
|
History
01 Jun 2026, 18:08
| Type | Values Removed | Values Added |
|---|---|---|
| CPE | cpe:2.3:a:docker:docker_desktop:*:*:*:*:*:*:*:* cpe:2.3:o:apple:macos:-:*:*:*:*:*:*:* |
|
| References | () https://docs.docker.com/desktop/release-notes/#4680 - Release Notes | |
| First Time |
Docker
Apple Docker docker Desktop Apple macos |
22 May 2026, 20:44
| Type | Values Removed | Values Added |
|---|---|---|
| New CVE |
Information
Published : 2026-05-22 20:16
Updated : 2026-06-01 18:08
NVD link : CVE-2026-5817
Mitre link : CVE-2026-5817
CVE.ORG link : CVE-2026-5817
JSON object : View
Products Affected
docker
- docker_desktop
apple
- macos
CWE
CWE-829
Inclusion of Functionality from Untrusted Control Sphere
