Description
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.
Affected products
| Vendor | Product | Affected | Fixed |
|---|---|---|---|
| Docker | Docker Desktop | 4.62.0 – < 4.68.0 | 4.68.0 |
Public exploits
Exploit or proof-of-concept code for this vulnerability is publicly available, which lowers the bar for attackers. Treat it as a reason to patch sooner.
GitHub 2 repositories
-
gouldnicholas/CVE-2026-5817-PoC ★ 0 · May 22, 2026
Docker Model Runner container-to-host RCE / Escape: A critical vulnerability that allows for container-to-host code execution in the Docker Model Runner MLX / SGLANG / VLLM inference backend.
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davidrxchester/CVE-2026-5817 ★ 0 · May 20, 2026
Docker Container-to-Host Remote Code Execution POC via vllm-metal trust_remote_code=True
Sources: PoC-in-GitHub, Metasploit Framework, Exploit-DB — updated daily. Only links are listed; no exploit code is hosted here.
Advisories 1
- WID-SEC-2026-1662 Docker Desktop Model Runner: Mehrere Schwachstellen ermöglichen Codeausführung BSI CERT-Bund (WID) · May 25, 2026
References
- https://docs.docker.com/desktop/release-notes/#4680 release-notes