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.
| Vendor | Product | Version(s) | CPE |
|---|---|---|---|
>= 4.62.0, < 4.68.0CPE matchmatch criteria | cpe:2.3:a:docker:docker_desktop:*:*:*:*:*:*:*:* |
CVSS version used by this source: 4.0
CVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:N/VC:H/VI:H/VA:H/SC:H/SI:H/SA:H/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X
The average CVE in this peer group has 0.0 Twitter, 0.1 Reddit, 0.1 Bluesky, 0.0 Mastodon, and 0.2 GitHub mentions.
No media coverage found for this CVE.
The average CVE in this peer group has 0.3 InfoSec Media, 0.0 Vendor Blog, and 0.0 Security Researcher mentions.
Remediation records are not available for this CVE.