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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.

PUBLISHED Reserved 2026-04-08 | Published 2026-05-22 | Updated 2026-05-27 | Assigner Docker




HIGH: 8.8CVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:N/VC:H/VI:H/VA:H/SC:H/SI:H/SA:H

HIGH: 8.2CVSS:3.1/AV:L/AC:L/PR:L/UI:R/S:C/C:H/I:H/A:H

Problem types

CWE-829: Inclusion of Functionality from Untrusted Control Sphere

Product status

Default status
unaffected

4.62.0 (semver) before 4.68.0
affected

Credits

David Rochester (@davidrxchester) finder

Nicholas Gould (@gouldnicholas) finder

References

docs.docker.com/desktop/release-notes/ release-notes

cve.org (CVE-2026-5817)

nvd.nist.gov (CVE-2026-5817)

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