CVE-2026-5843 (GCVE-0-2026-5843)
Vulnerability from cvelistv5 – Published: 2026-05-22 19:28 – Updated: 2026-05-22 19:28
VLAI
Title
Docker Model Runner container-to-host code execution via MLX-LM model_file importlib loading
Summary
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.
Severity
CWE
- CWE-829 - Inclusion of Functionality from Untrusted Control Sphere
Assigner
References
1 reference
| URL | Tags |
|---|---|
| https://docs.docker.com/desktop/release-notes/#4710 | release-notes |
Impacted products
1 product
| Vendor | Product | Version | |
|---|---|---|---|
| Docker | Docker Desktop |
Affected:
4.56.0 , < 4.71.0
(semver)
|
Credits
{
"containers": {
"cna": {
"affected": [
{
"defaultStatus": "unaffected",
"platforms": [
"MacOS"
],
"product": "Docker Desktop",
"vendor": "Docker",
"versions": [
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"lessThan": "4.71.0",
"status": "affected",
"version": "4.56.0",
"versionType": "semver"
}
]
}
],
"configurations": [
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}
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"value": "David Rochester (@davidrxchester)"
},
{
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"value": "Nicholas Gould (@gouldnicholas)"
}
],
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"value": "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 \u003ccode\u003emodel_file\u003c/code\u003e configuration field in \u003ccode\u003econfig.json\u003c/code\u003e. When a model\u0027s \u003ccode\u003econfig.json\u003c/code\u003e specifies a \u003ccode\u003emodel_file\u003c/code\u003e pointing to a Python file, MLX-LM uses \u003ccode\u003eimportlib\u003c/code\u003e to load and execute it with no \u003ccode\u003etrust_remote_code\u003c/code\u003e 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.\u003cbr\u003e\u003cbr\u003eAny container on the Docker network can trigger this by calling the \u003ccode\u003emodel-runner.docker.internal\u003c/code\u003e API to pull a malicious model from an attacker-controlled OCI registry and request inference."
}
],
"value": "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\u0027s 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.\n\nAny 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."
}
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"impacts": [
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"metrics": [
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"source": {
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"title": "Docker Model Runner container-to-host code execution via MLX-LM model_file importlib loading",
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"datePublished": "2026-05-22T19:28:38.857Z",
"dateReserved": "2026-04-08T17:43:50.508Z",
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}
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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