CVE-2026-5843

Published May 22, 2026

Last updated 6 days ago

Overview

Description
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.
Source
security@docker.com
NVD status
Analyzed
Products
docker_desktop

Risk scores

CVSS 4.0

Type
Secondary
Base score
8.8
Impact score
-
Exploitability score
-
Vector string
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
Severity
HIGH

CVSS 3.1

Type
Primary
Base score
8.6
Impact score
6
Exploitability score
1.8
Vector string
CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:H
Severity
HIGH

Weaknesses

security@docker.com
CWE-829

Social media

Hype score
Not currently trending

Configurations

References

Sources include official advisories and independent security research.