CVE-2026-5843
highpriority · track · 44EPSS 0.002 · 13 %ileexploit · PoCDEEUUSEPSS · scored 2026-10-27
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.
cvss
Technical severity, 0–10. One row per scoring source.
base score 0–10 · higher = more severe · hover a vector to decode
ssvc
A stakeholder decision — act, attend, or track — from exploitation and impact.
weaknesses
The CWE weakness classes this flaw belongs to.
exploits (1)
Public proof-of-concept and weaponised exploit code.
affected products (6)
Products and version ranges known to be affected.
advisories (1)
Vendor and ecosystem advisories describing this.
- WID-SEC-W-2026-1662Docker Desktop Model Runner: Mehrere Schwachstellen ermöglichen CodeausführungDeutsch2026-05-25csaf · cert_bundDE
Ein Angreifer kann mehrere Schwachstellen in Docker Desktop Model Runner ausnutzen, um beliebigen Programmcode auszuführen.
also known as (3)
Other names and identifiers for this entity.
sources
Which sources assert this record, and when.
references (4)
External citations — patches, advisories, analysis.
Attackers weaponise vulnerabilities like this against internet-exposed services. See what is exposed on your perimeter with a free passive scan.
Free scan