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VulnerabilityPublished Updated

CVE-2026-5843: Docker Desktop · Untrusted Functionality Inclusion

Affects Docker DesktopSource CVE Database V5

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Not known to be exploited · CVSS 8.8 High : upgrade to 4.71.0 soon.

Data as of 30 Oct 2026, 11:52 UTC

CVSS 4.0 base score
8.8High
How severe the flaw is on the 0–10 CVSS scale.
EPSS
0.2% chance of exploitation in 30 days – higher than 13% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
Patch
Available – fixed in 4.71.0
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

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 22 May 2026

  2. Detectable: no evidence on record.

    No public nuclei template indexed

  3. Weaponized: evidence found.

    Public exploit code: GitHub proofs of concept

  4. Exploited in the wild: no evidence on record.

    Not in CISA KEV and no source reports exploitation

  5. Observed by OffSeq Mirage: no evidence on record.

    No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), GitHub proofs of concept, the Metasploit, Exploit-DB and nuclei-templates index as of 30 Oct 2026.

What to do

Upgrade Docker Desktop to 4.71.0.

Affected software

ProductAffectedFixed in
DockerDocker DesktopAffected
  • >=4.56.0 <4.71.0
Fixed in
  • 4.71.0

AI-suggested

If you cannot patch yet, restrict access to the Docker network and the model-runner.docker.internal API to trusted users and containers only.

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.

References

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