Docker Desktop up to 4.67.x vllm-metal Inference Backend transformers.AutoTokenizer.from_pretrained inclusion of functionality from untrusted control sphere

CVSS Meta Temp Score
CVSS is a standardized scoring system to determine possibilities of attacks. The Temp Score considers temporal factors like disclosure, exploit and countermeasures. The unique Meta Score calculates the average score of different sources to provide a normalized scoring system.
Current Exploit Price (≈)
Our analysts are monitoring exploit markets and are in contact with vulnerability brokers. The range indicates the observed or calculated exploit price to be seen on exploit markets. A good indicator to understand the monetary effort required for and the popularity of an attack.
CTI Interest Score
Our Cyber Threat Intelligence team is monitoring different web sites, mailing lists, exploit markets and social media networks. The CTI Interest Score identifies the interest of attackers and the security community for this specific vulnerability in real-time. A high score indicates an elevated risk to be targeted for this vulnerability.
7.6$0-$5k0.00

Summaryinfo

A vulnerability classified as critical was found in Docker Desktop up to 4.67.x. This affects the function transformers.AutoTokenizer.from_pretrained of the component vllm-metal Inference Backend. The manipulation results in inclusion of functionality from untrusted control sphere. This vulnerability is cataloged as CVE-2026-5817. The attack must be initiated from a local position. There is no exploit available. Upgrading the affected component is advised.

Detailsinfo

A vulnerability classified as critical has been found in Docker Desktop up to 4.67.x. Affected is the function transformers.AutoTokenizer.from_pretrained of the component vllm-metal Inference Backend. The manipulation with an unknown input leads to a inclusion of functionality from untrusted control sphere vulnerability. CWE is classifying the issue as CWE-829. The product imports, requires, or includes executable functionality (such as a library) from a source that is outside of the intended control sphere. This is going to have an impact on confidentiality, integrity, and availability. CVE summarizes:

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.

The weakness was shared by David Rochester. The advisory is available at docs.docker.com. This vulnerability is traded as CVE-2026-5817 since 04/08/2026. The exploitability is told to be easy. Local access is required to approach this attack. Successful exploitation requires user interaction by the victim. Technical details are known, but there is no available exploit.

The vulnerability scanner Nessus provides a plugin with the ID 316464 (Docker Desktop < 4.68.0 Container Escape (CVE-2026-5817)), which helps to determine the existence of the flaw in a target environment.

Upgrading to version 4.68.0 eliminates this vulnerability.

The vulnerability is also documented in the vulnerability database at Tenable (316464). If you want to get best quality of vulnerability data, you may have to visit VulDB.

Productinfo

Type

Vendor

Name

Version

CPE 2.3info

CPE 2.2info

CVSSv4info

VulDB Vector: 🔒
VulDB Reliability: 🔍

CNA CVSS-B Score: 🔒
CNA CVSS-BT Score: 🔒
CNA Vector: 🔒

CVSSv3info

VulDB Meta Base Score: 7.7
VulDB Meta Temp Score: 7.6

VulDB Base Score: 7.3
VulDB Temp Score: 7.0
VulDB Vector: 🔒
VulDB Reliability: 🔍

CNA Base Score: 8.2
CNA Vector (Docker): 🔒

CVSSv2info

AVACAuCIA
💳💳💳💳💳💳
💳💳💳💳💳💳
💳💳💳💳💳💳
VectorComplexityAuthenticationConfidentialityIntegrityAvailability
UnlockUnlockUnlockUnlockUnlockUnlock
UnlockUnlockUnlockUnlockUnlockUnlock
UnlockUnlockUnlockUnlockUnlockUnlock

VulDB Base Score: 🔒
VulDB Temp Score: 🔒
VulDB Reliability: 🔍

Exploitinginfo

Class: Inclusion of functionality from untrusted control sphere
CWE: CWE-829
CAPEC: 🔒
ATT&CK: 🔒

Physical: Partially
Local: Yes
Remote: Partially

Availability: 🔒
Status: Not defined

EPSS Score: 🔒
EPSS Percentile: 🔒

Price Prediction: 🔍
Current Price Estimation: 🔒

0-DayUnlockUnlockUnlockUnlock
TodayUnlockUnlockUnlockUnlock

Nessus ID: 316464
Nessus Name: Docker Desktop < 4.68.0 Container Escape (CVE-2026-5817)

Threat Intelligenceinfo

Interest: 🔍
Active Actors: 🔍
Active APT Groups: 🔍

Countermeasuresinfo

Recommended: Upgrade
Status: 🔍

0-Day Time: 🔒

Upgrade: Desktop 4.68.0

Timelineinfo

04/08/2026 CVE reserved
05/23/2026 +45 days Advisory disclosed
05/23/2026 +0 days VulDB entry created
05/23/2026 +0 days VulDB entry last update

Sourcesinfo

Advisory: docs.docker.com
Researcher: David Rochester
Status: Confirmed

CVE: CVE-2026-5817 (🔒)
GCVE (CVE): GCVE-0-2026-5817
GCVE (VulDB): GCVE-100-365274

Entryinfo

Created: 05/23/2026 07:48
Updated: 05/23/2026 18:20
Changes: 05/23/2026 07:48 (78), 05/23/2026 18:20 (2)
Complete: 🔍
Cache ID: 216::103

If you want to get best quality of vulnerability data, you may have to visit VulDB.

Discussion

No comments yet. Languages: en.

Please log in to comment.

Do you want to use VulDB in your project?

Use the official API to access entries easily!