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CVE-2026-6859: Inclusion of Functionality from Untrusted Control Sphere in Red Hat Red Hat Enterprise Linux AI (RHEL AI) 3

0
High
VulnerabilityCVE-2026-6859cvecve-2026-6859
Published: Wed Apr 22 2026 (04/22/2026, 13:04:04 UTC)
Source: CVE Database V5
Vendor/Project: Red Hat
Product: Red Hat Enterprise Linux AI (RHEL AI) 3

Description

A flaw was found in InstructLab. The `linux_train.py` script hardcodes `trust_remote_code=True` when loading models from HuggingFace. This allows a remote attacker to achieve arbitrary Python code execution by convincing a user to run `ilab train/download/generate` with a specially crafted malicious model from the HuggingFace Hub. This vulnerability can lead to complete system compromise.

AI-Powered Analysis

Machine-generated threat intelligence

AILast updated: 04/22/2026, 14:01:13 UTC

Technical Analysis

The vulnerability CVE-2026-6859 affects Red Hat Enterprise Linux AI (RHEL AI) 3 through the InstructLab component's `linux_train.py` script. This script sets `trust_remote_code=True` when loading models from the HuggingFace Hub, which implicitly trusts and executes remote code embedded in those models. An attacker can exploit this by providing a specially crafted malicious model that, when loaded by a user running `ilab train/download/generate`, results in arbitrary Python code execution. This can lead to full system compromise. The CVSS v3.1 score is 8.8, indicating high severity. The vendor advisory does not currently specify any patch or mitigation steps.

Potential Impact

Successful exploitation allows remote attackers to execute arbitrary Python code on the affected system without privileges, leading to complete system compromise. This impacts confidentiality, integrity, and availability of the system running RHEL AI 3 with the vulnerable InstructLab component.

Mitigation Recommendations

Patch status is not yet confirmed — check the Red Hat advisory at https://access.redhat.com/security/cve/CVE-2026-6859 for current remediation guidance. Until an official fix is released, users should avoid running `ilab train/download/generate` commands with untrusted or unverified models from the HuggingFace Hub to prevent arbitrary code execution.

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Technical Details

Data Version
5.2
Assigner Short Name
redhat
Date Reserved
2026-04-22T12:54:46.753Z
Cvss Version
3.1
State
PUBLISHED
Remediation Level
null
Vendor Advisory Urls
[{"url":"https://access.redhat.com/security/cve/CVE-2026-6859","vendor":"Red Hat"}]

Threat ID: 69e8d12119fe3cd2cdb88e3d

Added to database: 4/22/2026, 1:46:09 PM

Last enriched: 4/22/2026, 2:01:13 PM

Last updated: 4/23/2026, 1:09:40 AM

Views: 7

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