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CVE-2026-6859 Red Hat CVE debrief

CVE-2026-6859 is a high-severity vulnerability in InstructLab, a project by Red Hat, that allows remote attackers to execute arbitrary Python code. The flaw is caused by the `linux_train.py` script hardcoding `trust_remote_code=True` when loading models from HuggingFace. This enables 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. The vulnerability has a CVSS score of 8.8 and is classified as HIGH severity. It affects InstructLab and Red Hat Enterprise Linux AI 3.0.

Vendor
Red Hat
Product
Red Hat Enterprise Linux AI (RHEL AI) 3
CVSS
HIGH 8.8
CISA KEV
Not listed in stored evidence
Original CVE published
2026-04-22
Original CVE updated
2026-07-15
Advisory published
2026-04-22
Advisory updated
2026-07-15

Who should care

Security teams and administrators responsible for InstructLab and Red Hat Enterprise Linux AI 3.0 should be aware of this vulnerability. The vulnerability can lead to complete system compromise, making it critical for organizations using these products to take immediate action.

Technical summary

The `linux_train.py` script in InstructLab has a hardcoded `trust_remote_code=True` setting when loading models from HuggingFace. This allows remote attackers to execute arbitrary Python code by providing a specially crafted malicious model. The vulnerability is triggered when a user runs `ilab train/download/generate` with the malicious model. The CVSS vector for this vulnerability is CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H.

Defensive priority

High priority should be given to patching or mitigating this vulnerability, as it can lead to complete system compromise. Organizations using InstructLab and Red Hat Enterprise Linux AI 3.0 should take immediate action to protect their systems.

Recommended defensive actions

  • Apply patches or updates provided by Red Hat to address the vulnerability.
  • Restrict access to the `ilab train/download/generate` command to trusted users only.
  • Implement additional security measures, such as validating models from HuggingFace before loading them.
  • Monitor systems for suspicious activity related to InstructLab and Red Hat Enterprise Linux AI 3.0.
  • Consider implementing compensating controls, such as network segmentation or intrusion detection systems.

Evidence notes

The CVE-2026-6859 vulnerability was publicly disclosed on April 22, 2026, and has since been modified on June 30, 2026. The vulnerability affects InstructLab and Red Hat Enterprise Linux AI 3.0. The CVSS score for this vulnerability is 8.8, indicating high severity.

Sources and references

Verified primary and authoritative sources

  • CVE-2026-6859 CVE Program record

    Publisher, destination, and source semantics verified

    URL: https://www.cve.org/CVERecord?id=CVE-2026-6859

    CVE Program - Official CVE Program record with source-provided CVE metadata.

  • CVE-2026-6859 NVD vulnerability detail

    Publisher, destination, and source semantics verified

    URL: https://nvd.nist.gov/vuln/detail/CVE-2026-6859

    NIST National Vulnerability Database - Official NIST NVD detail page and source-specific vulnerability assessment.

Supplemental references

Methodology and review provenance

AI-assisted synthesis based on stored public vulnerability evidence. System validation, approval state, and publication status do not by themselves establish human review of this revision. PatchSiren helps prioritize defensive review and does not prove exposure or remediation on any system.