InstructlabApplication · Redhat
CVE-2026-6859
Official description Straight from the sourceThe vendor's or NVD's own wording, published unedited. Authoritative, but often terse — it says what broke, rarely what to do.
NVD · uneditedA 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.
Technical summary Written by usOur analysis, written from the advisory, the CVSS vector and the affected-version data. It adds context the advisory leaves out, and never invents facts that are not in the source.
dbcve analysis · high confidenceThe vulnerability exists in InstructLab's linux_train.py script which hardcodes trust_remote_code=True when loading models from HuggingFace Hub. This setting permits arbitrary Python code execution embedded within a malicious model to run on the user's system during training, download, or generation operations, leading to complete system compromise.
Verify against the referenced sources before acting — the references below are authoritative for this CVE, this summary is not.
Affected products & versions What the vendor confirmedThe version ranges the vendor confirmed as vulnerable. If your version sits inside a range here, treat yourself as exposed until you have upgraded.
NVD · CPE data
InstructlabApplication
all versions
Enterprise Linux AiOperating system
= 3.0CVSS breakdown How the score is builtThe industry scoring standard. It rates how the flaw is reached, what it takes to exploit, and what an attacker gains — the score is derived from those, not the other way round.
From the vector- Attack vector
- Network
- Complexity
- Low
- Privileges
- None
- User interaction
- Required
- Scope
- Unchanged
- Confidentiality
- High
- Integrity
- High
- Availability
- High
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
Am I affected? How to checkSteps we derive from the advisory and the affected-version data, so you can decide whether this CVE reaches your setup. They are a guide, not a scan — your own configuration is the authority.
dbcve checksWork through these to decide whether this CVE applies to you.
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Verify InstructLab installationRun 'pip show instructlab' or check for the 'instructlab' package in your Python environmentAffected if instructlab is installed and the version is any (all versions affected)
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Locate linux_train.py scriptFind the file using 'find / -name linux_train.py 2>/dev/null' or check within the InstructLab package directory (typically in site-packages/instructlab/)Affected if the file exists in your InstructLab installation
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Inspect trust_remote_code parameterOpen linux_train.py and search for 'trust_remote_code' using grep or a text editorAffected if the parameter is set to 'True' (allows arbitrary code execution) or is hardcoded without validation
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Identify model loading callsSearch for HuggingFace model loading functions (AutoModel.from_pretrained, pipeline, etc.) in linux_train.pyAffected if models are loaded from remote Hub without disabling trust_remote_code
If InstructLab is installed and the linux_train.py script contains hardcoded trust_remote_code=True when loading remote HuggingFace models, the environment is vulnerable to arbitrary code execution from malicious models.
Generated from the published advisory. Verify against your own configuration.
Remediation Closing itWhat it takes to close this. Where a vendor fix exists we point at it; where none exists we say so plainly, and can build one. Effort estimates are scoped from the advisory, not from your codebase.
From vendor dataRemove the hardcoded trust_remote_code=True setting and default to trust_remote_code=False, or implement model verification/signing mechanisms to validate model integrity before execution.
Fix this in Instructlab
Scoped from the published advisory
- Consultation4.0 h
- Implementation4.0 h
- Testing8.0 h
- Review / QA4.0 h
An estimate, not a bill — we confirm scope with you before any work starts. Need it this week? Rush from $5,504.
Scan for this in your stack
Free · runs locallyCheck whether your project pulls in CVE-2026-6859 — or any other known-vulnerable package — straight from your lock files. Free and open source; it runs locally and uploads nothing.
References Go to the primary sourcePrimary sources — vendor advisories, patches and trackers. Where our summary and a reference disagree, the reference wins.
Primary sourcesPractitioner notes
ContributedPeer-ranked notes from engineers who’ve handled CVE-2026-6859 in production — separate from our analysis above.
The advisory tells you what broke. It rarely tells you what actually worked. If you’ve dealt with this one, that detail is what the next engineer is searching for.
- The version that genuinely resolved it — not the one the vendor claimed
- A config change or rule that shut the vector down
- A gotcha in the upgrade path that cost you an afternoon
No notes yet
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- Verified mitigations, workarounds, and config changes
- Version or environment caveats, and links to real fixes
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