GHSA-RXPQ-XGQX-FR7P
Vulnerability from github – Published: 2026-04-22 15:31 – Updated: 2026-04-29 22:08
VLAI
Summary
InstructLab Includes Functionality from Untrusted Control Sphere
Details
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.
Severity
8.8 (High)
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "instructlab"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"last_affected": "0.26.1"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2026-6859"
],
"database_specific": {
"cwe_ids": [
"CWE-829"
],
"github_reviewed": true,
"github_reviewed_at": "2026-04-29T22:08:37Z",
"nvd_published_at": "2026-04-22T14:17:07Z",
"severity": "HIGH"
},
"details": "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.",
"id": "GHSA-rxpq-xgqx-fr7p",
"modified": "2026-04-29T22:08:37Z",
"published": "2026-04-22T15:31:45Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-6859"
},
{
"type": "WEB",
"url": "https://access.redhat.com/security/cve/CVE-2026-6859"
},
{
"type": "WEB",
"url": "https://bugzilla.redhat.com/show_bug.cgi?id=2459998"
},
{
"type": "PACKAGE",
"url": "https://github.com/instructlab/instructlab"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
"type": "CVSS_V3"
}
],
"summary": "InstructLab Includes Functionality from Untrusted Control Sphere"
}
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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