CVE-2026-6859Instructlab: instructlab: arbitrary code execution due to hardcoded `trust_remote_code=true`
- 8.8HighCVSS base score
- 0.44%Exploitation in 30 daysEPSS · top 61% of all CVEs
- NoKnown exploitednot in CISA's KEV catalog
- NonePublic exploitsnone known yet
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.
Timeline
ID reserved
By redhat
Published
- 3 months later
· 3 months later
Record updated
Changes after publication (a new score, a public exploit, EPSS crossing 1, 10 or 50 %, leaving KEV) are kept since November 2026; earlier ones are not known.
Scores
| Scored by | CVSS | Score | Vector |
|---|---|---|---|
| redhatCNA (assigner) | 3.1 | High8.8 | CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H |
| redhat-SADPADP (enrichment) | 3.1 | High8.8 | CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H |
| NVDNVD · Modified | 3.1 | High8.8 | CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H |
- EPSS (exploitation in 30 days)
- 0.44% · top 61% of all CVEs (14 Nov 2026)
- CISA SSVC
- Exploitation: none · Automatable: no · Technical impact: total
The list uses the assigner's score when there is one, then CISA's, then NVD's: High 8.8.
Affected products
Red Hat · Red Hat Enterprise Linux AI (RHEL AI) 3
All versions: affected
Red Hat · Red Hat Enterprise Linux AI (RHEL AI) 3
All versions: affected
Red Hat · Red Hat Enterprise Linux AI (RHEL AI) 3
All versions: unaffected
Red Hat · Red Hat Enterprise Linux AI (RHEL AI) 3
All versions: affected
Red Hat · Red Hat Enterprise Linux AI (RHEL AI) 3
All versions: affected
Red Hat · Red Hat Enterprise Linux AI (RHEL AI) 3
All versions: unaffected
Affected packages
From reviewed advisories of the GitHub Advisory Database.
- PyPIinstructlabGHSA-rxpq-xgqx-fr7p (opens in a new tab)
What to do
Workaround: To mitigate this issue, only use models from trusted sources when performing `instructlab` operations. Review the origin and integrity of any HuggingFace model before using it with `ilab train/download/generate`. Consider running `instructlab` commands within a sandboxed or isolated environment to limit the potential impact of executing untrusted code.
References
References3
- https://access.redhat.com/security/cve/CVE-2026-6859 (opens in a new tab)vdb-entryx_refsource_REDHAT
- RHBZ#2459998 (opens in a new tab)issue-trackingx_refsource_REDHAT
- https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-6859.json (opens in a new tab)x_sadp-csaf-vex
Sources
The same CVE in the primary databases and aggregators, to check against.
- CVE.org record (opens in a new tab)
- CVE List JSON (GitHub) (opens in a new tab)
- NVD (opens in a new tab)
- FIRST EPSS (opens in a new tab)
- EUVD EUVD-2026-24752 (opens in a new tab)
- OSV.dev (opens in a new tab)
- GitHub Advisory GHSA-rxpq-xgqx-fr7p (opens in a new tab)
- CIRCL Vulnerability-Lookup (opens in a new tab)
Badge for a README or a ticket
[](https://cveledger.app/cve/CVE-2026-6859)Record last updated .