Vulnerability in instructlab (CVE-2026-6859)
Summary
Vulnerability in instructlab (CVE-2026-6859). Successful exploitation can lead to full system takeover. Exploitable via linux_train.py.
Original description
The description as published by the source.
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.
Source: NIST National Vulnerability Database NVD GitHub Advisory
Auto-generated summary
Assembled by SecPulse from the source data (CVSS, CWE, affected versions) using templates — no AI involved. Check the original description and references below for exact details.
A vulnerability tracked as CVE-2026-6859 has been found in instructlab.
Attackers can target a specific entry point like linux_train.py over the network to misuse the product.
Successful exploitation can lead to full system takeover. CVSS score: 8.8/10.
What to do: apply the vendor's official patched release.
If unsure, ask your IT team or search "instructlab CVE-2026-6859" on the vendor's site.
CVE-2026-6859 (instructlab) — CWE-829 / CVSS v3 8.8
Attack vector: remote (network-reachable) / unauthenticated
Attack surface: linux_train.py
Plan: 1) Audit SBOM/dependencies, 2) Stage→prod upgrade, 3) Add WAF/proxy monitoring on affected endpoints, 4) Hunt IOCs in logs.
Refs: see the GHSA / vendor advisory / patched release linked on this page.
A vulnerability (CWE-829) exists in instructlab. Attackers reach the vulnerable code path via linux_train.py without authentication.
Check the vendor advisory for the affected versions of instructlab. Attack surface: linux_train.py.
Severity: High (CVSS 8.8/10). Successful exploitation can lead to full system takeover.
Update to the patched release per vendor advisory.
Until the patch is applied: disable the affected feature, apply WAF rules, or restrict access via network ACLs.
Search webserver/proxy logs for unusual request patterns matching this CVE's known IOCs. Run grep -r 'instructlab' . against your dependency files (package-lock.json, requirements.txt, go.sum) to find affected services.
Response actions
Concrete steps and command examples for SOC/SRE teams to execute in order
-
1Identify exposure identify
grep -r 'instructlab' . | grep -v node_modulesリポジトリと本番環境の依存ファイル (package-lock.json / requirements.txt / go.sum / Gemfile.lock 等) で
instructlabを grep し、稼働しているサービス・バージョンを把握する。 -
2Post-deployment verification verify
Confirm patched version is live in productionパッチ適用後、ステージングで PoC または同等の悪用パターンを再現して脆弱性が閉じたことを確認。本番ではアクセスログ・WAF でアラート再発が無いか継続監視。
Affected packages
References
- advisory nvd.nist.gov
- package github.com
- web access.redhat.com
- web bugzilla.redhat.com
- web security.access.redhat.com