Vulnerability in mlflow (CVE-2026-8147)
Summary
Vulnerability in mlflow (CVE-2026-8147). Confidential information can be exposed externally. Exploitable via _before_request. Mitigation: upgrade to 3.13.0rc0 or later.
Original description
The description as published by the source.
In MLflow versions prior to 3.13.0, when running with authentication enabled, the trace API endpoints lack proper authorization validators. This allows any authenticated user to bypass experiment-level authorization controls on all trace operations, including reading, deleting, and modifying traces on experiments they do not have permission to access. The issue arises from the _before_request handler, which does not register authorization validators for trace endpoints, resulting in requests proceeding without validation. This vulnerability can expose sensitive data, destroy audit logs, and allow unauthorized modifications.
Source: GitHub Security Advisories (Global) 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-2026-8147 has been found in mlflow.
Attackers can target a specific entry point like _before_request over the network to misuse the product.
Confidential information can be exposed externally. CVSS score: 8.1/10.
What to do: upgrade mlflow to 3.13.0rc0 or later.
If unsure, ask your IT team or search "mlflow CVE-2026-8147" on the vendor's site.
CVE-2026-8147 (mlflow) — CWE-284 / CVSS v3 8.1
Attack vector: remote (network-reachable) / no user interaction
Attack surface: _before_request
Patched: 3.13.0rc0 — apply immediately
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-284) exists in mlflow. Attackers reach the vulnerable code path via _before_request.
Check the vendor advisory for the affected versions of mlflow. Attack surface: _before_request.
Severity: High (CVSS 8.1/10). Confidential information can be exposed externally.
Update to 3.13.0rc0.
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 'mlflow' . 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
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1Identify exposure identify
grep -r 'mlflow' . | 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
mlflowを grep し、稼働しているサービス・バージョンを把握する。 -
2Apply patch patch
Upgrade mlflow to 3.13.0rc0ステージング環境で 3.13.0rc0 に上げて回帰テスト → 本番反映。回帰テストはアプリの主要ハッピーパスを含めること。
-
3Post-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
- advisory github.com
- package github.com
- package pypi.org
- web github.com
- web huntr.com
- web github.com
- web github.com