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CVE-2026-2651 critical CVSS 9.0

Vulnerability in mlflow (CVE-2026-2651)

Summary

Vulnerability in mlflow (CVE-2026-2651). Successful exploitation can lead to full system takeover. Mitigation: upgrade to 3.11.1 or later.

Original description

The description as published by the source.

A vulnerability in MLflow versions <=3.10.1.dev0 allows unauthorized access to multipart upload (MPU) endpoints when the --serve-artifacts mode is enabled. The authorization logic does not enforce resource-level permission checks for /mlflow-artifacts/mpu/* endpoints, enabling attackers to overwrite artifacts belonging to other users. This can lead to unauthorized cross-user writes, model supply chain poisoning, and arbitrary code execution when compromised models are loaded. The issue is resolved in version 3.10.0.

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-2026-2651 has been found in mlflow.
Successful exploitation can lead to full system takeover. CVSS score: 9.0/10.
What to do: upgrade mlflow to 3.11.1 or later.
If unsure, ask your IT team or search "mlflow CVE-2026-2651" on the vendor's site.

CVE-2026-2651 (mlflow) — CWE-862 / CVSS v3 9.0
Attack vector: remote (network-reachable)
Patched: 3.11.1 — 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.

❓ What is the problem

A vulnerability (CWE-862) exists in mlflow.

📍 Affected scope

Check the vendor advisory for the affected versions of mlflow.

🔥 Severity

Severity: Critical (CVSS 9.0/10). Successful exploitation can lead to full system takeover.

🔧 How to fix

Update to 3.11.1.

🛡️ Workaround

Until the patch is applied: disable the affected feature, apply WAF rules, or restrict access via network ACLs.

🔍 Detection

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

  1. 1
    Identify 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。

  2. 2
    Apply patch patch 
    Upgrade mlflow to 3.11.1

    ステージング環境で 3.11.1 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。

  3. 3
    Post-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

Bitnami mlflow
[{"type":"SEMVER","events":[{"introduced":"0"},{"fixed":"3.11.1"}]}]
pip mlflow
[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"3.10.0"}]}]
PyPI mlflow
[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"3.10.0"}]}]

References

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