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CVE-2025-15036 critical CVSS 10.0

Vulnerability in mlflow (CVE-2025-15036)

Summary

vulnerability in mlflow (CVE-2025-15036). Successful exploitation can lead to full system takeover. Exploitable via ``extract_archive_to_dir``. Mitigation: upgrade to `3.9.0rc0` or later.

AI summary snake-internal / snake-material-v2

A vulnerability tracked as **CVE-2025-15036** has been found in mlflow. Attackers can target a specific entry point like ``extract_archive_to_dir`` over the network to misuse the product. Successful exploitation can lead to full system takeover. CVSS score: 10.0/10. What to do: upgrade mlflow to **3.9.0rc0** or later. If unsure, ask your IT team or search "mlflow CVE-2025-15036" on the vendor's site.
CVE-2025-15036 (mlflow) — CWE-29 / CVSS v3 10.0 Attack vector: remote (network-reachable) / unauthenticated Attack surface: `extract_archive_to_dir` Patched: `3.9.0rc0` — 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.
❓ What is the problem
**A vulnerability** (CWE-29) exists in mlflow. Attackers reach the vulnerable code path via ``extract_archive_to_dir`` without authentication.
📍 Affected scope
mlflow — . Attack surface: `extract_archive_to_dir`.
🔥 Severity
Severity: Critical (CVSS 10.0/10). Successful exploitation can lead to full system takeover
🔧 How to fix
Update to **3.9.0rc0**.
🛡️ 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 (7 steps)

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. 6
    Apply patch patch 
    Upgrade mlflow to 3.9.0rc0

    ステージング環境で 3.9.0rc0 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と、Step 3 で見つけた異常検知の続報チェックを含めること。

  3. 7
    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 Step 3 と同じログクエリでアラート再発が無いか継続監視。

Affected packages

PyPI mlflow
[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"3.9.0rc0"}]}]
Bitnami mlflow
[{"type":"SEMVER","events":[{"introduced":"0"},{"fixed":"3.9.0"}]}]

References

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