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CVE-2026-0596
high
CVSS 7.8
OS Command Injection in mlflow (CVE-2026-0596)
Summary
OS command injection in mlflow (CVE-2026-0596). Successful exploitation can lead to full system takeover. Exploitable via ``model_uri``. Mitigation: upgrade to `3.9.0` or later.
AI summary snake-internal / snake-material-v2
A vulnerability tracked as **CVE-2026-0596** has been found in mlflow.
Attackers can target a specific entry point like ``model_uri`` over the network to misuse the product.
Successful exploitation can lead to full system takeover. CVSS score: 7.8/10.
What to do: upgrade mlflow to **3.9.0** or later.
If unsure, ask your IT team or search "mlflow CVE-2026-0596" on the vendor's site.
CVE-2026-0596 (mlflow) — CWE-78 / CVSS v3 7.8
Attack vector: adjacent-network / unauthenticated / no user interaction
Attack surface: `model_uri`
Patched: `3.9.0` — 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
**OS command injection** (CWE-78) exists in mlflow. Attackers reach the vulnerable code path via ``model_uri`` without authentication.
📍 Affected scope
mlflow — . Attack surface: `model_uri`.
🔥 Severity
Severity: High (CVSS 7.8/10). Successful exploitation can lead to full system takeover
🔧 How to fix
Update to **3.9.0**.
🛡️ 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
-
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。
-
6Apply patch patch
Upgrade mlflow to 3.9.0ステージング環境で 3.9.0 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。
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7Post-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
pip
mlflow
[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"3.9.0"}]}]
PyPI
mlflow
[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"3.9.0"}]}]
Bitnami
mlflow
[{"type":"SEMVER","events":[{"introduced":"0"},{"fixed":"3.11.1"}]}]
References
- advisory https://nvd.nist.gov/vuln/detail/CVE-2026-0596
- advisory https://github.com/advisories/GHSA-rvhj-8chj-8v3c
- package https://github.com/mlflow/mlflow
- package https://pypi.org/project/mlflow
- web https://huntr.com/bounties/2e905add-f9f5-4309-a3db-b17de5981285
- web https://github.com/mlflow/mlflow/pull/19738
- web https://github.com/mlflow/mlflow/commit/202fac4c83ccc8544c087c142b80196d0e60695c