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CVE-2024-1560
Path Traversal in mlflow (CVE-2024-1560)
Summary
path traversal in mlflow (CVE-2024-1560). Data can be tampered with by attackers. Exploitable via ``_delete_artifact_mlflow_artifacts``. Mitigation: upgrade to `2.12.2` or later.
AI summary snake-internal / snake-material-v2
A vulnerability tracked as **CVE-2024-1560** has been found in mlflow.
Attackers can target a specific entry point like ``_delete_artifact_mlflow_artifacts`` over the network to misuse the product.
Data can be tampered with by attackers. CVSS score: ?/10.
What to do: upgrade mlflow to **2.12.2** or later.
If unsure, ask your IT team or search "mlflow CVE-2024-1560" on the vendor's site.
CVE-2024-1560 (mlflow) — CWE-22 /
Attack vector: remote (network-reachable) / no user interaction
Attack surface: `_delete_artifact_mlflow_artifacts` / `local_file_uri_to_path` / `delete_artifacts` / `local_artifact_repo.py`
Patched: `2.12.2` — 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
**Path traversal** (CWE-22) exists in mlflow. Attackers reach the vulnerable code path via ``_delete_artifact_mlflow_artifacts`` without authentication.
📍 Affected scope
mlflow — . Attack surface: `_delete_artifact_mlflow_artifacts` / `local_file_uri_to_path` / `delete_artifacts` / `local_artifact_repo.py`.
🔥 Severity
Severity: ?. Data can be tampered with by attackers
🔧 How to fix
Update to **2.12.2**.
🛡️ 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
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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。
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6Apply patch patch
Upgrade mlflow to 2.12.2ステージング環境で 2.12.2 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
Bitnami
mlflow
[{"type":"SEMVER","events":[{"introduced":"0"},{"fixed":"2.12.2"}]}]
PyPI
mlflow
[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"last_affected":"2.9.2"}]}]