Categories
CVE-2025-14287 high CVSS 8.8

Code Injection in Lfprojects (CVE-2025-14287)

Summary

Code injection in Lfprojects (CVE-2025-14287). Successful exploitation can lead to full system takeover.

Original description

The description as published by the source.

A command injection vulnerability exists in mlflow/mlflow versions before v3.7.0, specifically in the mlflow/sagemaker/__init__.py file at lines 161-167. The vulnerability arises from the direct interpolation of user-supplied container image names into shell commands without proper sanitization, which are then executed using os.system(). This allows attackers to execute arbitrary commands by supplying malicious input through the --container parameter of the CLI. The issue affects environments where MLflow is used, including development setups, CI/CD pipelines, and cloud deployments.

Source: NIST National Vulnerability Database 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-2025-14287 has been found in Lfprojects.
Successful exploitation can lead to full system takeover. CVSS score: 8.8/10.
What to do: apply the vendor's official patched release.
If unsure, ask your IT team or search "Lfprojects CVE-2025-14287" on the vendor's site.

CVE-2025-14287 (Lfprojects) — CWE-94 / CVSS v3 8.8
Attack vector: remote (network-reachable) / unauthenticated
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

Arbitrary code execution (CWE-94) exists in Lfprojects.

📍 Affected scope

Check the vendor advisory for the affected versions of Lfprojects.

🔥 Severity

Severity: High (CVSS 8.8/10). Successful exploitation can lead to full system takeover.

🔧 How to fix

Update to the patched release per vendor advisory.

🛡️ 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 'Lfprojects' . 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 'Lfprojects' . | 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 Lfprojects 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
    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":"3.7.0"}]}]

References

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