A command injection vulnerability exists in MLflow's model serving container initialization code, specifically in the _install_model_dependencies_to_env() function. When deploying a model with env_manager=LOCAL, MLflow reads dependency specifications from the model artifact's python_env.yaml file and directly interpolates them into a shell command without sanitization. This allows an attacker to supply a malicious model artifact and achieve arbitrary command execution on systems that deploy the model. The vulnerability affects versions 3.8.0 and is fixed in version 3.8.2.
CVE-2025-15379
This critical-severity CVE scores 9.8 under NVD CVSS v3. EPSS exploit probability: 2.0%, top 21% of all CVEs by exploit prediction. GitHub Security Advisory data not yet ingested — confidence will rise once GHSA publishes (typical lag: hours to days for open-source ecosystem CVEs; never for infrastructure-only CVEs).
- High severity, but no confirmed exploitation yet
No vendor fix yet — apply a workaround or compensating control (WAF / firewall / segmentation) and watch for a patch.
- CVSS v3
- 9.8
- EG Score
- 9.8(medium)
- EG Risk
- 75(Attend)EG Risk 75/100SSVC: Attend
EG Risk is EchelonGraph's 0–100 priority score: it fuses intrinsic severity with real-world exploitation and automatability so you can rank equal-severity CVEs and fix the most dangerous first. Higher = act sooner. Distinct from the 0–10 EG Score (severity).
How it’s computedSeverity98% × 45%Exploitation40% × 40%Automatability100% × 15%Action: Remediate soon — notable exploitation risk. - EPSS
- 78.6%
- KEV
- Not listed
Published
March 30, 2026
Last Modified
July 15, 2026
Advisory Details (5)
Auto-updated Jul 16, 20262452949 – (CVE-2025-15379) CVE-2025-15379 mlflow: MLflow: Arbitrary command execution via command injection in model serving container initialization.
https://bugzilla.redhat.com/show_bug.cgi?id=2452949huntr - The world's first bug bounty platform for AI/ML
https://huntr.com/bounties/dc9c1c20-7879-4050-87df-4d095fe5ca75commit 361b6f620adf (mlflow/mlflow)
Fix landed in mlflow/mlflow commit 361b6f620adf — awaiting tagged release
https://github.com/mlflow/mlflow/commit/361b6f620adf98385c6721e384fb5ef9a30bb05eAffected Packages
(1 across 1 ecosystem)
PyPI(1)
| Package | Vulnerable range | Fixed in | Dependents |
|---|---|---|---|
| mlflow | 0.0.1 ... 3.8.0rc0 (166 versions) | 3.8.1 | — |
Weakness Classification(2)
MITRE Common Weakness Enumeration — the root-cause categories this CVE belongs to.
Data Freshness Timeline
(refreshed 12× in last 7d / 46× in last 30d)
Each row is a source pipeline that fetched or updated this CVE on that date, with what changed. For example, "NVD update" means NVD published or revised its analysis for this CVE; "MITRE cvelistV5" means we ingested or refreshed it from the CNA feed. Most recent first.
Showing the most recent 100 of 118 total refreshes for this CVE.
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- 2026-07-15 02:22 UTCNVD updateCVSS v3 → 9.8
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Related CVEs(same CWE)
Same CWE
10 shownCWE-78 · CWE-77
- CVE-2009-20011EG 10.0CRITICAL
- CVE-2011-10017EG 10.0CRITICAL
- CVE-2011-10026EG 9.8CRITICAL
- CVE-2011-2195EG 9.8CRITICAL
- CVE-2011-2523EG 9.8EPSS 100%CRITICAL
- CVE-2010-5330EG 9.8 KEVEPSS 98%CRITICAL
- CVE-2009-5156EG 9.8EPSS 95%CRITICAL
- CVE-2007-3010EG 9.8 KEVEPSS 100%CRITICAL
- CVE-2005-2773EG 9.8 KEVEPSS 99%CRITICAL
- CVE-1999-0043EG 9.8EPSS 99%CRITICAL
Frequently asked(5)
What is CVE-2025-15379?
When was CVE-2025-15379 disclosed?
Is CVE-2025-15379 actively exploited?
What is the CVSS score of CVE-2025-15379?
How do I remediate CVE-2025-15379?
Dependency Blast Radius
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