CVE intelligence and bounded remediation
CVE-2025-15379 — Lfprojects Mlflow security vulnerability
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.
- Severity
- Critical
- CVSS
- 10 (3.0)
- Published
- 2026-03-30
- CISA KEV
- Not currently listed
- Ecosystem
- python/pypi
- Weaknesses
- CWE-77, CWE-78
Affected products
- lfprojects / mlflow
Matched remediation archetype
Command, code, expression, and template injection
This catalog composition supplies bounded fallback guidance. Explicitly reviewed curated workflows load with the complete record below.
Check exposure
- Trace untrusted values to process execution, interpreters, evaluators, template engines, dynamic imports, and administrative scripting features.
- Determine whether the affected path is reachable across each trust boundary and which service account or host privilege it inherits.
- Review configuration for optional execution features, unsafe compatibility modes, and shell invocation.
Remediate safely
- Replace string-built commands or evaluated code with fixed operations and structured argument APIs that do not invoke a shell.
- Use strict allowlists for operation identifiers and reject unexpected input before it reaches any interpreter.
- Update the affected component and add inert regression tests covering metacharacters, encoding variants, and alternate request paths.
Authoritative sources
Complete CVE record and remediation plan
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