Vulnerability-Lookup

CVE-2025-15379 (GCVE-0-2025-15379)

Vulnerability from cvelistv5 – Published: 2026-03-30 07:16 – Updated: 2026-03-31 13:50

Title

Command Injection in mlflow/mlflow

Summary

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 ?

10 (Critical)


                        
                          CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H

CWE

CWE-77 - Improper Neutralization of Special Elements used in a Command ('Command Injection')

Assigner

@huntr_ai

References

URL

Tags

	https://huntr.com/bounties/dc9c1c20-7879-4050-87d…
	https://github.com/mlflow/mlflow/commit/361b6f620…

Impacted products

	Vendor	Product	Version
	mlflow	mlflow/mlflow	Affected: unspecified , < 3.8.2 (custom)

Show details on NVD website

JSON

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FKIE_CVE-2025-15379

Vulnerability from fkie_nvd - Published: 2026-03-30 08:16 - Updated: 2026-03-30 13:26

Severity ?

10.0 (Critical) - CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H

Summary

References

	URL	Tags
	security@huntr.dev	https://github.com/mlflow/mlflow/commit/361b6f620adf98385c6721e384fb5ef9a30bb05e
	security@huntr.dev	https://huntr.com/bounties/dc9c1c20-7879-4050-87df-4d095fe5ca75

Impacted products

	Vendor	Product	Version

JSON

To clipboard

{
  "cveTags": [],
  "descriptions": [
    {
      "lang": "en",
      "value": "A command injection vulnerability exists in MLflow\u0027s 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\u0027s `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."
    },
    {
      "lang": "es",
      "value": "Existe una vulnerabilidad de inyecci\u00f3n de comandos en el c\u00f3digo de inicializaci\u00f3n del contenedor de servicio de modelos de MLflow, espec\u00edficamente en la funci\u00f3n `_install_model_dependencies_to_env()`. Al desplegar un modelo con `env_manager=LOCAL`, MLflow lee las especificaciones de dependencia del archivo `python_env.yaml` del artefacto del modelo y las interpola directamente en un comando de shell sin sanitizaci\u00f3n. Esto permite a un atacante suministrar un artefacto de modelo malicioso y lograr la ejecuci\u00f3n arbitraria de comandos en sistemas que despliegan el modelo. La vulnerabilidad afecta a las versiones 3.8.0 y est\u00e1 corregida en la versi\u00f3n 3.8.2."
    }
  ],
  "id": "CVE-2025-15379",
  "lastModified": "2026-03-30T13:26:07.647",
  "metrics": {
    "cvssMetricV30": [
      {
        "cvssData": {
          "attackComplexity": "LOW",
          "attackVector": "NETWORK",
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GHSA-R23Q-823P-VMF7

Vulnerability from github – Published: 2026-03-30 09:31 – Updated: 2026-04-01 19:08

Summary

MLflow Command Injection vulnerability

Details

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 3.8.1.

Severity ?

10.0 (Critical)


                  
                    CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H

Show details on source website

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "mlflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "3.8.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2025-15379"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-77"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-04-01T00:08:33Z",
    "nvd_published_at": "2026-03-30T08:16:15Z",
    "severity": "CRITICAL"
  },
  "details": "A command injection vulnerability exists in MLflow\u0027s 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\u0027s `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 3.8.1.",
  "id": "GHSA-r23q-823p-vmf7",
  "modified": "2026-04-01T19:08:35Z",
  "published": "2026-03-30T09:31:28Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-15379"
    },
    {
      "type": "WEB",
      "url": "https://github.com/mlflow/mlflow/commit/361b6f620adf98385c6721e384fb5ef9a30bb05e"
    },
    {
      "type": "WEB",
      "url": "https://github.com/mlflow/mlflow/commit/a22ce7157f646bdce4c95106fc38ccc9ca289205"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/mlflow/mlflow"
    },
    {
      "type": "WEB",
      "url": "https://huntr.com/bounties/dc9c1c20-7879-4050-87df-4d095fe5ca75"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "MLflow Command Injection vulnerability"
}

Sightings

Author	Source	Type	Date

Nomenclature

Seen: The vulnerability was mentioned, discussed, or observed by the user.
Confirmed: The vulnerability has been validated from an analyst's perspective.
Published Proof of Concept: A public proof of concept is available for this vulnerability.
Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
Not confirmed: The user expressed doubt about the validity of the vulnerability.
Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.

Detection rules are retrieved from Rulezet.

Action not permitted

CVE-2025-15379 (GCVE-0-2025-15379)

FKIE_CVE-2025-15379

GHSA-R23Q-823P-VMF7

Tags

Sightings

Nomenclature