Vulnerability-Lookup

PYSEC-2026-423

Vulnerability from pysec - Published: 2026-06-29 11:50 - Updated: 2026-07-01 20:22

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

Impacted products

Name	purl
mlflow	pkg:pypi/mlflow

Aliases

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "mlflow",
        "purl": "pkg:pypi/mlflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "3.8.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "0.0.1",
        "0.1.0",
        "0.2.0",
        "0.2.1",
        "0.3.0",
        "0.4.0",
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        "0.7.0",
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        "0.8.2",
        "0.9.0",
        "0.9.0.1",
        "0.9.1",
        "1.0.0",
        "1.1.0",
        "1.1.1.dev0",
        "1.10.0",
        "1.11.0",
        "1.12.0",
        "1.12.1",
        "1.13",
        "1.13.1",
        "1.14.0",
        "1.14.1",
        "1.15.0",
        "1.16.0",
        "1.17.0",
        "1.18.0",
        "1.19.0",
        "1.2.0",
        "1.20.0",
        "1.20.1",
        "1.20.2",
        "1.21.0",
        "1.22.0",
        "1.23.0",
        "1.23.1",
        "1.24.0",
        "1.25.0",
        "1.25.1",
        "1.26.0",
        "1.26.1",
        "1.27.0",
        "1.28.0",
        "1.29.0",
        "1.3.0",
        "1.30.0",
        "1.30.1",
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        "1.7.0",
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        "1.8.0",
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        "2.0.0rc0",
        "2.0.1",
        "2.1.0",
        "2.1.1",
        "2.10.0",
        "2.10.1",
        "2.10.2",
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        "2.11.1",
        "2.11.2",
        "2.11.3",
        "2.11.4",
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        "2.12.1",
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      ]
    }
  ],
  "aliases": [
    "CVE-2025-15379",
    "GHSA-r23q-823p-vmf7"
  ],
  "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": "PYSEC-2026-423",
  "modified": "2026-07-01T20:22:58.350388Z",
  "published": "2026-06-29T11:50:45.390530Z",
  "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"
    },
    {
      "type": "PACKAGE",
      "url": "https://pypi.org/project/mlflow"
    },
    {
      "type": "ADVISORY",
      "url": "https://github.com/advisories/GHSA-r23q-823p-vmf7"
    }
  ],
  "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"
}

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

Vulnerability from cvelistv5 – Published: 2026-03-30 07:16 – Updated: 2026-06-30 12:07

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

9 (Critical)


                        
                          CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:C/C:H/I:H/A:H

SSVC

Exploitation: poc Automatable: yes Technical Impact: total

CISA Coordinator (v2.0.3)

CWE

CWE-77 - Improper Neutralization of Special Elements used in a Command ('Command Injection')
CWE-78 - Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')

Assigner

@huntr_ai

References

5 references

URL	Tags
https://huntr.com/bounties/dc9c1c20-7879-4050-87d…
https://github.com/mlflow/mlflow/commit/361b6f620…
https://access.redhat.com/security/cve/CVE-2025-15379	vdb-entryx_refsource_REDHAT
https://bugzilla.redhat.com/show_bug.cgi?id=2452949	issue-trackingx_refsource_REDHAT
https://security.access.redhat.com/data/csaf/v2/v…	x_sadp-csaf-vex

Impacted products

2 products

Vendor	Product	Version
mlflow	mlflow/mlflow	Affected: unspecified , < 3.8.2 (custom)
Red Hat	Red Hat OpenShift AI (RHOAI)	cpe:/a:redhat:openshift_ai

Show details on NVD website

JSON

To clipboard

{
  "containers": {
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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

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	Other

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

PYSEC-2026-423

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

GHSA-R23Q-823P-VMF7

Tags

Sightings

Nomenclature