FKIE_CVE-2025-15031

Vulnerability from fkie_nvd - Published: 2026-03-18 23:17 - Updated: 2026-07-15 02:17
Summary
A vulnerability in MLflow's pyfunc extraction process allows for arbitrary file writes due to improper handling of tar archive entries. Specifically, the use of `tarfile.extractall` without path validation enables crafted tar.gz files containing `..` or absolute paths to escape the intended extraction directory. This issue affects the latest version of MLflow and poses a high/critical risk in scenarios involving multi-tenant environments or ingestion of untrusted artifacts, as it can lead to arbitrary file overwrites and potential remote code execution.
Impacted products
Vendor Product Version
lfprojects mlflow *

{
  "affected": [
    {
      "affectedData": [
        {
          "product": "mlflow/mlflow",
          "vendor": "mlflow",
          "versions": [
            {
              "lessThanOrEqual": "latest",
              "status": "affected",
              "version": "unspecified",
              "versionType": "custom"
            }
          ]
        }
      ],
      "source": "security@huntr.dev"
    },
    {
      "affectedData": [
        {
          "collectionURL": "https://access.redhat.com/downloads/content/package-browser/",
          "cpes": [
            "cpe:/a:redhat:openshift_ai"
          ],
          "defaultStatus": "affected",
          "packageName": "rhoai/odh-mlflow-rhel9",
          "product": "Red Hat OpenShift AI (RHOAI)",
          "vendor": "Red Hat"
        }
      ],
      "source": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c"
    }
  ],
  "configurations": [
    {
      "nodes": [
        {
          "cpeMatch": [
            {
              "criteria": "cpe:2.3:a:lfprojects:mlflow:*:*:*:*:*:*:*:*",
              "matchCriteriaId": "C1C49CD5-5BB0-422B-9A71-5A6832DF6713",
              "versionEndIncluding": "3.10.1",
              "vulnerable": true
            }
          ],
          "negate": false,
          "operator": "OR"
        }
      ]
    }
  ],
  "cveTags": [],
  "descriptions": [
    {
      "lang": "en",
      "value": "A vulnerability in MLflow\u0027s pyfunc extraction process allows for arbitrary file writes due to improper handling of tar archive entries. Specifically, the use of `tarfile.extractall` without path validation enables crafted tar.gz files containing `..` or absolute paths to escape the intended extraction directory. This issue affects the latest version of MLflow and poses a high/critical risk in scenarios involving multi-tenant environments or ingestion of untrusted artifacts, as it can lead to arbitrary file overwrites and potential remote code execution."
    },
    {
      "lang": "es",
      "value": "Una vulnerabilidad en el proceso de extracci\u00f3n pyfunc de MLflow permite escrituras arbitrarias de archivos debido a un manejo inadecuado de las entradas de archivos tar. Espec\u00edficamente, el uso de \u0027tarfile.extractall\u0027 sin validaci\u00f3n de ruta permite que archivos tar.gz manipulados que contienen \u0027..\u0027 o rutas absolutas escapen del directorio de extracci\u00f3n previsto. Este problema afecta a la \u00faltima versi\u00f3n de MLflow y plantea un riesgo alto/cr\u00edtico en escenarios que involucran entornos multi-inquilino o la ingesta de artefactos no confiables, ya que puede conducir a sobrescrituras arbitrarias de archivos y potencial ejecuci\u00f3n remota de c\u00f3digo."
    }
  ],
  "id": "CVE-2025-15031",
  "lastModified": "2026-07-15T02:17:19.360",
  "metrics": {
    "cvssMetricV30": [
      {
        "cvssData": {
          "attackComplexity": "LOW",
          "attackVector": "ADJACENT_NETWORK",
          "availabilityImpact": "NONE",
          "baseScore": 8.1,
          "baseSeverity": "HIGH",
          "confidentialityImpact": "HIGH",
          "integrityImpact": "HIGH",
          "privilegesRequired": "NONE",
          "scope": "UNCHANGED",
          "userInteraction": "NONE",
          "vectorString": "CVSS:3.0/AV:A/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:N",
          "version": "3.0"
        },
        "exploitabilityScore": 2.8,
        "impactScore": 5.2,
        "source": "security@huntr.dev",
        "type": "Secondary"
      }
    ],
    "cvssMetricV31": [
      {
        "cvssData": {
          "attackComplexity": "LOW",
          "attackVector": "NETWORK",
          "availabilityImpact": "NONE",
          "baseScore": 9.1,
          "baseSeverity": "CRITICAL",
          "confidentialityImpact": "HIGH",
          "integrityImpact": "HIGH",
          "privilegesRequired": "NONE",
          "scope": "UNCHANGED",
          "userInteraction": "NONE",
          "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:N",
          "version": "3.1"
        },
        "exploitabilityScore": 3.9,
        "impactScore": 5.2,
        "source": "nvd@nist.gov",
        "type": "Primary"
      },
      {
        "cvssData": {
          "attackComplexity": "LOW",
          "attackVector": "ADJACENT_NETWORK",
          "availabilityImpact": "NONE",
          "baseScore": 8.1,
          "baseSeverity": "HIGH",
          "confidentialityImpact": "HIGH",
          "integrityImpact": "HIGH",
          "privilegesRequired": "NONE",
          "scope": "UNCHANGED",
          "userInteraction": "NONE",
          "vectorString": "CVSS:3.1/AV:A/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:N",
          "version": "3.1"
        },
        "exploitabilityScore": 2.8,
        "impactScore": 5.2,
        "source": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c",
        "type": "Secondary"
      }
    ],
    "ssvcV203": [
      {
        "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
        "ssvcData": {
          "id": "CVE-2025-15031",
          "options": [
            {
              "exploitation": "poc"
            },
            {
              "automatable": "no"
            },
            {
              "technicalImpact": "total"
            }
          ],
          "role": "CISA Coordinator",
          "timestamp": "2026-03-19T13:52:23.186232Z",
          "version": "2.0.3"
        }
      }
    ]
  },
  "published": "2026-03-18T23:17:28.693",
  "references": [
    {
      "source": "security@huntr.dev",
      "tags": [
        "Exploit",
        "Mitigation",
        "Third Party Advisory"
      ],
      "url": "https://huntr.com/bounties/09856f77-f968-446f-a930-657d126efe4e"
    },
    {
      "source": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c",
      "url": "https://access.redhat.com/security/cve/CVE-2025-15031"
    },
    {
      "source": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c",
      "url": "https://bugzilla.redhat.com/show_bug.cgi?id=2448912"
    },
    {
      "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
      "tags": [
        "Exploit",
        "Mitigation",
        "Third Party Advisory"
      ],
      "url": "https://huntr.com/bounties/09856f77-f968-446f-a930-657d126efe4e"
    },
    {
      "source": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c",
      "url": "https://security.access.redhat.com/data/csaf/v2/vex/2025/cve-2025-15031.json"
    }
  ],
  "sourceIdentifier": "security@huntr.dev",
  "vulnStatus": "Modified",
  "weaknesses": [
    {
      "description": [
        {
          "lang": "en",
          "value": "CWE-22"
        }
      ],
      "source": "security@huntr.dev",
      "type": "Secondary"
    },
    {
      "description": [
        {
          "lang": "en",
          "value": "CWE-22"
        }
      ],
      "source": "0b0ca135-0b70-47e7-9f44-1890c2a1c46c",
      "type": "Secondary"
    }
  ]
}



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Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.

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