FKIE_CVE-2024-37054

Vulnerability from fkie_nvd - Published: 2024-06-04 12:15 - Updated: 2026-06-17 07:37
Severity
8.8 (High) - CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
8.8 (High) - CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
Summary
Deserialization of untrusted data can occur in versions of the MLflow platform running version 0.9.0 or newer, enabling a maliciously uploaded PyFunc model to run arbitrary code on an end user’s system when interacted with.
References
6f8de1f0-f67e-45a6-b68f-98777fdb759chttps://hiddenlayer.com/sai-security-advisory/mlflow-june2024Exploit, Third Party Advisory
af854a3a-2127-422b-91ae-364da2661108https://hiddenlayer.com/sai-security-advisory/mlflow-june2024Exploit, Third Party Advisory
Impacted products
Vendor Product Version
lfprojects mlflow *
To clipboard 

{
  "affected": [
    {
      "affectedData": [
        {
          "defaultStatus": "unaffected",
          "packageName": "mlflow",
          "product": "MLflow",
          "repo": "https://github.com/mlflow/mlflow",
          "vendor": "MLflow",
          "versions": [
            {
              "lessThanOrEqual": "*",
              "status": "affected",
              "version": "0.9.0",
              "versionType": "semver"
            }
          ]
        }
      ],
      "source": "6f8de1f0-f67e-45a6-b68f-98777fdb759c"
    },
    {
      "affectedData": [
        {
          "cpes": [
            "cpe:2.3:a:lfprojects:mlflow:0.9.0:*:*:*:*:*:*:*"
          ],
          "defaultStatus": "unknown",
          "product": "mlflow",
          "vendor": "lfprojects",
          "versions": [
            {
              "lessThanOrEqual": "*",
              "status": "affected",
              "version": "0.9.0",
              "versionType": "custom"
            }
          ]
        }
      ],
      "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0"
    }
  ],
  "configurations": [
    {
      "nodes": [
        {
          "cpeMatch": [
            {
              "criteria": "cpe:2.3:a:lfprojects:mlflow:*:*:*:*:*:*:*:*",
              "matchCriteriaId": "E10BF8AE-F58F-44F2-9BDB-B74DD0B9F651",
              "versionStartIncluding": "0.9.0",
              "vulnerable": true
            }
          ],
          "negate": false,
          "operator": "OR"
        }
      ]
    }
  ],
  "cveTags": [],
  "descriptions": [
    {
      "lang": "en",
      "value": "Deserialization of untrusted data can occur in versions of the MLflow platform running version 0.9.0 or newer, enabling a maliciously uploaded PyFunc model to run arbitrary code on an end user\u2019s system when interacted with."
    },
    {
      "lang": "es",
      "value": "La deserializaci\u00f3n de datos que no son de confianza puede ocurrir en versiones de la plataforma MLflow que ejecutan la versi\u00f3n 0.9.0 o posterior, lo que permite que un modelo PyFunc cargado maliciosamente ejecute c\u00f3digo arbitrario en el sistema de un usuario final cuando interact\u00faa con \u00e9l."
    }
  ],
  "id": "CVE-2024-37054",
  "lastModified": "2026-06-17T07:37:41.117",
  "metrics": {
    "cvssMetricV31": [
      {
        "cvssData": {
          "attackComplexity": "LOW",
          "attackVector": "NETWORK",
          "availabilityImpact": "HIGH",
          "baseScore": 8.8,
          "baseSeverity": "HIGH",
          "confidentialityImpact": "HIGH",
          "integrityImpact": "HIGH",
          "privilegesRequired": "NONE",
          "scope": "UNCHANGED",
          "userInteraction": "REQUIRED",
          "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
          "version": "3.1"
        },
        "exploitabilityScore": 2.8,
        "impactScore": 5.9,
        "source": "6f8de1f0-f67e-45a6-b68f-98777fdb759c",
        "type": "Secondary"
      },
      {
        "cvssData": {
          "attackComplexity": "LOW",
          "attackVector": "NETWORK",
          "availabilityImpact": "HIGH",
          "baseScore": 8.8,
          "baseSeverity": "HIGH",
          "confidentialityImpact": "HIGH",
          "integrityImpact": "HIGH",
          "privilegesRequired": "NONE",
          "scope": "UNCHANGED",
          "userInteraction": "REQUIRED",
          "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H",
          "version": "3.1"
        },
        "exploitabilityScore": 2.8,
        "impactScore": 5.9,
        "source": "nvd@nist.gov",
        "type": "Primary"
      }
    ],
    "ssvcV203": [
      {
        "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
        "ssvcData": {
          "id": "CVE-2024-37054",
          "options": [
            {
              "exploitation": "none"
            },
            {
              "automatable": "no"
            },
            {
              "technicalImpact": "total"
            }
          ],
          "role": "CISA Coordinator",
          "timestamp": "2024-06-06T15:01:38.249209Z",
          "version": "2.0.3"
        }
      }
    ]
  },
  "published": "2024-06-04T12:15:11.190",
  "references": [
    {
      "source": "6f8de1f0-f67e-45a6-b68f-98777fdb759c",
      "tags": [
        "Exploit",
        "Third Party Advisory"
      ],
      "url": "https://hiddenlayer.com/sai-security-advisory/mlflow-june2024"
    },
    {
      "source": "af854a3a-2127-422b-91ae-364da2661108",
      "tags": [
        "Exploit",
        "Third Party Advisory"
      ],
      "url": "https://hiddenlayer.com/sai-security-advisory/mlflow-june2024"
    }
  ],
  "sourceIdentifier": "6f8de1f0-f67e-45a6-b68f-98777fdb759c",
  "vulnStatus": "Analyzed",
  "weaknesses": [
    {
      "description": [
        {
          "lang": "en",
          "value": "CWE-502"
        }
      ],
      "source": "6f8de1f0-f67e-45a6-b68f-98777fdb759c",
      "type": "Secondary"
    },
    {
      "description": [
        {
          "lang": "en",
          "value": "CWE-502"
        }
      ],
      "source": "nvd@nist.gov",
      "type": "Primary"
    }
  ]
}



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