FKIE_CVE-2024-24591

Vulnerability from fkie_nvd - Published: 2024-02-06 15:15 - Updated: 2026-06-17 07:14
Severity
8.0 (High) - CVSS:3.1/AV:N/AC:L/PR:L/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
A path traversal vulnerability in versions 1.4.0 to 1.14.1 of the client SDK of Allegro AI’s ClearML platform enables a maliciously uploaded dataset to write local or remote files to an arbitrary location on an end user’s system when interacted with.
References
6f8de1f0-f67e-45a6-b68f-98777fdb759chttps://hiddenlayer.com/research/not-so-clear-how-mlops-solutions-can-muddy-the-waters-of-your-supply-chain/Exploit, Technical Description, Third Party Advisory
af854a3a-2127-422b-91ae-364da2661108https://hiddenlayer.com/research/not-so-clear-how-mlops-solutions-can-muddy-the-waters-of-your-supply-chain/Exploit, Technical Description, Third Party Advisory
Impacted products
Vendor Product Version
clear clearml *
To clipboard 

{
  "affected": [
    {
      "affectedData": [
        {
          "defaultStatus": "unaffected",
          "packageName": "clearml",
          "product": "ClearML",
          "repo": "https://github.com/allegroai/clearml",
          "vendor": "Allegro.AI",
          "versions": [
            {
              "lessThan": "1.14.2",
              "status": "affected",
              "version": "1.4.0",
              "versionType": "custom"
            }
          ]
        }
      ],
      "source": "6f8de1f0-f67e-45a6-b68f-98777fdb759c"
    }
  ],
  "configurations": [
    {
      "nodes": [
        {
          "cpeMatch": [
            {
              "criteria": "cpe:2.3:a:clear:clearml:*:*:*:*:*:*:*:*",
              "matchCriteriaId": "8D066706-293A-46C9-BF61-DA1BA1A79E7C",
              "versionEndIncluding": "1.14.1",
              "versionStartIncluding": "1.4.0",
              "vulnerable": true
            }
          ],
          "negate": false,
          "operator": "OR"
        }
      ]
    }
  ],
  "cveTags": [],
  "descriptions": [
    {
      "lang": "en",
      "value": "A path traversal vulnerability in versions 1.4.0 to 1.14.1 of the client SDK of Allegro AI\u2019s ClearML platform enables a maliciously uploaded dataset to write local or remote files to an arbitrary location on an end user\u2019s system when interacted with.\n"
    },
    {
      "lang": "es",
      "value": "Vulnerabilidad de path traversal en la versi\u00f3n 1.4.0 o posterior de la plataforma ClearML de Allegro AI, permite que un conjunto de datos cargado maliciosamente escriba archivos locales o remotos en una ubicaci\u00f3n arbitraria en el sistema de un usuario final cuando interact\u00faa con \u00e9l."
    }
  ],
  "id": "CVE-2024-24591",
  "lastModified": "2026-06-17T07:14:39.733",
  "metrics": {
    "cvssMetricV31": [
      {
        "cvssData": {
          "attackComplexity": "LOW",
          "attackVector": "NETWORK",
          "availabilityImpact": "HIGH",
          "baseScore": 8.0,
          "baseSeverity": "HIGH",
          "confidentialityImpact": "HIGH",
          "integrityImpact": "HIGH",
          "privilegesRequired": "LOW",
          "scope": "UNCHANGED",
          "userInteraction": "REQUIRED",
          "vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:R/S:U/C:H/I:H/A:H",
          "version": "3.1"
        },
        "exploitabilityScore": 2.1,
        "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-2024-24591",
          "options": [
            {
              "exploitation": "poc"
            },
            {
              "automatable": "no"
            },
            {
              "technicalImpact": "total"
            }
          ],
          "role": "CISA Coordinator",
          "timestamp": "2025-05-08T15:35:43.174246Z",
          "version": "2.0.3"
        }
      }
    ]
  },
  "published": "2024-02-06T15:15:09.367",
  "references": [
    {
      "source": "6f8de1f0-f67e-45a6-b68f-98777fdb759c",
      "tags": [
        "Exploit",
        "Technical Description",
        "Third Party Advisory"
      ],
      "url": "https://hiddenlayer.com/research/not-so-clear-how-mlops-solutions-can-muddy-the-waters-of-your-supply-chain/"
    },
    {
      "source": "af854a3a-2127-422b-91ae-364da2661108",
      "tags": [
        "Exploit",
        "Technical Description",
        "Third Party Advisory"
      ],
      "url": "https://hiddenlayer.com/research/not-so-clear-how-mlops-solutions-can-muddy-the-waters-of-your-supply-chain/"
    }
  ],
  "sourceIdentifier": "6f8de1f0-f67e-45a6-b68f-98777fdb759c",
  "vulnStatus": "Modified",
  "weaknesses": [
    {
      "description": [
        {
          "lang": "en",
          "value": "CWE-22"
        }
      ],
      "source": "6f8de1f0-f67e-45a6-b68f-98777fdb759c",
      "type": "Secondary"
    },
    {
      "description": [
        {
          "lang": "en",
          "value": "CWE-22"
        }
      ],
      "source": "nvd@nist.gov",
      "type": "Primary"
    }
  ]
}



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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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  • Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.



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Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.