Vulnerability-Lookup

CVE-2024-3099 (GCVE-0-2024-3099)

Vulnerability from cvelistv5 – Published: 2024-06-06 18:08 – Updated: 2024-08-01 19:32

Title

Denial of Service and Data Model Poisoning via URL Encoding in mlflow/mlflow

Summary

A vulnerability in mlflow/mlflow version 2.11.1 allows attackers to create multiple models with the same name by exploiting URL encoding. This flaw can lead to Denial of Service (DoS) as an authenticated user might not be able to use the intended model, as it will open a different model each time. Additionally, an attacker can exploit this vulnerability to perform data model poisoning by creating a model with the same name, potentially causing an authenticated user to become a victim by using the poisoned model. The issue stems from inadequate validation of model names, allowing for the creation of models with URL-encoded names that are treated as distinct from their URL-decoded counterparts.

Severity

5.4 (Medium)


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

SSVC

Exploitation: poc Automatable: no Technical Impact: partial

CISA Coordinator · CISA-ADP (v2.0.3)

Decision recorded 2024-06-07 12:51 UTC

CWE

CWE-475 - Undefined Behavior for Input to API

Assigner

@huntr_ai mitre root

References

1 reference

URL	Tags
https://huntr.com/bounties/8d96374a-ce8d-480e-9cb…

Impacted products

2 products

Vendor	Product	Version
mlflow	mlflow/mlflow	Affected: unspecified , ≤ latest (custom)
lfprojects	mlflow	Affected: 2.11.1 cpe:2.3:a:lfprojects:mlflow:2.11.1:::::::*

Show details on NVD website

JSON

To clipboard

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          {
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FKIE_CVE-2024-3099

Vulnerability from fkie_nvd - Published: 2024-06-06 19:15 - Updated: 2026-06-17 07:43

Severity

5.4 (Medium) - CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:L

Summary

References

	URL	Tags
	security@huntr.dev	https://huntr.com/bounties/8d96374a-ce8d-480e-9cb0-0a7e5165c24a	Exploit, Issue Tracking, Third Party Advisory
	af854a3a-2127-422b-91ae-364da2661108	https://huntr.com/bounties/8d96374a-ce8d-480e-9cb0-0a7e5165c24a	Exploit, Issue Tracking, Third Party Advisory

Impacted products

	Vendor	Product	Version
	lfprojects	mlflow	-

JSON

To clipboard

{
  "affected": [
    {
      "affectedData": [
        {
          "product": "mlflow/mlflow",
          "vendor": "mlflow",
          "versions": [
            {
              "lessThanOrEqual": "latest",
              "status": "affected",
              "version": "unspecified",
              "versionType": "custom"
            }
          ]
        }
      ],
      "source": "security@huntr.dev"
    },
    {
      "affectedData": [
        {
          "cpes": [
            "cpe:2.3:a:lfprojects:mlflow:2.11.1:*:*:*:*:*:*:*"
          ],
          "defaultStatus": "unknown",
          "product": "mlflow",
          "vendor": "lfprojects",
          "versions": [
            {
              "status": "affected",
              "version": "2.11.1"
            }
          ]
        }
      ],
      "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0"
    }
  ],
  "configurations": [
    {
      "nodes": [
        {
          "cpeMatch": [
            {
              "criteria": "cpe:2.3:a:lfprojects:mlflow:-:*:*:*:*:*:*:*",
              "matchCriteriaId": "F18F1880-033C-4E18-913C-6C5356427ABB",
              "vulnerable": true
            }
          ],
          "negate": false,
          "operator": "OR"
        }
      ]
    }
  ],
  "cveTags": [],
  "descriptions": [
    {
      "lang": "en",
      "value": "A vulnerability in mlflow/mlflow version 2.11.1 allows attackers to create multiple models with the same name by exploiting URL encoding. This flaw can lead to Denial of Service (DoS) as an authenticated user might not be able to use the intended model, as it will open a different model each time. Additionally, an attacker can exploit this vulnerability to perform data model poisoning by creating a model with the same name, potentially causing an authenticated user to become a victim by using the poisoned model. The issue stems from inadequate validation of model names, allowing for the creation of models with URL-encoded names that are treated as distinct from their URL-decoded counterparts."
    },
    {
      "lang": "es",
      "value": "Una vulnerabilidad en mlflow/mlflow versi\u00f3n 2.11.1 permite a los atacantes crear m\u00faltiples modelos con el mismo nombre explotando la codificaci\u00f3n URL. Esta falla puede provocar una denegaci\u00f3n de servicio (DoS), ya que es posible que un usuario autenticado no pueda utilizar el modelo deseado, ya que abrir\u00e1 un modelo diferente cada vez. Adem\u00e1s, un atacante puede aprovechar esta vulnerabilidad para envenenar el modelo de datos creando un modelo con el mismo nombre, lo que podr\u00eda provocar que un usuario autenticado se convierta en v\u00edctima al utilizar el modelo envenenado. El problema surge de una validaci\u00f3n inadecuada de los nombres de los modelos, lo que permite la creaci\u00f3n de modelos con nombres codificados en URL que se tratan como distintos de sus hom\u00f3logos decodificados en URL."
    }
  ],
  "id": "CVE-2024-3099",
  "lastModified": "2026-06-17T07:43:18.473",
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          "confidentialityImpact": "NONE",
          "integrityImpact": "LOW",
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        "source": "security@huntr.dev",
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}

GHSA-8F8Q-Q2J7-7J2M

Vulnerability from github – Published: 2024-06-06 21:30 – Updated: 2024-10-11 16:31

Summary

Undefined Behavior in mlflow

Details

Severity

5.4 (Medium)


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

Show details on source website

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "mlflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.11.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2024-3099"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-475"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2024-06-06T22:38:43Z",
    "nvd_published_at": "2024-06-06T19:15:59Z",
    "severity": "MODERATE"
  },
  "details": "A vulnerability in mlflow/mlflow version 2.11.1 allows attackers to create multiple models with the same name by exploiting URL encoding. This flaw can lead to Denial of Service (DoS) as an authenticated user might not be able to use the intended model, as it will open a different model each time. Additionally, an attacker can exploit this vulnerability to perform data model poisoning by creating a model with the same name, potentially causing an authenticated user to become a victim by using the poisoned model. The issue stems from inadequate validation of model names, allowing for the creation of models with URL-encoded names that are treated as distinct from their URL-decoded counterparts.",
  "id": "GHSA-8f8q-q2j7-7j2m",
  "modified": "2024-10-11T16:31:58Z",
  "published": "2024-06-06T21:30:36Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2024-3099"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/mlflow/mlflow"
    },
    {
      "type": "WEB",
      "url": "https://huntr.com/bounties/8d96374a-ce8d-480e-9cb0-0a7e5165c24a"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:L",
      "type": "CVSS_V3"
    }
  ],
  "summary": "Undefined Behavior in mlflow"
}

GSD-2024-3099

Vulnerability from gsd - Updated: 2024-04-03 05:02

Details

** RESERVED ** This candidate has been reserved by an organization or individual that will use it when announcing a new security problem. When the candidate has been publicized, the details for this candidate will be provided.

Aliases

CVE-2024-3099

JSON

To clipboard

{
  "gsd": {
    "metadata": {
      "exploitCode": "unknown",
      "remediation": "unknown",
      "reportConfidence": "confirmed",
      "type": "vulnerability"
    },
    "osvSchema": {
      "aliases": [
        "CVE-2024-3099"
      ],
      "id": "GSD-2024-3099",
      "modified": "2024-04-03T05:02:29.885505Z",
      "schema_version": "1.4.0"
    }
  },
  "namespaces": {
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      },
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            "value": "** RESERVED ** This candidate has been reserved by an organization or individual that will use it when announcing a new security problem. When the candidate has been publicized, the details for this candidate will be provided."
          }
        ]
      }
    }
  }
}

PYSEC-2026-1645

Vulnerability from pysec - Published: 2026-07-07 11:45 - Updated: 2026-07-07 17:24

Details

Severity

5.4 (Medium)


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

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": "2.11.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "0.0.1",
        "0.1.0",
        "0.2.0",
        "0.2.1",
        "0.3.0",
        "0.4.0",
        "0.4.1",
        "0.4.2",
        "0.5.0",
        "0.5.1",
        "0.5.2",
        "0.6.0",
        "0.7.0",
        "0.8.0",
        "0.8.1",
        "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",
        "1.4.0",
        "1.5.0",
        "1.6.0",
        "1.7.0",
        "1.7.1",
        "1.7.2",
        "1.8.0",
        "1.9.0",
        "1.9.1",
        "2.0.0",
        "2.0.0rc0",
        "2.0.1",
        "2.1.0",
        "2.1.1",
        "2.10.0",
        "2.10.1",
        "2.10.2",
        "2.11.0",
        "2.11.1",
        "2.11.2",
        "2.2.0",
        "2.2.1",
        "2.2.2",
        "2.3.0",
        "2.3.1",
        "2.3.2",
        "2.4.0",
        "2.4.1",
        "2.4.2",
        "2.5.0",
        "2.6.0",
        "2.7.0",
        "2.7.1",
        "2.8.0",
        "2.8.1",
        "2.9.0",
        "2.9.1",
        "2.9.2"
      ]
    }
  ],
  "aliases": [
    "CVE-2024-3099",
    "GHSA-8f8q-q2j7-7j2m"
  ],
  "details": "A vulnerability in mlflow/mlflow version 2.11.1 allows attackers to create multiple models with the same name by exploiting URL encoding. This flaw can lead to Denial of Service (DoS) as an authenticated user might not be able to use the intended model, as it will open a different model each time. Additionally, an attacker can exploit this vulnerability to perform data model poisoning by creating a model with the same name, potentially causing an authenticated user to become a victim by using the poisoned model. The issue stems from inadequate validation of model names, allowing for the creation of models with URL-encoded names that are treated as distinct from their URL-decoded counterparts.",
  "id": "PYSEC-2026-1645",
  "modified": "2026-07-07T17:24:42.323174Z",
  "published": "2026-07-07T11:45:45.961654Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2024-3099"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/mlflow/mlflow"
    },
    {
      "type": "WEB",
      "url": "https://huntr.com/bounties/8d96374a-ce8d-480e-9cb0-0a7e5165c24a"
    },
    {
      "type": "PACKAGE",
      "url": "https://pypi.org/project/mlflow"
    },
    {
      "type": "ADVISORY",
      "url": "https://github.com/advisories/GHSA-8f8q-q2j7-7j2m"
    }
  ],
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:L",
      "type": "CVSS_V3"
    }
  ],
  "summary": "Undefined Behavior in mlflow"
}

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.

The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base model, served locally by ML-Gateway. They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.

Related by attack behaviour

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.

Action not permitted

CVE-2024-3099 (GCVE-0-2024-3099)

FKIE_CVE-2024-3099

GHSA-8F8Q-Q2J7-7J2M

GSD-2024-3099

PYSEC-2026-1645

Tags

Sightings

Nomenclature

Related by attack behaviour