CVE-2024-3099 Denial of Service and Data Model Poisoning via URL Encoding in mlflow/mlflow

2024-06-0618:08:16

CWE-475

@huntr_ai

www.cve.org

vulnerability

mlflow

version

exploitation

url encoding

denial of service

data model poisoning

authentication

inadequate validation

5.4 Medium

CVSS3

Attack Vector

NETWORK

Attack Complexity

LOW

Privileges Required

LOW

User Interaction

NONE

Scope

UNCHANGED

Confidentiality Impact

NONE

Integrity Impact

LOW

Availability Impact

LOW

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

0.0004 Low

EPSS

Percentile

9.1%

JSON

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.

CNA Affected

[
  {
    "vendor": "mlflow",
    "product": "mlflow/mlflow",
    "versions": [
      {
        "version": "unspecified",
        "status": "affected",
        "versionType": "custom",
        "lessThanOrEqual": "latest"
      }
    ]
  }
]