// For flags

CVE-2024-37052

 

Severity Score

8.8
*CVSS v3.1

Exploit Likelihood

*EPSS

Affected Versions

*CPE

Public Exploits

0
*Multiple Sources

Exploited in Wild

-
*KEV

Decision

Track*
*SSVC
Descriptions

Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.1.0 or newer, enabling a maliciously uploaded scikit-learn model to run arbitrary code on an end user’s system when interacted with.

La deserialización de datos que no son de confianza puede ocurrir en versiones de la plataforma MLflow que ejecutan la versión 1.1.0 o posterior, lo que permite que un modelo scikit-learn cargado maliciosamente ejecute código arbitrario en el sistema de un usuario final cuando interactúa con él.

*Credits: N/A
CVSS Scores
Attack Vector
Network
Attack Complexity
Low
Privileges Required
None
User Interaction
Required
Scope
Unchanged
Confidentiality
High
Integrity
High
Availability
High
* Common Vulnerability Scoring System
SSVC
  • Decision:Track*
Exploitation
None
Automatable
No
Tech. Impact
Total
* Organization's Worst-case Scenario
Timeline
  • 2024-05-31 CVE Reserved
  • 2024-06-04 CVE Published
  • 2024-06-06 EPSS Updated
  • 2024-08-02 CVE Updated
  • ---------- Exploited in Wild
  • ---------- KEV Due Date
  • ---------- First Exploit
CWE
  • CWE-502: Deserialization of Untrusted Data
CAPEC
  • CAPEC-586: Object Injection
Affected Vendors, Products, and Versions
Vendor Product Version Other Status
Vendor Product Version Other Status <-- --> Vendor Product Version Other Status
MLflow
Search vendor "MLflow"
 MLflow
Search vendor "MLflow" for product "MLflow"
 <= 1.1.0
Search vendor "MLflow" for product "MLflow" and version " <= 1.1.0"
en
Affected