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Information exposure in MLflow

High severity GitHub Reviewed Published Dec 5, 2023 to the GitHub Advisory Database • Updated Dec 11, 2023

Package

pip mlflow (pip)

Affected versions

< 2.9.0

Patched versions

2.9.0

Description

An issue in MLFlow versions 2.8.1 and before allows a remote attacker to obtain sensitive information via a crafted request to REST API.

References

Published by the National Vulnerability Database Dec 5, 2023
Published to the GitHub Advisory Database Dec 5, 2023
Reviewed Dec 11, 2023
Last updated Dec 11, 2023

Severity

High

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v3 base metrics

Attack vector
Network
Attack complexity
Low
Privileges required
None
User interaction
None
Scope
Unchanged
Confidentiality
High
Integrity
None
Availability
None

CVSS v3 base metrics

Attack vector: More severe the more the remote (logically and physically) an attacker can be in order to exploit the vulnerability.
Attack complexity: More severe for the least complex attacks.
Privileges required: More severe if no privileges are required.
User interaction: More severe when no user interaction is required.
Scope: More severe when a scope change occurs, e.g. one vulnerable component impacts resources in components beyond its security scope.
Confidentiality: More severe when loss of data confidentiality is highest, measuring the level of data access available to an unauthorized user.
Integrity: More severe when loss of data integrity is the highest, measuring the consequence of data modification possible by an unauthorized user.
Availability: More severe when the loss of impacted component availability is highest.
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N

EPSS score

1.500%
(87th percentile)

Weaknesses

CVE ID

CVE-2023-43472

GHSA ID

GHSA-wqxf-447m-6f5f

Source code

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