CVE-2026-32207
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Cross-Site Scripting in Azure Machine Learning

Publication date: 2026-05-07

Last updated on: 2026-05-08

Assigner: Microsoft Corporation

Description
Improper neutralization of input during web page generation ('cross-site scripting') in Azure Machine Learning allows an unauthorized attacker to perform spoofing over a network.
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Meta Information
Published
2026-05-07
Last Modified
2026-05-08
Generated
2026-06-19
AI Q&A
2026-05-08
EPSS Evaluated
2026-06-18
NVD
CVE-2026-32207
EUVD
EUVD-2026-28447
Affected Vendors & Products
Showing 1 associated CPE
Vendor Product Version / Range
microsoft azure_machine_learning *
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Exploitability
CWE
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KEV
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CWE ID Description
CWE-79 The product does not neutralize or incorrectly neutralizes user-controllable input before it is placed in output that is used as a web page that is served to other users.
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Executive Summary

This vulnerability is a cross-site scripting (XSS) issue in Azure Machine Learning. It occurs because the system does not properly neutralize input during web page generation, allowing an unauthorized attacker to inject malicious scripts.

As a result, the attacker can perform spoofing attacks over a network, potentially tricking users or systems by presenting false information.

Impact Analysis

This vulnerability can have severe impacts including unauthorized access and control over user interactions due to spoofing.

  • Confidentiality can be compromised (C:H) as attackers may steal sensitive information.
  • Integrity can be compromised (I:H) as attackers may alter data or content.
  • Availability can be compromised (A:H) as attackers may disrupt services.
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