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
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.
CVSS Scores
EPSS Scores
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Meta Information
Affected Vendors & Products
| Vendor | Product | Version / Range |
|---|---|---|
| microsoft | azure_machine_learning | * |
Helpful Resources
Exploitability
CWE
KEV
| 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. |
Attack-Flow Graph
AI Powered Q&A
Can you explain this vulnerability to me?
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.
How can this vulnerability impact me? :
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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