Improper neutralization of special elements in output used by a downstream component ('injection') in Azure Machine Learning allows an unauthorized attacker to perform spoofing over a network.

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Workaround

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History

Tue, 12 May 2026 17:30:00 +0000

Type Values Removed Values Added
Description Improper neutralization of special elements in output used by a downstream component ('injection') in Azure Machine Learning allows an unauthorized attacker to perform spoofing over a network.
Title Azure Machine Learning Notebook Spoofing Vulnerability
First Time appeared Microsoft
Microsoft azure Machine Learning
Weaknesses CWE-74
CPEs cpe:2.3:a:microsoft:azure_machine_learning:*:*:*:*:*:*:*:*
Vendors & Products Microsoft
Microsoft azure Machine Learning
References
Metrics cvssV3_1

{'score': 8.2, 'vector': 'CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:L/A:N/E:U/RL:O/RC:C'}


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cve-icon MITRE

Status: PUBLISHED

Assigner: microsoft

Published:

Updated: 2026-05-12T17:54:08.065Z

Reserved: 2026-03-24T00:52:01.353Z

Link: CVE-2026-33833

cve-icon Vulnrichment

No data.

cve-icon NVD

Status : Received

Published: 2026-05-12T18:17:05.160

Modified: 2026-05-12T18:17:05.160

Link: CVE-2026-33833

cve-icon Redhat

No data.

cve-icon OpenCVE Enrichment

Updated: 2026-05-12T19:30:23Z

Weaknesses