EUVD-2026-82587

Incorrect authorization in Azure Machine Learning allows an unauthorized attacker to disclose information over a network...

CVE-2026-68791

Incorrect authorization in Azure Machine Learning allows an unauthorized attacker to disclose information over a network...

CVE-2026-68791

CVE-2026-68791 is an incorrect authorization vulnerability in Azure Machine Learning that allows an unauthenticated, network-based attacker to disclose information with HIGH severity (CVSS 3.1: 8.6). The attack requires no prior privileges or user interaction, and the scope is CHANGED , indicatin...

Azure Machine Learning Information Disclosure Vulnerability

Incorrect authorization in Azure Machine Learning allows an unauthorized attacker to disclose information over a network...

PYSEC-2026-1664 Exposure of Sensitive Information in mltable

Azure Machine Learning Compute Instance for SDK Users Information Disclosure Vulnerability...

CVE-2026-33833

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...

EUVD-2026-29580

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...

CVE-2026-33833

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...

CVE-2026-33833

Azure Machine Learning is affected where the issue occurs in the downstream component’s output handling, described as an improper neutralization of special elements that enables network spoofing. The CVE-2026-33833 entry notes an attacker could exploit this via a network vector with no user inter...

CVE-2026-33833 Azure Machine Learning Notebook Spoofing Vulnerability

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CVE-2026-33833 Azure Machine Learning Notebook Spoofing Vulnerability

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Azure Machine Learning Notebook Spoofing Vulnerability

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...

PT-2026-40141

Name of the Vulnerable Software and Affected Versions Azure Machine Learning affected versions not specified Description Improper neutralization of special elements in output used by a downstream component allows an unauthorized attacker to perform spoofing over a network. This issue can lead to...

KLA91034 Multiple vulnerabilities in Microsoft Azure

Multiple vulnerabilities were found in Microsoft Azure. Malicious users can exploit these vulnerabilities to spoof user interface, bypass security restrictions, gain privileges. Below is a complete list of vulnerabilities: 1. A spoofing vulnerability in Azure Machine Learning Notebook can be...

Microsoft Azure Machine Learning 注入漏洞

Microsoft Azure Machine Learning is a machine learning service provided by Microsoft Corporation in the United States. There is an injection vulnerability present in Microsoft Azure Machine Learning. Attackers utilize this vulnerability to carry out phishing attacks...

CVE-2026-32207

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...

EUVD-2026-28447

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...

CVE-2026-32207

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...

CVE-2026-32207 Azure Machine Learning Notebook Spoofing Vulnerability

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CVE-2026-32207

CVE-2026-32207 concerns an XSS vulnerability in Azure Machine Learning Notebook/Notebook UI where improper neutralization of input during web page generation enables an unauthenticated attacker to spoof content over the network. Underlying cause: improper sanitization of user-controlled input in ...