CVE-2026-32207
HighSummary
Azure Machine Learning has an improper neutralization of input during web page generation, leading to a cross-site scripting (XSS) vulnerability. This allows an unauthorized attacker to perform spoofing over a network.
Risk Assessment
The organization may be exposed to attacks that could lead to data theft or session hijacking. This could result in loss of customer trust and potential financial losses.
Recommendation
It is recommended to implement proper input sanitization mechanisms and regularly update Azure Machine Learning components to minimize the risk of XSS attacks.
Other vulnerabilities in Azure Machine Learning
See all- CVE-2026-33833High
Improper neutralization of special elements in output used by a downstream component in Azure Machine Learning allows an unauthorized attacker to perform spoofing over a network.
- CVE-2023-23382Medium
An information disclosure vulnerability in Azure Machine Learning Compute Instance. An attacker could exploit this to gain unauthorized access to data.
Original NVD description (English source)
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.