CVE-2026-32207 Azure Machine Learning Notebook Spoofing Vulnerability
An attacker can perform spoofing attacks via cross-site scripting in Azure Machine Learning notebooks, requiring a patch to mitigate.
- Exploited in the wild
- Not known
- Login needed
- Not needed
- Attackable
- Over the internet
- Victim action needed
- A user has to click or open something
- Fix
- None listed
What is CVE-2026-32207?
CVE-2026-32207 is a high-severity cross-site scripting vulnerability in Microsoft Azure Machine Learning, published on 7 May 2026. An attacker can exploit it over the internet without logging in, and only if a user opens a file or follows a link.
Official 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.
Weakness: CWE-79
Which versions are affected by CVE-2026-32207?
It affects 1 product.
Products include Microsoft Azure Machine Learning.
How do I fix CVE-2026-32207?
No fix has been published for CVE-2026-32207 yet. Limit exposure of the affected software until one is available.
Escape output for the context it lands in and set a strict Content Security Policy. Upgrading the affected component is the real fix. More about Cross-site scripting.
Is CVE-2026-32207 being exploited?
There is no known exploitation of CVE-2026-32207 in the wild and no public exploit code.
Other vulnerabilities in Microsoft Azure Machine Learning
- CVE-2025-49746 Azure Machine Learning Elevation of Privilege Vulnerability
- CVE-2025-49747 Azure Machine Learning Elevation of Privilege Vulnerability
- CVE-2025-30390 Azure ML Compute Elevation of Privilege Vulnerability
- CVE-2026-68791 Azure Machine Learning Information Disclosure Vulnerability
- CVE-2026-33833 Azure Machine Learning Notebook Spoofing Vulnerability
Sources
Also known as GHSA-h553-38x2-qp6q.