Improper Neutralization of Special Elements in Output Used by a Downstream Component in Azure Machine Learning - CVE-2026-33833
Published: May 13, 2026
Vulnerability identifier: #VU131313
CSH Severity: High
CVSS v4.0: CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:A/VC:H/VI:L/VA:N/SC:N/SI:N/SA:N/E:U/U:Amber
CVE-ID: CVE-2026-33833
CWE-ID: CWE-74
Exploitation vector: Remote access
Exploit availability:
No public exploit available
Vendor: Microsoft
Affected software:
Azure Machine Learning
Azure Machine Learning
Detailed vulnerability description
The vulnerability allows a remote attacker to compromise the target system.
The vulnerability exists due to improper neutralization of special elements in output used by a downstream component in Azure Machine Learning. A remote attacker can perform spoofing attack.
How to mitigate CVE-2026-33833
Install updates from vendor's website.