CVE-2026-33833 Details
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.
A spoofing vulnerability has been identified in Azure Machine Learning due to improper neutralization of special elements in output, which can be exploited by an unauthorized attacker over the network. This issue affects Azure Machine Learning Notebook version 1.7.6.
Users are advised to update to the latest version of Azure Machine Learning. The security update can be downloaded from the Azure Notebooks entry on the Microsoft DevOps platform.
Metrics
CVSS 4.0 Severity and Vector Strings:
No CVSS 4.0 data is available for this CVE.
CVSS 3.x Severity and Vector Strings:
No data available for CVSS Version 2.0 on this CVE.
CISA-ADP
Assessed May 13, 2026References to Advisories, Solutions, and Tools
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| URL | Source(s) | Tag(s) |
|---|---|---|
| https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-33833 | [email protected] | Vendor Advisory |
Weakness Enumeration
| CWE-ID | CWE Name | Source |
|---|---|---|
| CWE-74 | Improper Neutralization of Special Elements in Output Used by a Downstream Component ('Injection') | [email protected] |
Affected Products
| Product | Versions |
|---|---|
| microsoft azure machine learning | 3.0.0 |
CPE
Remediation
| |
Change History
4 change records found show changes
| Date | Action | Recorded By |
|---|---|---|
| Jun 18, 2026 | Initial Analysis | [email protected] |
| Jun 17, 2026 | CVE Modified | [email protected] |
| Jun 17, 2026 | CVE Modified | CISA-ADP |
| May 12, 2026 | New CVE Received | [email protected] |