Azure Machine Learning
CVE-2026-32207 — Azure Machine Learning Notebook Spoofing Vulnerability
Executive Summary
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.
Overview
6.1
CVSS MEDIUM
Critical
MS Severity
Not Exploited
MS Exploit Status
Not Found
MS Exploit Likelihood
CVSS Vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:L/I:L/A:N/E:U/RL:O/RC:C
ATTACK VECTOR
Network
ATTACK COMPLEXITY
Low
PRIVILEGES REQUIRED
None
USER INTERACTION
Required
SCOPE
Changed
CONFIDENTIALITY
High
INTEGRITY
High
AVAILABILITY
High
EXPLOIT CODE MATURITY
Unproven
REMEDIATION LEVEL
Official Fix
REPORT CONFIDENCE
Confirmed
Temporal Score: 7.7
EPSS Score
0.00579
probability of exploitation in the next 30 days
0.43009 percentile - updated 2026-06-21
View on FIRST.org
Known Exploits
No known exploits have been linked for this CVE yet. When available, exploit references will be sourced from public repositories and may be unverified, incomplete, or non-functional. Always review code carefully before use in any environment.
Acknowledgments
Jianyang Song
References
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