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
0.4474 percentile - updated 2026-08-14
View on FIRST.org
Exploits & PoC
No public exploit or PoC has been linked for this CVE yet. When available, references are sourced from public repositories and may be unverified or non-functional — review carefully before use.
Detection Rules
No public Sigma or Nuclei detection rule has been mapped to this CVE yet. Coverage is concentrated on exploited / high-profile vulnerabilities; check SigmaHQ for updates.
Acknowledgments
Jianyang Song
References
On This Page