Azure Machine Learning
CVE-2026-33833 — Azure Machine Learning Notebook Spoofing Vulnerability
Executive Summary
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.
Overview
8.2
CVSS HIGH
Important
MS Severity
Not Exploited
MS Exploit Status
Less Likely
MS Exploit Likelihood
CVSS Vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/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
Low
AVAILABILITY
None
EXPLOIT CODE MATURITY
Unproven
REMEDIATION LEVEL
Official Fix
REPORT CONFIDENCE
Confirmed
Temporal Score: 7.1
EPSS Score
0.00498
probability of exploitation in the next 30 days
0.38669 percentile - updated 2026-06-21
View on FIRST.org
Affected Products
1 affected product
| Product | KB Article | Severity | Impact | Restart Required |
|---|---|---|---|---|
| Azure Machine Learning | Release Notes (Security Update) |
Important | Spoofing | No |
Patches
1 patch
| Article | Type | Restart |
|---|---|---|
Release Notes |
Security Update | No |
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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