Cyber Resilience

CVE-2026-32207

High

Published: 07 May 2026

Published
07 May 2026
Modified
08 May 2026
KEV Added
—
Patch
—
CVSS Score v3.1 8.8 CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
EPSS Score 0.0058 43.3th percentile
Risk Priority 55 floored blend · peak EPSS

Summary

CVE-2026-32207 is a high-severity Cross-site Scripting (CWE-79) vulnerability in Microsoft Azure Machine Learning. Its CVSS base score is 8.8 (High).

Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 43.3th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.

This vulnerability is AI-related — categorised as Other Platforms; in the Other ATLAS/OWASP Terms risk domain.

OWASP Top 10 for Web (2025)

A05:2025 Injection

EU & UK References

Vulnerability details

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.

CWE(s)
CWE-79

AI Security AnalysisAI

AI Category
Other Platforms
Risk Domain
Other ATLAS/OWASP Terms
OWASP Top 10 for LLMs 2025
None mapped
Classification Reason
Matched keywords: machine learning

Related Threats

MITRE ATT&CK Enterprise TechniquesAI

T1190 Exploit Public-Facing Application Initial Access
Adversaries may attempt to exploit a weakness in an Internet-facing host or system to initially access a network.
attack.mitre.org →
T1539 Steal Web Session Cookie Credential Access
An adversary may steal web application or service session cookies and use them to gain access to web applications or Internet services as an authenticated user without needing credentials.
attack.mitre.org →
Why these techniques?

XSS vuln in Azure ML web app directly enables T1190 exploitation of public-facing application and facilitates T1539 web session cookie theft via script injection.

Confidence: MEDIUM · MITRE ATT&CK Enterprise v19.0

CVEs Like This One

CVE-2025-49747Same product: Microsoft Azure Machine Learning
CVE-2025-47995Same product: Microsoft Azure Machine Learning
CVE-2025-49746Same product: Microsoft Azure Machine Learning
CVE-2026-21264Same vendor: Microsoft
CVE-2025-62211Same vendor: Microsoft
CVE-2025-62459Same vendor: Microsoft
CVE-2026-26105Same vendor: Microsoft
CVE-2025-62210Same vendor: Microsoft
CVE-2026-42897Same vendor: Microsoft
CVE-2026-26144Same vendor: Microsoft

Affected Assets

microsoft
azure machine learning
all versions

Mitigating Controls

Likely Mitigating Controls AI

Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.

CA-8 Penetration Testing
addresses: CWE-79

Penetration testing submits XSS payloads to web applications, detecting cross-site scripting flaws for subsequent remediation.

SI-10 Information Input Validation
addresses: CWE-79

Validates web inputs to reject script-related content that could produce XSS.

SI-15 Information Output Filtering
addresses: CWE-79

Output validation against expected content can reject or sanitize script content in generated web pages, reducing XSS exploitability.

References