Cyber Posture

CVE-2025-49747

Critical

Published: 18 July 2025

Published
18 July 2025
Modified
14 August 2025
KEV Added
Patch
CVSS Score 9.9 CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:H
EPSS Score 0.0066 71.3th percentile
Risk Priority 20 60% EPSS · 20% KEV · 20% CVSS

Summary

CVE-2025-49747 is a critical-severity Missing Authorization (CWE-862) vulnerability in Microsoft Azure Machine Learning. Its CVSS base score is 9.9 (Critical).

Operationally, exploitation aligns with the MITRE ATT&CK technique Exploitation for Privilege Escalation (T1068); ranked in the top 28.7% of CVEs by exploit likelihood; 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.

The strongest mitigations our analysis identified are NIST 800-53 AC-3 (Access Enforcement) and AC-6 (Least Privilege).

Threat & Defense at a Glance

What attackers do: exploitation maps to Exploitation for Privilege Escalation (T1068). What defenders deploy: see the NIST 800-53 controls recommended below.
Threat & Defense Details

Mitigating Controls (NIST 800-53 r5)AI

prevent

Requires enforcement of approved authorizations for access to system resources in Azure Machine Learning, directly addressing the missing authorization that enables privilege escalation.

prevent

Enforces least privilege to limit the scope and impact of privilege escalation from low-privilege accounts exploiting the missing authorization.

prevent

Mandates identification, reporting, and correction of flaws like this missing authorization vulnerability through timely patching as per Microsoft's advisory.

MITRE ATT&CK Enterprise TechniquesAI

T1068 Exploitation for Privilege Escalation Privilege Escalation
Adversaries may exploit software vulnerabilities in an attempt to elevate privileges.
Why these techniques?

Missing authorization in Azure Machine Learning enables an authorized attacker to perform privilege escalation over a network via exploitation.

NVD Description

Missing authorization in Azure Machine Learning allows an authorized attacker to elevate privileges over a network.

Deeper analysisAI

CVE-2025-49747 is a missing authorization vulnerability (CWE-862) affecting Azure Machine Learning. Published on 2025-07-18, it enables an authorized attacker to elevate privileges over a network. The issue carries a CVSS v3.1 base score of 9.9 (AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:H), classifying it as critical due to its potential for widespread impact.

An attacker requires low privileges (PR:L) to exploit the vulnerability remotely over the network (AV:N) with low attack complexity (AC:L) and no user interaction (UI:N). Exploitation results in a scope change (S:C) and high impacts across confidentiality, integrity, and availability (C:H/I:H/A:H), specifically allowing privilege escalation within the affected Azure Machine Learning environment.

Microsoft's advisory provides mitigation guidance in its update guide at https://msrc.microsoft.com/update-guide/vulnerability/CVE-2025-49747. Security practitioners should consult this resource for patching and workaround details.

Details

CWE(s)

Affected Products

microsoft
azure machine learning
all versions

AI Security AnalysisAI

AI Category
Other Platforms
Risk Domain
Other ATLAS/OWASP Terms
OWASP Top 10 for LLMs 2025
None mapped
Classification Reason
Azure Machine Learning is a cloud-based platform for managing machine learning workflows, including training, deployment, and inference, fitting the 'Other Platforms' category for AI/ML services.

CVEs Like This One

CVE-2025-47995Same product: Microsoft Azure Machine Learning
CVE-2025-49746Same product: Microsoft Azure Machine Learning
CVE-2026-32207Same product: Microsoft Azure Machine Learning
CVE-2025-49723Same vendor: Microsoft
CVE-2025-21396Same vendor: Microsoft
CVE-2025-54914Same vendor: Microsoft
CVE-2026-24293Same vendor: Microsoft
CVE-2025-21359Same vendor: Microsoft
CVE-2025-21367Same vendor: Microsoft
CVE-2025-49739Same vendor: Microsoft

References