Overview
On April 30, 2025, Microsoft published details about a critical security vulnerability identified as CVE-2025-30390 in Azure Machine Learning (Azure ML). This vulnerability allows an authorized attacker to escalate privileges over a network, potentially compromising entire machine learning workloads hosted in Azure.
Technical Details
This vulnerability is categorized under CWE-285: Improper Authorization. The flaw lies in the insufficient enforcement of authorization checks in Azure ML’s compute environments. A user with limited privileges can exploit the weakness to gain elevated access and potentially perform administrative-level actions.
The vulnerability is rated CRITICAL with a CVSS v3.1 base score of 9.9. The CVSS vector string is:
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:H/E:U/RL:O/RC:C
This score reflects the fact that the attack is:
- Network-accessible (AV:N)
- Requires low attack complexity (AC:L)
- Needs only low privileges (PR:L)
- Requires no user interaction (UI:N)
- Has a high impact on confidentiality, integrity, and availability (C:H/I:H/A:H)
Impacted Systems
All versions of Azure Machine Learning compute environments are potentially affected. The vulnerability is relevant to cloud-hosted scenarios and may not directly impact on-premises solutions, as noted by the tag exclusively-hosted-service.
Mitigation and Response
Microsoft has published a security advisory and recommended actions. Although no public exploit is known at the time of publication, organizations using Azure ML are strongly urged to review Microsoft’s guidance:
MSRC Advisory on CVE-2025-30390
The advisory indicates that the vulnerability is not currently exploited in the wild, and exploitation is considered unlikely. However, due to the high impact, it remains a priority for remediation.
Understanding the Risk
This CVE demonstrates the risks of insufficient access control mechanisms in cloud-based machine learning platforms. In scenarios where compute resources are shared among users or teams, improper isolation and authorization logic can allow lateral movement or privilege abuse, violating the principle of least privilege (PoLP).
The SSVC (Stakeholder-Specific Vulnerability Categorization) model applied by CISA further reinforces the urgency, classifying the technical impact as total and recommending swift coordination despite no current exploitation.
Conclusion
CVE-2025-30390 is a high-priority vulnerability for any organization leveraging Azure ML. The combination of low complexity and high impact makes it critical to address, even in the absence of known exploitation. Security teams should monitor vendor advisories closely and apply any available patches or mitigations.
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