Cyber Resilience

CVE-2023-23382

Microsoft Azure Machine Learning 3.0.0 – 3.0.02076.0001

Published
14 February 2023
Modified
21 November 2024
Patch / advisory
View advisory
CVSS Score v3.1 6.5
Click a component to see what it means
Raw vectorCVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N
EPSS Score 0.031 87th percentile
Risk Priority 55 floored blend · peak EPSS

Summary

CVE-2023-23382 is a medium-severity Storing Passwords in a Recoverable Format (CWE-257) vulnerability in Microsoft Azure Machine Learning. Its CVSS base score is 6.5 (Medium).

Operationally, exploitation aligns with the MITRE ATT&CK technique Group Policy Preferences (T1552.006); ranked in the top 13% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.

This vulnerability is AI-related — categorised as Other AI Platforms.

EU & UK References

Vulnerability Data

Azure Machine Learning Compute Instance Information Disclosure Vulnerability

CWE(s)
CWE-257NVD-CWE-noinfo

AI Security AnalysisAI

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

Related Threats

MITRE ATT&CK Enterprise Techniques

T1552.006 Group Policy Preferences Credential Access
Adversaries may attempt to find unsecured credentials in Group Policy Preferences (GPP).
attack.mitre.org →
T1552 Unsecured Credentials Credential Access
Adversaries may search compromised systems to find and obtain insecurely stored credentials.
attack.mitre.org →
T1552.001 Credentials In Files Credential Access
Adversaries may search local file systems and remote file shares for files containing insecurely stored credentials.
attack.mitre.org →
T1552.002 Credentials in Registry Credential Access
Adversaries may search the Registry on compromised systems for insecurely stored credentials.
attack.mitre.org →
Derived from this CVE’s CWE(s) via the direct CWE→ATT&CK cross-walk.

CVEs Like This One

CVE-2023-28312Same product: Microsoft Azure Machine Learning
CVE-2023-21726Same vendor: Microsoft
CVE-2023-38738Same vendor: Microsoft
CVE-2023-35625Same vendor: Microsoft
CVE-2024-3073Shared CWE-257
CVE-2026-20128Shared CWE-257
CVE-2024-20686Same vendor: Microsoft
CVE-2023-24946Same vendor: Microsoft
CVE-2024-38264Same vendor: Microsoft
CVE-2025-8904Shared CWE-257

Affected Assets

microsoft
azure machine learning
3.0.0 — 3.0.02076.0001

Mitigating Controls

Control response

Prevent
Stop it (NIST 800-53)

—

Detect
Catch it (NIST detect / respond)

—

Harden
Shrink the surface (DISA STIG)

—

Validate
Prove the fix (OWASP ASVS)
  • V11.4.2
  • V11.4.4

Mitigating Controls (NIST CSF 2.0) AI

Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.

PR.DS-01 mostly match
prevents

Protecting data-at-rest with cryptographic hashes directly prevents recoverable password storage.

PR.PS-06 partial match
prevents

Secure SDLC practices include requirements for non-recoverable password storage.

Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI

Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.

A.5.17 Authentication information full match
degrades

Directly requires secure handling and protection of authentication information, preventing storage in recoverable formats.

A.8.5 Secure authentication full match
degrades

Mandates secure authentication mechanisms that preclude recoverable password storage.

A.8.24 Use of cryptography partial match
degrades

Requires proper use of cryptography, which can mitigate recoverable storage if applied correctly to passwords.

A.8.25 Secure development life cycle partial match
prevents

Secure SDLC includes requirements that reduce the likelihood of introducing recoverable password storage.

A.8.28 Secure coding partial match
prevents

Secure coding practices can prevent developers from implementing recoverable password storage.

References