Raw vector
CVSS:3.1/AV:N/AC:L/PR:H/UI:R/S:U/C:N/I:H/A:NCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2023-38188 is a medium-severity Cross-site Scripting (CWE-79) vulnerability in Microsoft Azure Hdinsight. Its CVSS base score is 4.5 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Protocol or Service Impersonation (T1001.003); ranked in the top 38% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
CVE-2023-38188 is a spoofing vulnerability affecting Azure Apache Hadoop, assigned CWE-79 and carrying a CVSS 4.5 rating that reflects network attack vector, low complexity, high privileges required, and user interaction needed to produce high integrity impact without affecting confidentiality or availability.
An authenticated attacker with high privileges who can also induce user interaction may exploit the flaw to perform spoofing actions that alter data integrity within the Hadoop environment.
The referenced Microsoft Security Response Center advisory at https://msrc.microsoft.com/update-guide/vulnerability/CVE-2023-38188 provides official guidance on available patches and mitigation steps for the affected Azure service.
EPSS for the CVE rose materially from a low baseline to a peak of 0.0741 on 2025-01-22 before receding to the current value of 0.0028, indicating a period of increased exploitation interest after disclosure.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-42010
Vulnerability Data
Azure Apache Hadoop Spoofing Vulnerability
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
—
—
—
V1.1.2V1.3.2
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.
Penetration testing submits XSS payloads to web applications, detecting cross-site scripting flaws for subsequent remediation.
Validates web inputs to reject script-related content that could produce XSS.
Output validation against expected content can reject or sanitize script content in generated web pages, reducing XSS exploitability.
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.
Secure SDLC practices directly target introduction of XSS via coding standards/testing (mostly), yet the single broad outcome leaves many specific neutralization vectors unaddressed (partial).
Patching and EOL replacement can remediate known XSS instances in libraries or frameworks (partial) but do nothing to enforce input neutralization in application code (none).
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.5.6 only promotes membership in groups to improve knowledge, receive alerts, and share information; it performs no action that stops XSS exploitation (or even the underlying neutralization defect) and is a pure dependency for other controls per the owner's labeling rule.