Cyber Resilience

CVE-2023-35317

High

Published: 11 July 2023

Published
11 July 2023
Modified
21 November 2024
KEV Added
Patch
CVSS Score v3.1 7.8 CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
EPSS Score 0.0011 28.8th percentile
Risk Priority 16 60% EPSS · 20% KEV · 20% CVSS

Summary

CVE-2023-35317 is a high-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Microsoft Windows Server 2012. Its CVSS base score is 7.8 (High).

Operationally, ranked at the 28.8th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.

EU & UK References

Vulnerability details

Windows Server Update Service (WSUS) Elevation of Privilege Vulnerability

CWE(s)

Related Threats

No named actor attribution yet. ATT&CK technique mapping in progress for this CVE.

Affected Assets

microsoft
windows server 2012
all versions, r2
microsoft
windows server 2016
all versions
microsoft
windows server 2019
all versions
microsoft
windows server 2022
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.

addresses: CWE-502

Penetration testing supplies malicious serialized objects, detecting unsafe deserialization and supporting corrective actions.

addresses: CWE-502

Evaluation of untrusted data handling (deserialization testing) reveals unsafe processing, which the required remediation process addresses.

addresses: CWE-502

Untrusted serialized data can be deserialized and observed inside the chamber, blocking gadget-chain exploitation outside the sandbox.

addresses: CWE-502

Validates or rejects untrusted serialized data before deserialization occurs.

addresses: CWE-502

Identifies and blocks malicious code introduced through deserialization of untrusted data at system boundaries.

addresses: CWE-502

Integrity verification of serialized information can detect tampering before deserialization occurs.

addresses: CWE-502

Provenance of associated data allows detection of untrusted sources before deserialization or processing occurs.

References