Cyber Resilience

CVE-2023-44216

Microsoft Windows 11

Public PoC
Published
27 September 2023
Modified
21 November 2024
CVSS Score v3.1 5.3
Click a component to see what it means
Raw vectorCVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:N/A:N
EPSS Score 0.018 77th percentile
Risk Priority 45 floored blend · peak EPSS

Summary

CVE-2023-44216 is a medium-severity Observable Discrepancy (CWE-203) vulnerability in Microsoft Windows 11. Its CVSS base score is 5.3 (Medium).

Operationally, exploitation aligns with the MITRE ATT&CK technique Account Discovery (T1087); ranked in the top 23% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.

EU & UK References

Vulnerability Data

PVRIC (PowerVR Image Compression) on Imagination 2018 and later GPU devices offers software-transparent compression that enables cross-origin pixel-stealing attacks against feTurbulence and feBlend in the SVG Filter specification, aka a GPU.zip issue. For example, attackers can sometimes accurately determine text…

more

contained on a web page from one origin if they control a resource from a different origin.

CWE(s)

Related Threats

MITRE ATT&CK Enterprise Techniques

T1087 Account Discovery Discovery
Adversaries may attempt to get a listing of valid accounts, usernames, or email addresses on a system or within a compromised environment.
T1110 Brute Force Credential Access
Adversaries may use brute force techniques to gain access to accounts when passwords are unknown or when password hashes are obtained.
T1595 Active Scanning Reconnaissance
Adversaries may execute active reconnaissance scans to gather information that can be used during targeting.
Derived from this CVE’s CWE(s) via the direct CWE→ATT&CK cross-walk.

CVEs Like This One

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CVE-2023-20569Same product: Amd Ryzen 5 7600X
CVE-2025-48561Same product: Google Android
CVE-2024-54476Same product: Apple Macos
CVE-2023-21330Same product: Google Android
CVE-2023-21293Same product: Google Android
CVE-2023-40090Same product: Google Android
CVE-2023-21332Same product: Google Android
CVE-2024-43095Same product: Google Android
CVE-2023-21336Same product: Google Android

Affected Assets

canonical
ubuntu linux
22.04
amd
ryzen 7 4800u
all versions
intel
core i7-10510u
all versions
intel
core i7-12700k
all versions
intel
core i7-8700
all versions
microsoft
windows 11
all versions
intel
core i7-10610u
all versions
intel
core i7-11800h
all versions
nvidia
geforce rtx 3060
all versions
microsoft
windows 10
all versions
+6 more product configuration(s) — see NVD for full list

Mitigating Controls

Control response

Prevent
Stop it (NIST 800-53)

Detect
Catch it (NIST detect / respond)

Harden
Shrink the surface (DISA STIG)
  • 1 hardening rule · 1 OS baseline
Validate
Prove the fix (OWASP ASVS)

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-203

Misdirection can normalize or falsify responses to eliminate observable discrepancies that aid reconnaissance.

addresses: CWE-203

Observable discrepancies in system behavior can be modulated to create covert storage or timing channels; the required analysis detects and constrains such avenues.

addresses: CWE-203

Prevents attackers from using observable differences in error responses to infer internal system details or state.

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.PS-06 mostly match
prevents

Secure SDLC practices directly prevent observable response discrepancies via consistent error handling and timing.

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.

none

Accurate, synchronized timestamps reduce observable timing discrepancies that an attacker could exploit to infer sensitive information or distinguish between success and failure paths.

References