Cyber Resilience

CVE-2022-23573

HighPublic PoC

Published: 04 February 2022

Published
04 February 2022
Modified
21 November 2024
KEV Added
Patch
CVSS Score v3.1 7.6 CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:H
EPSS Score 0.0029 53.2th percentile
Risk Priority 15 60% EPSS · 20% KEV · 20% CVSS

Summary

CVE-2022-23573 is a high-severity Use of Uninitialized Resource (CWE-908) vulnerability in Google Tensorflow. Its CVSS base score is 7.6 (High).

Operationally, ranked in the top 46.8% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.

This vulnerability is AI-related — categorised as Deep Learning Frameworks.

EU & UK References

Vulnerability details

Tensorflow is an Open Source Machine Learning Framework. The implementation of `AssignOp` can result in copying uninitialized data to a new tensor. This later results in undefined behavior. The implementation has a check that the left hand side of the…

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assignment is initialized (to minimize number of allocations), but does not check that the right hand side is also initialized. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

CWE(s)

AI Security AnalysisAI

AI Category
Deep Learning Frameworks
Risk Domain
N/A
OWASP Top 10 for LLMs 2025
None mapped
Classification Reason
Matched keywords: tensorflow, machine learning, tensorflow, tensorflow, tensorflow, tensorflow

Related Threats

Affected Assets

google
tensorflow
2.7.0 · ≤ 2.5.2 · 2.6.0 — 2.6.2

Mitigating Controls

No mitigating controls mapped yet. The per-CVE control annotator has not reached this CVE.

References