Cyber Resilience

CVE-2022-35960

Medium

Published: 16 September 2022

Published
16 September 2022
Modified
21 November 2024
KEV Added
Patch
CVSS Score v3.1 5.9 CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
EPSS Score 0.0021 43.3th percentile
Risk Priority 12 60% EPSS · 20% KEV · 20% CVSS

Summary

CVE-2022-35960 is a medium-severity Reachable Assertion (CWE-617) vulnerability in Google Tensorflow. Its CVSS base score is 5.9 (Medium).

Operationally, ranked at the 43.3th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.

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

EU & UK References

Vulnerability details

TensorFlow is an open source platform for machine learning. In `core/kernels/list_kernels.cc's TensorListReserve`, `num_elements` is assumed to be a tensor of size 1. When a `num_elements` of more than 1 element is provided, then `tf.raw_ops.TensorListReserve` fails the `CHECK_EQ` in `CheckIsAlignedAndSingleElement`. We…

more

have patched the issue in GitHub commit b5f6fbfba76576202b72119897561e3bd4f179c7. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

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
2.10, 2.8.0, 2.9.0 · 2.7.0 — 2.7.2

Mitigating Controls

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

References