Cyber Resilience

CVE-2022-35952

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 0.0022 44.6th percentile
Risk Priority 12 60% EPSS · 20% KEV · 20% CVSS

Summary

CVE-2022-35952 is a medium-severity Reachable Assertion (CWE-617) vulnerability in Google Tensorflow. Its CVSS base score is 5.9 (Medium).

Operationally, ranked at the 44.6th 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. The `UnbatchGradOp` function takes an argument `id` that is assumed to be a scalar. A nonscalar `id` can trigger a `CHECK` failure and crash the program. It also requires its argument…

more

`batch_index` to contain three times the number of elements as indicated in its `batch_index.dim_size(0)`. An incorrect `batch_index` can trigger a `CHECK` failure and crash the program. We have patched the issue in GitHub commit 5f945fc6409a3c1e90d6970c9292f805f6e6ddf2. 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 · 2.7.0 — 2.7.2 · 2.8.0 — 2.8.1 · 2.9.0 — 2.9.1

Mitigating Controls

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

References