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Vulnerability details: VCID-akmu-fas1-33h6
Vulnerability ID VCID-akmu-fas1-33h6
Aliases CVE-2022-21741
GHSA-428x-9xc2-m8mj
PYSEC-2022-120
PYSEC-2022-65
Summary Tensorflow is an Open Source Machine Learning Framework. ### Impact An attacker can craft a TFLite model that would trigger a division by zero in the implementation of depthwise convolutions. The parameters of the convolution can be user controlled and are also used within a division operation to determine the size of the padding that needs to be added before applying the convolution. There is no check before this division that the divisor is strictly positive. 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.
Status Published
Exploitability None
Weighted Severity None
Risk None
Affected and Fixed Packages Package Details
Weaknesses (3)
No exploits are available.
Exploit Prediction Scoring System (EPSS)
Percentile 0.46146
EPSS Score 0.00232
Published At May 30, 2026, 12:55 p.m.
Date Actor Action Source VulnerableCode Version
2026-05-30T20:29:35.376278+00:00 Pypa Importer Import https://github.com/pypa/advisory-database/blob/main/vulns/tensorflow-gpu/PYSEC-2022-120.yaml 38.6.0