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| Vulnerability ID | VCID-bmvq-fjkr-2fc3 |
| 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 |
| System | Score | Found at |
|---|---|---|
| There are no known severity scores. | ||
No EPSS data available for this vulnerability.
| Date | Actor | Action | Source | VulnerableCode Version |
|---|---|---|---|---|
| 2026-06-02T04:16:36.627332+00:00 | Pypa Importer | Import | https://github.com/pypa/advisory-database/blob/main/vulns/tensorflow-gpu/PYSEC-2022-120.yaml | 38.6.0 |