TensorFlow vulnerable to OOB read in `Gather_nd` in TF Lite

CRÍTICO 9.1CVE-2022-35937 · BIT-tensorflow-2022-35937 · GHSA-pxrw-j2fv-hx3h · Published 16/09/2022 · updated 17/06/2026

En resumen

CVE-2022-35937 es una vulnerabilidad CRÍTICO (CVSS 9.1) que afecta a tensorflow, tensorflow-cpu, tensorflow-gpu.
Probabilidad de explotación en los próximos 30 días (EPSS): 0.57%, mayor que el 47.2% de las vulnerabilidades.
Solución: actualizar a 2.8.1, 2.9.1, 2.7.2 o posterior.

Package	Affected versions	Patched versions
tensorflow PyPI	`≥ 2.8.0, < 2.8.1≥ 2.9.0, < 2.9.1< 2.7.2`	`2.8.12.9.12.7.2`
tensorflow-cpu PyPI	`≥ 2.8.0, < 2.8.1≥ 2.9.0, < 2.9.1< 2.7.2`	`2.8.12.9.12.7.2`
tensorflow-gpu PyPI	`≥ 2.8.0, < 2.8.1≥ 2.9.0, < 2.9.1< 2.7.2`	`2.8.12.9.12.7.2`
tensorflow google	`= 2.10≥ 2.7.0, < 2.7.2≥ 2.8.0, < 2.8.1≥ 2.9.0, < 2.9.1`	`2.7.22.8.12.9.1`

Description

Impact

The GatherNd function takes arguments that determine the sizes of inputs and outputs. If the inputs given are greater than or equal to the sizes of the outputs, an out-of-bounds memory read is triggered.

Patches

We have patched the issue in GitHub commit 595a65a3e224a0362d7e68c2213acfc2b499a196.

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.

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Attribution

This vulnerability has been reported by Hui Peng from Baidu Security.

NVD description

TensorFlow is an open source platform for machine learning. The `GatherNd` function takes arguments that determine the sizes of inputs and outputs. If the inputs given are greater than or equal to the sizes of the outputs, an out-of-bounds memory read is triggered. This issue has been patched in GitHub commit 595a65a3e224a0362d7e68c2213acfc2b499a196. 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.