CVE-2021-37675: Division by 0 in most convolution operators in TensorFlow

Severity: medium (CVSS 5.5 v3.1)
Exploited in the wild: not listed in CISA KEV
EPSS: 0.2% probability of exploitation in the next 30 days
Public exploit or detection template: none known
Published: 2021-08-12 · updated 2026-06-17
Weakness: CWE-369

Description

TensorFlow is an end-to-end open source platform for machine learning. In affected versions most implementations of convolution operators in TensorFlow are affected by a division by 0 vulnerability where an attacker can trigger a denial of service via a crash. The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/framework/common_shape_fns.cc#L577) is missing several validations before doing divisions and modulo operations. We have patched the issue in GitHub commit 8a793b5d7f59e37ac7f3cd0954a750a2fe76bad4. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

Affected products

tensorflow: from 2.3.0 before 2.3.4; from 2.4.0 before 2.4.3; 2.5.0, 2.6.0-rc0, 2.6.0-rc1, 2.6.0-rc2 — fixed in 2.3.4, 2.4.3

How to fix

Upgrade to a fixed version: tensorflow 2.3.4, 2.4.3. Check the vendor advisory for mitigations.

References

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