CVE-2021-29522: Division by 0 in `Conv3DBackprop*`

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: yes
Published: 2021-05-14 · updated 2026-06-17
Weakness: CWE-369

Description

TensorFlow is an end-to-end open source platform for machine learning. The `tf.raw_ops.Conv3DBackprop*` operations fail to validate that the input tensors are not empty. In turn, this would result in a division by 0. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/a91bb59769f19146d5a0c20060244378e878f140/tensorflow/core/kernels/conv_grad_ops_3d.cc#L430-L450) does not check that the divisor used in computing the shard size is not zero. Thus, if attacker controls the input sizes, they can trigger a denial of service via a division by zero error. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

Affected products

tensorflow: before 2.1.4; from 2.2.0 before 2.2.3; from 2.3.0 before 2.3.3; from 2.4.0 before 2.4.2 — fixed in 2.1.4, 2.2.3, 2.3.3, 2.4.2

How to fix

Upgrade to a fixed version: tensorflow 2.1.4, 2.2.3, 2.3.3, 2.4.2. Check the vendor advisory for mitigations.

References

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