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  <updated>2026-10-09T19:54:54.600830+00:00</updated>
  <author>
    <name>Vulnerability-Lookup</name>
    <email>csirt@opendfir.org</email>
  </author>
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  <entry>
    <id>https://cve.radiocsirt.org/vuln/cve-2021-29517</id>
    <title>CVE-2021-29517 — Division by zero in `Conv3D`</title>
    <updated>2026-10-09T19:54:54.636105+00:00</updated>
    <content type="xhtml">
      <div xmlns="http://www.w3.org/1999/xhtml"><p><strong>Affected:</strong> tensorflow</p>
<p>TensorFlow is an end-to-end open source platform for machine learning. A malicious user could trigger a division by 0 in `Conv3D` implementation. The implementation(https://github.com/tensorflow/tensorflow/blob/42033603003965bffac51ae171b51801565e002d/tensorflow/core/kernels/conv_ops_3d.cc#L143-L145) does a modulo operation based on user controlled input. Thus, when `filter` has a 0 as the fifth element, this results in a division by 0. Additionally, if the shape of the two tensors is not valid, an Eigen assertion can be triggered, resulting in a program crash. 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.</p></div>
    </content>
    <link href="https://cve.radiocsirt.org/vuln/cve-2021-29517"/>
  </entry>
  <entry>
    <id>https://cve.radiocsirt.org/vuln/ghsa-772p-x54p-hjrv</id>
    <title>GHSA-772p-x54p-hjrv — Division by zero in `Conv3D`</title>
    <updated>2026-10-09T19:54:54.636174+00:00</updated>
    <content type="xhtml">
      <div xmlns="http://www.w3.org/1999/xhtml"><p><strong>Affected:</strong> PyPI: tensorflow, PyPI: tensorflow-cpu, PyPI: tensorflow-gpu</p>
<p>### Impact
A malicious user could trigger a division by 0 in `Conv3D` implementation:</p>
<p>```python
import tensorflow as tf</p>
<p>input_tensor = tf.constant([], shape=[0, 0, 0, 0, 0], dtype=tf.float32)
filter_tensor = tf.constant([], shape=[0, 0, 0, 0, 0], dtype=tf.float32)</p>
<p>tf.raw_ops.Conv3D(input=input_tensor, filter=filter_tensor, strides=[1, 56, 56, 56, 1], padding='VALID', data_format='NDHWC', dilations=[1, 1, 1, 23, 1])
```</p>
<p>The [implementation](https://github.com/tensorflow/tensorflow/blob/42033603003965bffac51ae171b51801565e002d/tensorflow/core/kernels/conv_ops_3d.cc#L143-L145) does a modulo operation based on user controlled input:</p>
<p>```cc
  const int64 out_depth = filter.dim_size(4);
  OP_REQUIRES(context, in_depth % filter_depth == 0, ...);
```</p>
<p>Thus, when `filter` has a 0 as the fifth element, this results in a division by 0.</p>
<p>Additionally, if the shape of the two tensors is not valid, an Eigen assertion can be triggered, resulting in a program crash:</p>
<p>```python
import tensorflow as tf</p>
<p>input_tensor = tf.constant([], shape=[2, 2, 2, 2, 0], dtype=tf.float32)
filter_tensor = tf.constant([], shape=[0, 0, 2, 6, 2], dtype=tf.float32)</p>
<p>tf.raw_ops.Conv3D(input=input_tensor, filter=filter_tensor, strides=[1, 56, 39, 34, 1], padding='VALID', data_format='NDHWC', dilations=[1, 1, 1, 1, 1])
```</p>
<p>The shape of the two tensors must follow the constraints specified in the [op description](https://www.tensorflow.org/api_docs/python/tf/raw_ops/Conv3D).</p>
<p>### Patches
We have patched the iss…</p></div>
    </content>
    <link href="https://cve.radiocsirt.org/vuln/ghsa-772p-x54p-hjrv"/>
  </entry>
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