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  <updated>2026-10-09T12:32:52.236139+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-2021-29524</id>
    <title>CVE-2021-29524 — Division by 0 in `Conv2DBackpropFilter`</title>
    <updated>2026-10-09T12:32:52.237764+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. An attacker can trigger a division by 0 in `tf.raw_ops.Conv2DBackpropFilter`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/496c2630e51c1a478f095b084329acedb253db6b/tensorflow/core/kernels/conv_grad_shape_utils.cc#L130) does a modulus operation where the divisor is controlled by the caller. 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-2021-29524"/>
  </entry>
  <entry>
    <id>https://cve.radiocsirt.org/vuln/ghsa-r4pj-74mg-8868</id>
    <title>GHSA-r4pj-74mg-8868 — Division by 0 in `Conv2DBackpropFilter`</title>
    <updated>2026-10-09T12:32:52.237820+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
An attacker can trigger a division by 0 in `tf.raw_ops.Conv2DBackpropFilter`:</p>
<p>```python
import tensorflow as tf</p>
<p>input_tensor = tf.constant([], shape=[0, 0, 1, 0], dtype=tf.float32)
filter_sizes = tf.constant([1, 1, 1, 1], shape=[4], dtype=tf.int32)
out_backprop = tf.constant([], shape=[0, 0, 1, 1], dtype=tf.float32)</p>
<p>tf.raw_ops.Conv2DBackpropFilter(input=input_tensor, filter_sizes=filter_sizes,
                                out_backprop=out_backprop,
                                strides=[1, 66, 18, 1], use_cudnn_on_gpu=True,
                                padding='SAME', explicit_paddings=[],
                                data_format='NHWC', dilations=[1, 1, 1, 1])
```                 
                    
This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/496c2630e51c1a478f095b084329acedb253db6b/tensorflow/core/kernels/conv_grad_shape_utils.cc#L130) does a modulus operation where the divisor is controlled by the caller:</p>
<p>```cc 
  if (dims-&gt;in_depth % filter_shape.dim_size(num_dims - 2)) { ... }
```
    
### Patches
We have patched the issue in GitHub commit [fca9874a9b42a2134f907d2fb46ab774a831404a](https://github.com/tensorflow/tensorflow/commit/fca9874a9b42a2134f907d2fb46ab774a831404a).</p>
<p>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>
<p>### For more infor…</p></div>
    </content>
    <link href="https://cve.radiocsirt.org/vuln/ghsa-r4pj-74mg-8868"/>
  </entry>
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