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    <item>
      <title>CVE-2021-29526 — Division by 0 in `Conv2D`</title>
      <link>https://cve.radiocsirt.org/vuln/cve-2021-29526</link>
      <description>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; tensorflow&lt;/p&gt;
&lt;p&gt;TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a division by 0 in `tf.raw_ops.Conv2D`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/988087bd83f144af14087fe4fecee2d250d93737/tensorflow/core/kernels/conv_ops.cc#L261-L263) does a division by a quantity that 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.&lt;/p&gt;</description>
      <content:encoded>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; tensorflow&lt;/p&gt;
&lt;p&gt;TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a division by 0 in `tf.raw_ops.Conv2D`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/988087bd83f144af14087fe4fecee2d250d93737/tensorflow/core/kernels/conv_ops.cc#L261-L263) does a division by a quantity that 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.&lt;/p&gt;</content:encoded>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/cve-2021-29526</guid>
    </item>
    <item>
      <title>GHSA-4vf2-4xcg-65cx — Division by 0 in `Conv2D`</title>
      <link>https://cve.radiocsirt.org/vuln/ghsa-4vf2-4xcg-65cx</link>
      <description>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; PyPI: tensorflow, PyPI: tensorflow-cpu, PyPI: tensorflow-gpu&lt;/p&gt;
&lt;p&gt;### Impact
An attacker can trigger a division by 0 in `tf.raw_ops.Conv2D`:&lt;/p&gt;
&lt;p&gt;```python
import tensorflow as tf&lt;/p&gt;
&lt;p&gt;input = tf.constant([], shape=[0, 0, 0, 0], dtype=tf.float32)
filter = tf.constant([], shape=[0, 0, 0, 0], dtype=tf.float32)&lt;/p&gt;
&lt;p&gt;strides = [1, 1, 1, 1]
padding = &amp;#34;SAME&amp;#34;
                               
tf.raw_ops.Conv2D(input=input, filter=filter, strides=strides, padding=padding)
```                            
                               
This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/988087bd83f144af14087fe4fecee2d250d93737/tensorflow/core/kernels/conv_ops.cc#L261-L263) does a division by a quantity that is controlled by the caller:
```cc
  const int64 patch_depth = filter.dim_size(2);
  if (in_depth % patch_depth != 0) { ... }
```
  
### Patches
We have patched the issue in GitHub commit [b12aa1d44352de21d1a6faaf04172d8c2508b42b](https://github.com/tensorflow/tensorflow/commit/b12aa1d44352de21d1a6faaf04172d8c2508b42b).
  
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.&lt;/p&gt;
&lt;p&gt;### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.&lt;/p&gt;
&lt;p&gt;### Attribution 
This vulnerability has been reported by Ying Wang and…&lt;/p&gt;</description>
      <content:encoded>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; PyPI: tensorflow, PyPI: tensorflow-cpu, PyPI: tensorflow-gpu&lt;/p&gt;
&lt;p&gt;### Impact
An attacker can trigger a division by 0 in `tf.raw_ops.Conv2D`:&lt;/p&gt;
&lt;p&gt;```python
import tensorflow as tf&lt;/p&gt;
&lt;p&gt;input = tf.constant([], shape=[0, 0, 0, 0], dtype=tf.float32)
filter = tf.constant([], shape=[0, 0, 0, 0], dtype=tf.float32)&lt;/p&gt;
&lt;p&gt;strides = [1, 1, 1, 1]
padding = &amp;#34;SAME&amp;#34;
                               
tf.raw_ops.Conv2D(input=input, filter=filter, strides=strides, padding=padding)
```                            
                               
This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/988087bd83f144af14087fe4fecee2d250d93737/tensorflow/core/kernels/conv_ops.cc#L261-L263) does a division by a quantity that is controlled by the caller:
```cc
  const int64 patch_depth = filter.dim_size(2);
  if (in_depth % patch_depth != 0) { ... }
```
  
### Patches
We have patched the issue in GitHub commit [b12aa1d44352de21d1a6faaf04172d8c2508b42b](https://github.com/tensorflow/tensorflow/commit/b12aa1d44352de21d1a6faaf04172d8c2508b42b).
  
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.&lt;/p&gt;
&lt;p&gt;### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.&lt;/p&gt;
&lt;p&gt;### Attribution 
This vulnerability has been reported by Ying Wang and…&lt;/p&gt;</content:encoded>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/ghsa-4vf2-4xcg-65cx</guid>
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