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      <title>CVE-2022-21735 — Division by zero in Tensorflow</title>
      <link>https://cve.radiocsirt.org/vuln/cve-2022-21735</link>
      <description>&lt;p&gt;Tensorflow is an Open Source Machine Learning Framework. The implementation of `FractionalMaxPool` can be made to crash a TensorFlow process via a division by 0. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.&lt;/p&gt;</description>
      <content:encoded>&lt;p&gt;Tensorflow is an Open Source Machine Learning Framework. The implementation of `FractionalMaxPool` can be made to crash a TensorFlow process via a division by 0. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.&lt;/p&gt;</content:encoded>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/cve-2022-21735</guid>
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    <item>
      <title>GHSA-87v6-crgm-2gfj — Division by zero in Tensorflow</title>
      <link>https://cve.radiocsirt.org/vuln/ghsa-87v6-crgm-2gfj</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 
The [implementation of `FractionalMaxPool`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/fractional_max_pool_op.cc#L36-L192) can be made to crash a TensorFlow process via a division by 0:&lt;/p&gt;
&lt;p&gt;```python
import tensorflow as tf
import numpy as np&lt;/p&gt;
&lt;p&gt;tf.raw_ops.FractionalMaxPool(
  value=tf.constant(value=[[[[1, 4, 2, 3]]]], dtype=tf.int64),
  pooling_ratio=[1.0, 1.44, 1.73, 1.0],
  pseudo_random=False,
  overlapping=False,
  deterministic=False,
  seed=0,
  seed2=0,
  name=None)
```&lt;/p&gt;
&lt;p&gt;### Patches
We have patched the issue in GitHub commit [ba4e8ac4dc2991e350d5cc407f8598c8d4ee70fb](https://github.com/tensorflow/tensorflow/commit/ba4e8ac4dc2991e350d5cc407f8598c8d4ee70fb).&lt;/p&gt;
&lt;p&gt;The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, 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 Faysal Hossain Shezan from University of Virginia.&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 
The [implementation of `FractionalMaxPool`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/fractional_max_pool_op.cc#L36-L192) can be made to crash a TensorFlow process via a division by 0:&lt;/p&gt;
&lt;p&gt;```python
import tensorflow as tf
import numpy as np&lt;/p&gt;
&lt;p&gt;tf.raw_ops.FractionalMaxPool(
  value=tf.constant(value=[[[[1, 4, 2, 3]]]], dtype=tf.int64),
  pooling_ratio=[1.0, 1.44, 1.73, 1.0],
  pseudo_random=False,
  overlapping=False,
  deterministic=False,
  seed=0,
  seed2=0,
  name=None)
```&lt;/p&gt;
&lt;p&gt;### Patches
We have patched the issue in GitHub commit [ba4e8ac4dc2991e350d5cc407f8598c8d4ee70fb](https://github.com/tensorflow/tensorflow/commit/ba4e8ac4dc2991e350d5cc407f8598c8d4ee70fb).&lt;/p&gt;
&lt;p&gt;The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, 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 Faysal Hossain Shezan from University of Virginia.&lt;/p&gt;</content:encoded>
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