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    <link>https://vulnerability.circl.lu</link>
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      <title>CVE-2022-41900 — FractionalMaxPool and FractionalAVGPool heap out-of-bounds acess in Tensorflow</title>
      <link>https://vulnerability.circl.lu/vuln/cve-2022-41900</link>
      <description>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; tensorflow&lt;/p&gt;
&lt;p&gt;TensorFlow is an open source platform for machine learning. The security vulnerability results in FractionalMax(AVG)Pool with illegal pooling_ratio. Attackers using Tensorflow can exploit the vulnerability. They can access heap memory which is not in the control of user, leading to a crash or remote code execution. We have patched the issue in GitHub commit 216525144ee7c910296f5b05d214ca1327c9ce48. The fix will be included in TensorFlow 2.11.0. We will also cherry pick this commit on TensorFlow 2.10.1.&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 open source platform for machine learning. The security vulnerability results in FractionalMax(AVG)Pool with illegal pooling_ratio. Attackers using Tensorflow can exploit the vulnerability. They can access heap memory which is not in the control of user, leading to a crash or remote code execution. We have patched the issue in GitHub commit 216525144ee7c910296f5b05d214ca1327c9ce48. The fix will be included in TensorFlow 2.11.0. We will also cherry pick this commit on TensorFlow 2.10.1.&lt;/p&gt;</content:encoded>
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    <item>
      <title>GHSA-xvwp-h6jv-7472 — FractionalMaxPool and FractionalAVGPool heap out-of-bounds acess</title>
      <link>https://vulnerability.circl.lu/vuln/ghsa-xvwp-h6jv-7472</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 input `pooling_ratio` that is smaller than 1 will trigger a heap OOB in [`tf.raw_ops.FractionalMaxPool`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/fractional_max_pool_op.cc) and [`tf.raw_ops.FractionalAvgPool`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/fractional_avg_pool_op.cc).&lt;/p&gt;
&lt;p&gt;### Patches
We have patched the issue in GitHub commit [216525144ee7c910296f5b05d214ca1327c9ce48](https://github.com/tensorflow/tensorflow/commit/216525144ee7c910296f5b05d214ca1327c9ce48).&lt;/p&gt;
&lt;p&gt;The fix will be included in TensorFlow 2.11.0. We will also cherry pick this commit on TensorFlow 2.10.1.&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;</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 input `pooling_ratio` that is smaller than 1 will trigger a heap OOB in [`tf.raw_ops.FractionalMaxPool`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/fractional_max_pool_op.cc) and [`tf.raw_ops.FractionalAvgPool`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/fractional_avg_pool_op.cc).&lt;/p&gt;
&lt;p&gt;### Patches
We have patched the issue in GitHub commit [216525144ee7c910296f5b05d214ca1327c9ce48](https://github.com/tensorflow/tensorflow/commit/216525144ee7c910296f5b05d214ca1327c9ce48).&lt;/p&gt;
&lt;p&gt;The fix will be included in TensorFlow 2.11.0. We will also cherry pick this commit on TensorFlow 2.10.1.&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;</content:encoded>
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