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      <title>CVE-2020-15194 — Denial of Service in Tensorflow</title>
      <link>https://cve.radiocsirt.org/vuln/cve-2020-15194</link>
      <description>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; tensorflow&lt;/p&gt;
&lt;p&gt;In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `SparseFillEmptyRowsGrad` implementation has incomplete validation of the shapes of its arguments. Although `reverse_index_map_t` and `grad_values_t` are accessed in a similar pattern, only `reverse_index_map_t` is validated to be of proper shape. Hence, malicious users can pass a bad `grad_values_t` to trigger an assertion failure in `vec`, causing denial of service in serving installations. The issue is patched in commit 390611e0d45c5793c7066110af37c8514e6a6c54, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.&amp;#34;&lt;/p&gt;</description>
      <content:encoded>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; tensorflow&lt;/p&gt;
&lt;p&gt;In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `SparseFillEmptyRowsGrad` implementation has incomplete validation of the shapes of its arguments. Although `reverse_index_map_t` and `grad_values_t` are accessed in a similar pattern, only `reverse_index_map_t` is validated to be of proper shape. Hence, malicious users can pass a bad `grad_values_t` to trigger an assertion failure in `vec`, causing denial of service in serving installations. The issue is patched in commit 390611e0d45c5793c7066110af37c8514e6a6c54, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.&amp;#34;&lt;/p&gt;</content:encoded>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/cve-2020-15194</guid>
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    <item>
      <title>GHSA-9mqp-7v2h-2382 — Denial of Service in Tensorflow</title>
      <link>https://cve.radiocsirt.org/vuln/ghsa-9mqp-7v2h-2382</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 `SparseFillEmptyRowsGrad` implementation has incomplete validation of the shapes of its arguments:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/sparse_fill_empty_rows_op.cc#L235-L241&lt;/p&gt;
&lt;p&gt;Although `reverse_index_map_t` and `grad_values_t` are accessed in a similar pattern, only `reverse_index_map_t` is validated to be of proper shape. Hence, malicious users can pass a bad `grad_values_t` to trigger an assertion failure in `vec`, causing denial of service in serving installations.&lt;/p&gt;
&lt;p&gt;### Patches
We have patched the issue in 390611e0d45c5793c7066110af37c8514e6a6c54 and will release a patch release for all affected versions.&lt;/p&gt;
&lt;p&gt;We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.&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;
&lt;p&gt;### Attribution
This vulnerability is a variant of [GHSA-63xm-rx5p-xvqr](https://github.com/tensorflow/tensorflow/security/advisories/GHSA-63xm-rx5p-xvqr)&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 `SparseFillEmptyRowsGrad` implementation has incomplete validation of the shapes of its arguments:
https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/sparse_fill_empty_rows_op.cc#L235-L241&lt;/p&gt;
&lt;p&gt;Although `reverse_index_map_t` and `grad_values_t` are accessed in a similar pattern, only `reverse_index_map_t` is validated to be of proper shape. Hence, malicious users can pass a bad `grad_values_t` to trigger an assertion failure in `vec`, causing denial of service in serving installations.&lt;/p&gt;
&lt;p&gt;### Patches
We have patched the issue in 390611e0d45c5793c7066110af37c8514e6a6c54 and will release a patch release for all affected versions.&lt;/p&gt;
&lt;p&gt;We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.&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;
&lt;p&gt;### Attribution
This vulnerability is a variant of [GHSA-63xm-rx5p-xvqr](https://github.com/tensorflow/tensorflow/security/advisories/GHSA-63xm-rx5p-xvqr)&lt;/p&gt;</content:encoded>
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