First published: Thu Aug 12 2021(Updated: )
### Impact The implementation of `tf.raw_ops.SparseDenseCwiseDiv` is vulnerable to a division by 0 error: ```python import tensorflow as tf import numpy as np tf.raw_ops.SparseDenseCwiseDiv( sp_indices=np.array([[4]]), sp_values=np.array([-400]), sp_shape=np.array([647.]), dense=np.array([0])) ``` The [implementation](https://github.com/tensorflow/tensorflow/blob/a1bc56203f21a5a4995311825ffaba7a670d7747/tensorflow/core/kernels/sparse_dense_binary_op_shared.cc#L56) uses a common class for all binary operations but fails to treat the division by 0 case separately. ### Patches We have patched the issue in GitHub commit [d9204be9f49520cdaaeb2541d1dc5187b23f31d9](https://github.com/tensorflow/tensorflow/commit/d9204be9f49520cdaaeb2541d1dc5187b23f31d9). The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. ### 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. ### Attribution This vulnerability has been reported by members of the Aivul Team from Qihoo 360.
Credit: security-advisories@github.com security-advisories@github.com
Affected Software | Affected Version | How to fix |
---|---|---|
Google TensorFlow | >=2.3.0<2.3.4 | |
Google TensorFlow | >=2.4.0<2.4.3 | |
Google TensorFlow | =2.5.0 | |
Google TensorFlow | =2.6.0-rc0 | |
Google TensorFlow | =2.6.0-rc1 | |
Google TensorFlow | =2.6.0-rc2 | |
pip/tensorflow-gpu | =2.5.0 | 2.5.1 |
pip/tensorflow-gpu | >=2.4.0<2.4.3 | 2.4.3 |
pip/tensorflow-gpu | <2.3.4 | 2.3.4 |
pip/tensorflow-cpu | =2.5.0 | 2.5.1 |
pip/tensorflow-cpu | >=2.4.0<2.4.3 | 2.4.3 |
pip/tensorflow-cpu | <2.3.4 | 2.3.4 |
pip/tensorflow | =2.5.0 | 2.5.1 |
pip/tensorflow | >=2.4.0<2.4.3 | 2.4.3 |
pip/tensorflow | <2.3.4 | 2.3.4 |
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