First published: Fri Nov 05 2021(Updated: )
### Impact The [shape inference code for `DeserializeSparse`](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/ops/sparse_ops.cc#L152-L168) can trigger a null pointer dereference: ```python import tensorflow as tf dataset = tf.data.Dataset.range(3) @tf.function def test(): y = tf.raw_ops.DeserializeSparse( serialized_sparse=tf.data.experimental.to_variant(dataset), dtype=tf.int32) test() ``` This is because the shape inference function assumes that the `serialize_sparse` tensor is a tensor with positive rank (and having `3` as the last dimension). However, in the example above, the argument is a scalar (i.e., rank 0). ### Patches We have patched the issue in GitHub commit [d3738dd70f1c9ceb547258cbb82d853da8771850](https://github.com/tensorflow/tensorflow/commit/d3738dd70f1c9ceb547258cbb82d853da8771850). The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, 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 | <2.4.4 | |
Google TensorFlow | >=2.5.0<2.5.2 | |
Google TensorFlow | =2.6.0 | |
pip/tensorflow-gpu | <2.4.4 | 2.4.4 |
pip/tensorflow-gpu | >=2.5.0<2.5.2 | 2.5.2 |
pip/tensorflow-gpu | >=2.6.0<2.6.1 | 2.6.1 |
pip/tensorflow-cpu | <2.4.4 | 2.4.4 |
pip/tensorflow-cpu | >=2.5.0<2.5.2 | 2.5.2 |
pip/tensorflow-cpu | >=2.6.0<2.6.1 | 2.6.1 |
pip/tensorflow | <2.4.4 | 2.4.4 |
pip/tensorflow | >=2.5.0<2.5.2 | 2.5.2 |
pip/tensorflow | >=2.6.0<2.6.1 | 2.6.1 |
<2.4.4 | ||
>=2.5.0<2.5.2 | ||
=2.6.0 |
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