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GHSA-2p25-55c9-h58q

Overflow/crash in `tf.tile` when tiling tensor is large

Source: GitHub Advisory Database (reviewed) Moderate CVE-2021-41198

Packages

EcosystemPackageAffectedFixed in
PyPI tensorflow >= 2.6.0, < 2.6.1 2.6.1
PyPI tensorflow >= 2.5.0, < 2.5.2 2.5.2
PyPI tensorflow < 2.4.4 2.4.4
PyPI tensorflow-cpu >= 2.6.0, < 2.6.1 2.6.1
PyPI tensorflow-cpu >= 2.5.0, < 2.5.2 2.5.2
PyPI tensorflow-cpu < 2.4.4 2.4.4
PyPI tensorflow-gpu >= 2.6.0, < 2.6.1 2.6.1
PyPI tensorflow-gpu >= 2.5.0, < 2.5.2 2.5.2
PyPI tensorflow-gpu < 2.4.4 2.4.4

Details

As written in the advisory (Markdown source, shown as plain text).

### Impact If `tf.tile` is called with a large input argument then the TensorFlow process will crash due to a `CHECK`-failure caused by an overflow. ```python import tensorflow as tf import numpy as np tf.keras.backend.tile(x=np.ones((1,1,1)), n=[100000000,100000000, 100000000]) ``` The number of elements in the output tensor is too much for the `int64_t` type and the overflow is detected via a `CHECK` statement. This aborts the process. ### Patches We have patched the issue in GitHub commit [9294094df6fea79271778eb7e7ae1bad8b5ef98f](https://github.com/tensorflow/tensorflow/commit/9294094df6fea79271778eb7e7ae1bad8b5ef98f) (merging [#51138](https://github.com/tensorflow/tensorflow/pull/51138)). 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 externally via a [GitHub issue](https://github.com/tensorflow/tensorflow/issues/46911).

References

External links from the advisory. They lead to third-party sites.