medium
5.5
CWE
190
Advisory Published
Advisory Published
Updated

CVE-2021-41198: Overflow/crash in `tf.tile` when tiling tensor is large

First published: Fri Nov 05 2021(Updated: )

### 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).

Credit: security-advisories@github.com security-advisories@github.com

Affected SoftwareAffected VersionHow to fix
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
TensorFlow Keras<2.4.4
TensorFlow Keras>=2.5.0<2.5.2
TensorFlow Keras>=2.6.0<2.6.1

Remedy

https://github.com/tensorflow/tensorflow/commit/9294094df6fea79271778eb7e7ae1bad8b5ef98f

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Reference Links

Frequently Asked Questions

  • What is the severity of CVE-2021-41198?

    The CVE-2021-41198 vulnerability has been rated as a high severity issue due to the risk of process crashes.

  • How do I fix CVE-2021-41198?

    To remediate CVE-2021-41198, upgrade your TensorFlow installation to version 2.4.4 or to a version between 2.5.0 and 2.5.2 or 2.6.0 and 2.6.1.

  • What systems are vulnerable to CVE-2021-41198?

    CVE-2021-41198 affects TensorFlow versions prior to 2.4.4, between 2.5.0 and 2.5.2, and between 2.6.0 and 2.6.1.

  • What is the impact of CVE-2021-41198?

    The impact of CVE-2021-41198 results in TensorFlow crashing when a large input argument is passed to the tf.tile function.

  • Can CVE-2021-41198 be exploited remotely?

    CVE-2021-41198 requires local access to exploit, as it involves calling a specific TensorFlow function with crafted inputs.

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