medium
5.5
CWE
190
Advisory Published
Advisory Published
Updated

CVE-2021-41199: Overflow/crash in `tf.image.resize` when size is large

First published: Fri Nov 05 2021(Updated: )

### Impact If `tf.image.resize` 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.layers.UpSampling2D( size=1610637938, data_format='channels_first', interpolation='bilinear')(np.ones((5,1,1,1))) ``` 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 [e5272d4204ff5b46136a1ef1204fc00597e21837](https://github.com/tensorflow/tensorflow/commit/e5272d4204ff5b46136a1ef1204fc00597e21837) (merging [#51497](https://github.com/tensorflow/tensorflow/pull/51497)). 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/46914).

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

Remedy

https://github.com/tensorflow/tensorflow/commit/e5272d4204ff5b46136a1ef1204fc00597e21837

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Reference Links

Frequently Asked Questions

  • What is the severity of CVE-2021-41199?

    CVE-2021-41199 has a high severity rating due to the potential for crashes in the TensorFlow process on large input arguments.

  • How do I fix CVE-2021-41199?

    To fix CVE-2021-41199, update TensorFlow to version 2.4.4 or higher, specifically to versions 2.5.2 or 2.6.1.

  • Which versions of TensorFlow are affected by CVE-2021-41199?

    CVE-2021-41199 affects TensorFlow versions prior to 2.4.4 as well as 2.5.0 and 2.6.0.

  • What causes the crash in CVE-2021-41199?

    The crash is caused by a CHECK-failure due to an overflow when calling tf.image.resize with a large input argument.

  • Is CVE-2021-41199 a remote attack vector?

    CVE-2021-41199 does not provide a remote attack vector as it requires local execution of the TensorFlow code with specific inputs.

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