CVE-2021-37640: Integer division by 0 in sparse reshaping in TensorFlow
First published: Thu Aug 12 2021(Updated: )
### Impact The implementation of `tf.raw_ops.SparseReshape` can be made to trigger an integral division by 0 exception: ```python import tensorflow as tf tf.raw_ops.SparseReshape( input_indices = np.ones((1,3)), input_shape = np.array([1,1,0]), new_shape = np.array([1,0])) ``` The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/reshape_util.cc#L176-L181) calls the reshaping functor whenever there is at least an index in the input but does not check that shape of the input or the target shape have both a non-zero number of elements. The [reshape functor](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/reshape_util.cc#L40-L78) blindly divides by the dimensions of the target shape. Hence, if this is not checked, code will result in a division by 0. ### Patches We have patched the issue in GitHub commit [4923de56ec94fff7770df259ab7f2288a74feb41](https://github.com/tensorflow/tensorflow/commit/4923de56ec94fff7770df259ab7f2288a74feb41). The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1 as this is the other affected version. ### 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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Reference Links
- https://github.com/tensorflow/tensorflow/commit/4923de56ec94fff7770df259ab7f2288a74feb41
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-95xm-g58g-3p88
- https://nvd.nist.gov/vuln/detail/CVE-2021-37640
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-553.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-751.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-262.yaml
- https://github.com/advisories/GHSA-95xm-g58g-3p88 (Advisory)
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