GHSA-95xm-g58g-3p88

Dashboard / Vulnerabilities / GHSA-95xm-g58g-3p88

GHSA-95xm-g58g-3p88

Summary: Integer division by 0 in sparse reshaping

Details: ### 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.

References: https://github.com/tensorflow/tensorflow/security/advisories/GHSA-95xm-g58g-3p88, https://nvd.nist.gov/vuln/detail/CVE-2021-37640, https://github.com/tensorflow/tensorflow/commit/4923de56ec94fff7770df259ab7f2288a74feb41, 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/tensorflow/tensorflow