Advisory Package Curation

Integer division by 0 in sparse reshaping ### 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.

Integer division by 0 in sparse reshaping 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])) ```

Integer division by 0 in sparse reshaping 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])) ```

Integer division by 0 in sparse reshaping 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])) ```

TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.SparseReshape` can be made to trigger an integral division by 0 exception. 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. We have patched the issue in GitHub 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.

TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.SparseReshape` can be made to trigger an integral division by 0 exception. 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. We have patched the issue in GitHub 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.

TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.SparseReshape` can be made to trigger an integral division by 0 exception. 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. We have patched the issue in GitHub 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.

TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.SparseReshape` can be made to trigger an integral division by 0 exception. 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. We have patched the issue in GitHub 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.

TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.SparseReshape` can be made to trigger an integral division by 0 exception. 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. We have patched the issue in GitHub 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.

TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.SparseReshape` can be made to trigger an integral division by 0 exception. 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. We have patched the issue in GitHub 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.