Vulnerability: Overflow/denial of service in `tf.raw_ops.ReverseSequence` ### Impact
The implementation of `tf.raw_ops.ReverseSequence` allows for stack overflow and/or `CHECK`-fail based denial of service.

```python
import tensorflow as tf

input = tf.zeros([1, 1, 1], dtype=tf.int32)
seq_lengths = tf.constant([0], shape=[1], dtype=tf.int32)

tf.raw_ops.ReverseSequence(
    input=input, seq_lengths=seq_lengths, seq_dim=-2, batch_dim=0)
```

The [implementation](https://github.com/tensorflow/tensorflow/blob/5b3b071975e01f0d250c928b2a8f901cd53b90a7/tensorflow/core/kernels/reverse_sequence_op.cc#L114-L118) fails to validate that `seq_dim` and `batch_dim` arguments are valid.
  
Negative values for `seq_dim` can result in stack overflow or `CHECK`-failure, depending on the version of Eigen code used to implement the operation. Similar behavior can be exhibited by invalid values of `batch_dim`.
  
### Patches
We have patched the issue in GitHub commit [ecf768cbe50cedc0a45ce1ee223146a3d3d26d23](https://github.com/tensorflow/tensorflow/commit/ecf768cbe50cedc0a45ce1ee223146a3d3d26d23).

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.

### 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 Ying Wang and Yakun Zhang of Baidu X-Team.
Vulnerability ID: GHSA-6qgm-fv6v-rfpv
CWE: CWE-120
Severity score: 2.5
Project: https://github.com/tensorflow/tensorflow
Published: 2021-05-21
File: tensorflow/core/kernels/reverse_sequence_op.cc
Commit message: Add missing validations to reverse_sequence_op

PiperOrigin-RevId: 372178683
Change-Id: Iac97ebab5b342f1262c77a7d9bcb4267b305ce5b
Commit author: Mihai Maruseac

Vulnerable version (before fix):
 class ReverseSequenceOp : public OpKernel {       : OpKernel(context) {     OP_REQUIRES_OK(context, context->GetAttr("batch_dim", &batch_dim_));     OP_REQUIRES_OK(context, context->GetAttr("seq_dim", &seq_dim_));   }    void Compute(OpKernelContext* context) override {

Fixed version (after fix):
 class ReverseSequenceOp : public OpKernel {       : OpKernel(context) {     OP_REQUIRES_OK(context, context->GetAttr("batch_dim", &batch_dim_));     OP_REQUIRES_OK(context, context->GetAttr("seq_dim", &seq_dim_));     OP_REQUIRES(context, batch_dim_ >= 0,                 errors::InvalidArgument("Invalid batch_dim ", batch_dim_));     OP_REQUIRES(context, seq_dim_ >= 0,                 errors::InvalidArgument("Invalid seq_dim ", seq_dim_));   }    void Compute(OpKernelContext* context) override {

Patch:
patch: @@ -115,6 +115,10 @@ class ReverseSequenceOp : public OpKernel {
       : OpKernel(context) {
     OP_REQUIRES_OK(context, context->GetAttr("batch_dim", &batch_dim_));
     OP_REQUIRES_OK(context, context->GetAttr("seq_dim", &seq_dim_));
+    OP_REQUIRES(context, batch_dim_ >= 0,
+                errors::InvalidArgument("Invalid batch_dim ", batch_dim_));
+    OP_REQUIRES(context, seq_dim_ >= 0,
+                errors::InvalidArgument("Invalid seq_dim ", seq_dim_));
   }
 
   void Compute(OpKernelContext* context) override {
path: tensorflow/core/kernels/reverse_sequence_op.cc