Vulnerability: Out of bounds read in Tensorflow ### Impact 
The [implementation of shape inference for `ReverseSequence`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/ops/array_ops.cc#L1636-L1671) does not fully validate the value of `batch_dim` and can result in a heap OOB read:

```python
import tensorflow as tf

@tf.function
def test():
  y = tf.raw_ops.ReverseSequence(
    input = ['aaa','bbb'],
    seq_lengths = [1,1,1],
    seq_dim = -10,
    batch_dim = -10 )
  return y
    
test()
```

There is a check to make sure the value of `batch_dim` does not go over the rank of the input, but there is no check for negative values:

```cc
  const int32_t input_rank = c->Rank(input);
  if (batch_dim >= input_rank) {
    return errors::InvalidArgument( 
        "batch_dim must be < input rank: ", batch_dim, " vs. ", input_rank);
  }
  // ...
  
  DimensionHandle batch_dim_dim = c->Dim(input, batch_dim);
``` 
    
Negative dimensions are allowed in some cases to mimic Python's negative indexing (i.e., indexing from the end of the array), however if the value is too negative then [the implementation of `Dim`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/shape_inference.h#L415-L428) would access elements before the start of an array:

```cc
  DimensionHandle Dim(ShapeHandle s, int64_t idx) {
    if (!s.Handle() || s->rank_ == kUnknownRank) {
      return UnknownDim();
    }
    return DimKnownRank(s, idx);
  } 
·
  static DimensionHandle DimKnownRank(ShapeHandle s, int64_t idx) {
    CHECK_NE(s->rank_, kUnknownRank);
    if (idx < 0) {
      return s->dims_[s->dims_.size() + idx];
    }
    return s->dims_[idx];
  }
```

### Patches
We have patched the issue in GitHub commit [37c01fb5e25c3d80213060460196406c43d31995](https://github.com/tensorflow/tensorflow/commit/37c01fb5e25c3d80213060460196406c43d31995).

The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, 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 Yu Tian of Qihoo 360 AIVul Team.
Vulnerability ID: GHSA-6gmv-pjp9-p8w8
CWE: CWE-125
Severity score: 8.1
Project: https://github.com/tensorflow/tensorflow
Published: 2022-02-09
File: tensorflow/core/ops/array_ops.cc
Commit message: Fix out of bound error in ReverseSequence Op shape function

PiperOrigin-RevId: 411896080
Change-Id: I7e59a38e2f960886edf2b6c54ed5a84e86a9b193
Commit author: Isha Arkatkar

Vulnerable version (before fix):
 REGISTER_OP("ReverseSequence")         return errors::InvalidArgument(             "batch_dim must be < input rank: ", batch_dim, " vs. ", input_rank);       }       if (seq_dim >= input_rank) {         return errors::InvalidArgument(             "seq_dim must be < input rank: ", seq_dim, " vs. ", input_rank);       }        DimensionHandle batch_dim_dim = c->Dim(input, batch_dim);       TF_RETURN_IF_ERROR(           c->Merge(batch_dim_dim, c->Dim(seq_lens_shape, 0), &batch_dim_dim));

Fixed version (after fix):
 REGISTER_OP("ReverseSequence")         return errors::InvalidArgument(             "batch_dim must be < input rank: ", batch_dim, " vs. ", input_rank);       }        if (seq_dim >= input_rank) {         return errors::InvalidArgument(             "seq_dim must be < input rank: ", seq_dim, " vs. ", input_rank);       }        // To prevent out of bound access when calling c->Dim(input, batch_dim),       // batch_dim range [-1 * input rank, input rank) is allowed. However,       // the op implementation has a stricter bound for batch_dim requiring >= 0       // value. Thus, perform strict check here.       if (batch_dim < 0) {         return errors::InvalidArgument("batch_dim must be >=0, got ",                                        batch_dim);       }        DimensionHandle batch_dim_dim = c->Dim(input, batch_dim);       TF_RETURN_IF_ERROR(           c->Merge(batch_dim_dim, c->Dim(seq_lens_shape, 0), &batch_dim_dim));

Patch:
patch: @@ -1653,11 +1653,21 @@ REGISTER_OP("ReverseSequence")
         return errors::InvalidArgument(
             "batch_dim must be < input rank: ", batch_dim, " vs. ", input_rank);
       }
+
       if (seq_dim >= input_rank) {
         return errors::InvalidArgument(
             "seq_dim must be < input rank: ", seq_dim, " vs. ", input_rank);
       }
 
+      // To prevent out of bound access when calling c->Dim(input, batch_dim),
+      // batch_dim range [-1 * input rank, input rank) is allowed. However,
+      // the op implementation has a stricter bound for batch_dim requiring >= 0
+      // value. Thus, perform strict check here.
+      if (batch_dim < 0) {
+        return errors::InvalidArgument("batch_dim must be >=0, got ",
+                                       batch_dim);
+      }
+
       DimensionHandle batch_dim_dim = c->Dim(input, batch_dim);
       TF_RETURN_IF_ERROR(
           c->Merge(batch_dim_dim, c->Dim(seq_lens_shape, 0), &batch_dim_dim));
path: tensorflow/core/ops/array_ops.cc