Vulnerability: Missing validation in shape inference for `Dequantize` ### Impact
The shape inference code for `tf.raw_ops.Dequantize` has a vulnerability that could trigger a denial of service via a segfault if an attacker provides invalid arguments:

```python
import tensorflow as tf

tf.compat.v1.disable_v2_behavior()
tf.raw_ops.Dequantize(
  input_tensor = tf.constant(-10.0, dtype=tf.float32),
  input_tensor = tf.cast(input_tensor, dtype=tf.quint8),
  min_range = tf.constant([], shape=[0], dtype=tf.float32),
  max_range = tf.constant([], shape=[0], dtype=tf.float32),
  mode  = 'MIN_COMBINED',
  narrow_range=False,
  axis=-10,
  dtype=tf.dtypes.float32)
```

The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/ops/array_ops.cc#L2999-L3014) uses `axis` to select between two different values for `minmax_rank` which is then used to retrieve tensor dimensions. However, code assumes that `axis` can be either `-1` or a value greater than `-1`, with no validation for the other values.

### Patches
We have patched the issue in GitHub commit [da857cfa0fde8f79ad0afdbc94e88b5d4bbec764](https://github.com/tensorflow/tensorflow/commit/da857cfa0fde8f79ad0afdbc94e88b5d4bbec764).

The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, 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 Yakun Zhang of Baidu Security.
Vulnerability ID: GHSA-qfpc-5pjr-mh26
CWE: CWE-20
Severity score: 5.5
Project: https://github.com/tensorflow/tensorflow
Published: 2021-08-25
File: tensorflow/core/ops/array_ops.cc
Commit message: Fix a shape inference issue leading to nullptr deref.

PiperOrigin-RevId: 387712259
Change-Id: I7e670772b259c068a501a187cd89f18773bb95a1
Commit author: Mihai Maruseac

Vulnerable version (before fix):
 REGISTER_OP("Dequantize")       if (!s.ok() && s.code() != error::NOT_FOUND) {         return s;       }       const int minmax_rank = (axis == -1) ? 0 : 1;       TF_RETURN_IF_ERROR(shape_inference::UnchangedShape(c));       ShapeHandle minmax;

Fixed version (after fix):
 REGISTER_OP("Dequantize")       if (!s.ok() && s.code() != error::NOT_FOUND) {         return s;       }       if (axis < -1) {         return errors::InvalidArgument("axis should be at least -1, got ",                                        axis);       }       const int minmax_rank = (axis == -1) ? 0 : 1;       TF_RETURN_IF_ERROR(shape_inference::UnchangedShape(c));       ShapeHandle minmax;

Patch:
patch: @@ -2990,6 +2990,10 @@ REGISTER_OP("Dequantize")
       if (!s.ok() && s.code() != error::NOT_FOUND) {
         return s;
       }
+      if (axis < -1) {
+        return errors::InvalidArgument("axis should be at least -1, got ",
+                                       axis);
+      }
       const int minmax_rank = (axis == -1) ? 0 : 1;
       TF_RETURN_IF_ERROR(shape_inference::UnchangedShape(c));
       ShapeHandle minmax;
path: tensorflow/core/ops/array_ops.cc