Check fail can be triggered in `tf.raw_ops.GatherV2` under jit compile mode.
Hi @Lyutoon ,

Please report check fails and other vulnerabilities [here](https://bughunters.google.com/). For more details, please check https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md and follow the instrcutions.

I have replicated the reported behaviour with tf-nightly(2.14.0-dev20230601) in colab and attached screenshot below.Check fail observed with jit_compile=True and without jit compile an exception is raised.

<img width="1498" alt="Screenshot 2023-06-02 at 11 20 45 AM" src="https://github.com/tensorflow/tensorflow/assets/116063290/61a5f1fc-f7b6-46bf-8bf9-6451329346da">

Thanks!
 Hi, thanks for your reply!

But here I noticed that in `SECURITY.md`, it said "**we will no longer consider assertion failures (e.g., CHECK-fails) as vulnerabilities**". 
So I'm wondering that if I still need to report these problem via google VRP? Or what is the proper way to report these kind of problems?

Thanks! Hi @Lyutoon ,

Check-fails may not be considered as vulnerabilities currently for rewarding the reporters but credit will be given for those who reported through proper channel. But still Engineering team will take a call on the issue based on severity and we are instructed to motivate the users to report check fails also in the attached forum above.

Request you to please report the issues there also. Thanks! This issue is stale because it has been open for 7 days with no activity. It will be closed if no further activity occurs. Thank you.
<details><summary>Click to expand!</summary> 
 
 ### Issue Type

Bug

### Have you reproduced the bug with TF nightly?

Yes

### Source

source

### Tensorflow Version

2.14.0

### Custom Code

Yes

### OS Platform and Distribution

Ubuntu 20.04

### Mobile device

Ubuntu 20.04

### Python version

3.8.10

### Bazel version

_No response_

### GCC/Compiler version

_No response_

### CUDA/cuDNN version

_No response_

### GPU model and memory

_No response_

### Current Behaviour?

Check fail can be triggered in `tf.raw_ops.GatherV2` under jit compile mode. While in normal mode, it won't be triggered but through an `InvalidArgumentError`.

### Standalone code to reproduce the issue

```shell
import os 
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
import tensorflow as tf
import numpy as np

params=tf.random.uniform([4], dtype=tf.dtypes.float32, maxval=100000000)
indices=tf.random.uniform([4, 0], dtype=tf.dtypes.int32, minval=-10000, maxval=60000)
axis=tf.random.uniform([], dtype=tf.dtypes.int64, minval=-100000000, maxval=1000000000)
batch_dims=11282

@tf.function(jit_compile=True)
def fuzz_jit():
    y = tf.raw_ops.GatherV2(params=params, indices=indices, axis=axis, batch_dims=batch_dims)
    return y

def fuzz_normal():
    y = tf.raw_ops.GatherV2(params=params, indices=indices, axis=axis, batch_dims=batch_dims)
    return y

y1 = fuzz_jit()  # trigger the check fail under jit compile mode.
print('[+] JIT ok')
y2 = fuzz_normal()  # if you run y2 first, it will through error rather than check fail.
print('[+] Normal ok')
```


### Relevant log output

```shell
% python test.py
2023-06-02 11:10:06.042625: F tensorflow/core/framework/shape_inference.cc:705] Check failed: rank >= 0 (0 vs. -11280)rank must not be negative
zsh: abort (core dumped)  python test.py
```
</details>