Credsweeper

What's Changed
* MlValidator object is created once
* CredSweeper is installed with pip as CLI tool additionally
* CredSweeper may be used as github action
* Added size limit option to skip large files in scan

Changes:
- change TF to ONNX for faster runtime https://github.com/Samsung/CredSweeper/pull/96
- change default number of threads to 1 https://github.com/Samsung/CredSweeper/pull/83
- optional find files by extension https://github.com/Samsung/CredSweeper/pull/101
- modified JWT pattern to improve metrics https://github.com/Samsung/CredSweeper/pull/104
- style fixes, type fixes, duplicate code removal

Change list:
- Limit max `tensorflow` version by `<2.8.0` due to the new `tensorflow` release that changes API

Fix issue with tensorflow:

$ python -m credsweeper --path tests/samples/password --ml_validation
Traceback (most recent call last):
File "/home/user/CredSweeper/credsweeper/ml_model/ml_validator.py", line 12, in <module>
from tensorflow.python.keras.preprocessing.sequence import pad_sequences
ModuleNotFoundError: No module named 'tensorflow.python.keras.preprocessing'



New `tensorflow==2.8.0` might be supported in `1.2.2`, `1.3.0` or later versions

Short description:
- Make execution time ~5x faster
- Less CLI output if result is saved to json
- Fix crash in case of non-utf default system encoding
- Add option to specify ML threshold (less or more sensitive)
- New field in the output: float "ml_probability" which is non empty if ml validation was used


Please note:
Faster execution partially based on changes to the [`credsweeper/rules/config.yaml`](https://github.com/Samsung/CredSweeper/blob/main/credsweeper/rules/config.yaml)
**If you modified this file in your deployment - please apply similar modifications to a newer version!**

Change list:
- Add diff scan for `.patch` files. See `--diff_path PATH` CLI argument
- Add support for non UTF-8 encoding in files
- Add 5 new regex rules: Firebase Domain, AWS S3 Bucket, Nonce, Salt, Certificate
- New severity type: Info
- Update ML model. Retrain it with new rules (mentioned above) and updated dataset
- Add batching for ML model, so it would run in parallel (or even on GPU if `tensorflow-gpu` configured by the user)
- Add value field for the output

Add fist release on pypi: https://pypi.org/project/credsweeper/

Bring up CredSweeper