hawk-scanner 0.3.9

A powerful scanner to scan your Filesystem, S3, MongoDB, MySQL, PostgreSQL, Redis, Slack, Google Cloud Storage and Firebase storage for PII and sensitive data using text and OCR analysis. Hawk-eye can also analyse supports most of the file types like docx, xlsx, pptx, pdf, jpg, png, gif, zip, tar, rar, etc.

🦅 Hawk-eye

Find PII & Secrets like never before across your entire infrastructure with same tool!

Description • Installation • Features • Configuration • Acknowledgements

🦅 HAWK Eye - Highly Advanced Watchful Keeper Eye

HAWK Eye is a powerful and versatile CLI (Command-Line Interface) tool designed to be your vigilant watchkeeper, guarding against potential data breaches and cyber threats across various platforms. Inspired by the precision and vision of majestic birds of prey, HAWK Eye swiftly scans multiple data sources, including S3, MySQL, PostgreSQL, MongoDB, CouchDB, Google Drive, Slack, Redis, Firebase, filesystem, and Google Cloud buckets (GCS), for Personally Identifiable Information (PII) and secrets. It uses text analysis and OCR techniques to go throug most of the documents, database and different file types like docx, xlsx, pptx, pdf, jpg, png, gif, zip, tar, rar, etc.

Why "HAWK Eye"?

The name "HAWK Eye" captures the essence of a Highly Advanced Watchful Keeper. Like the keen vision of a hawk, this tool enables you to monitor and safeguard your data with precision and accuracy, ensuring data privacy and security.

HAWK Eye in Action

See how this works on Youtube - https://youtu.be/LuPXE7UJKOY

Installation via pip or pip3

   pip3 install hawk-scanner

Example working command (Use all/fs/s3/gcs etc...)

   hawk_scanner all --connection connection.yml --fingerprint fingerprint.yml --json output.json --debug

Note: Scanning Postgresql?, then you have to install some extra dependencies.

For scanning postgresql source, this tool requires psycopg2-binary dependency, we can't ship this dependency with main package because psycopg2-binary not works with most of the systems espically with Windows, so you have to install it manually.

   pip3 install psycopg2-binary

Building or running from source

HAWK Eye is a Python-based CLI tool that can be installed using the following steps:

1. Clone the HAWK Eye repository to your local machine.

      git clone https://github.com/rohitcoder/hawk-eye.git
   

2. Navigate to the HAWK Eye directory.
3. Run the following command to install the required dependencies:

      pip3 install -r requirements.txt
   

4. Create a connection.yml file in the root directory and add your connection profiles (see the "How to Configure HAWK Eye Connections" section for details).
5. Run the following command to install HAWK Eye:

      python3 hawk_scanner/main.py
   

Key features

• Swiftly scans multiple data sources (S3, MySQL, PostgreSQL, Redis, Firebase, filesystem, and GCS) for PII data and malware exposure.
• Advanced algorithms and deep scanning capabilities provide thorough security auditing.
• Real-time alerts and notifications keep you informed of potential data vulnerabilities using Slack and other integrations, with more coming soon.
• New command support for S3, MySQL, PostgreSQL, Redis, Firebase, filesystem, and GCS expands the tool's capabilities.
• --debug flag enables printing of all debugging output for comprehensive troubleshooting.
• Save output in JSON format using the --json flag and specify a file name like --json output.json.
• Proudly crafted with love and a sense of humor to make your security journey enjoyable and stress-free.

Usage

To unleash the power of HAWK Eye, simply follow the steps mentioned in the "Usage" section of the "README.md" file.

Options

Note: If you don't provide any command, it will run all commands (firebase, fs, gcs, mysql, postgresql, redis, s3) by default.

Option	Description
firebase	Scan Firebase profiles for PII and secrets data.
fs	Scan filesystem profiles for PII and secrets data.
gcs	Scan GCS (Google Cloud Storage) profiles for PII and secrets data.
mysql	Scan MySQL profiles for PII and secrets data.
mongodb	Scan MongoDB profiles for PII and secrets data.
couchdb	Scan CouchDB profiles for PII and secrets data.
slack	Scan slack profiles for PII and secrets data.
postgresql	Scan postgreSQL profiles for PII and secrets data.
redis	Scan Redis profiles for PII and secrets data.
s3	Scan S3 profiles for PII and secrets data.
gdrive	Scan Google drive profiles for PII and secrets data.
gdrive_workspace	Scan Google drive Workspace profiles for PII and secrets data.
--connection	Provide a connection YAML local file path like --connection connection.yml, this file will contain all creds and configs for different sources and other configurations.
--fingerprint	Provide a fingerprint file path like --fingerprint fingerprint.yml, this file will override default fingerprints.
--debug	Enable Debug mode.
--json	Provide --json file name to save output in json file like --json output.json
--shutup	Use --shutup flag if you want to hide Hawk ASCII art from your terminal 😁

How to Configure HAWK Eye Connections (Profiles in connection.yml)

HAWK Eye uses a YAML file to store connection profiles for various data sources. The connection.yml file is located in the config directory. You can add new profiles to this file to enable HAWK Eye to scan additional data sources. The following sections describe the process for adding new profiles to the connection.yml file.

Your connection fille will look like this

notify:
  redacted: True
  suppress_duplicates: True
  slack:
    webhook_url: https://hooks.slack.com/services/T0XXXXXXXXXXX/BXXXXXXXX/1CIyXXXXXXXXXXXXXXX

sources:
  redis:
    redis_example:
      host: YOUR_REDIS_HOST
  s3:
    s3_example:
      access_key: YOUR_S3_ACCESS_KEY
      secret_key: YOUR_S3_SECRET_KEY
      bucket_name: YOUR_S3_BUCKET_NAME
      cache: true
  gcs:
    gcs_example:
      credentials_file: /path/to/your/credential_file.json
      bucket_name: YOUR_GCS_BUCKET_NAME
      cache: true
      exclude_patterns:
        - .pdf
        - .docx
  firebase:
    firebase_example:
      credentials_file: /path/to/your/credential_file.json
      bucket_name: YOUR_FIREBASE_BUCKET_NAME
      cache: true
      exclude_patterns:
        - .pdf
        - .docx
  mysql:
    mysql_example:
      host: YOUR_MYSQL_HOST
      port: YOUR_MYSQL_PORT
      user: YOUR_MYSQL_USERNAME
      password: YOUR_MYSQL_PASSWORD
      database: YOUR_MYSQL_DATABASE_NAME
      limit_start: 0   # Specify the starting limit for the range
      limit_end: 500   # Specify the ending limit for the range
      tables:
        - table1
        - table2
  postgresql:
    postgresql_example:
      host: YOUR_POSTGRESQL_HOST
      port: YOUR_POSTGRESQL_PORT
      user: YOUR_POSTGRESQL_USERNAME
      password: YOUR_POSTGRESQL_PASSWORD
      database: YOUR_POSTGRESQL_DATABASE_NAME
      limit_start: 0   # Specify the starting limit for the range
      limit_end: 500   # Specify the ending limit for the range
      tables:
        - table1
        - table2
  mongodb:
    mongodb_example:
      uri: YOUR_MONGODB_URI
      host: YOUR_MONGODB_HOST
      port: YOUR_MONGODB_PORT
      username: YOUR_MONGODB_USERNAME
      password: YOUR_MONGODB_PASSWORD
      database: YOUR_MONGODB_DATABASE_NAME
      uri: YOUR_MONGODB_URI  # Use either URI or individual connection parameters
      limit_start: 0   # Specify the starting limit for the range
      limit_end: 500   # Specify the ending limit for the range
      collections:
        - collection1
        - collection2
  fs:
    fs_example:
      path: /path/to/your/filesystem/directory
      exclude_patterns:
        - .pdf
        - .docx
        - private
        - venv
        - node_modules
  
 gdrive:
    drive_example:
      folder_name:
      credentials_file: /Users/kumarohit/Downloads/client_secret.json ## this will be oauth app json file
      cache: true
      exclude_patterns:
        - .pdf
        - .docx

  gdrive_workspace:
    drive_example:
      folder_name:
      credentials_file: /Users/kumarohit/Downloads/client_secret.json ## this will be service account json file
      impersonate_users:
        - [e-mail]
        - [e-mail]
      cache: true
      exclude_patterns:
        - .pdf
        - .docx

  slack:
    slack_example:
      token: xoxp-XXXXXXXXXXXXXXXXXXXXXXXXX # get your slack app these permissiosn https://api.slack.com/methods/team.info and https://api.slack.com/methods/conversations.list
      channel_types: "public_channel,private_channel"
      # Optional: List of channel names to check
      # channel_names:
      #   - general
      #   - random

You can add or remove profiles from the connection.yml file as needed. You can also configure only one or two data sources if you don't need to scan all of them.

Adding New Commands

HAWK Eye's extensibility empowers developers to contribute new security commands. Here's how:

1. Fork the HAWK Eye repository to your GitHub account.
2. Create a new Python file for your security command inside the commands directory, with a descriptive name.
3. Define a function execute(args) within the new Python file, containing the logic for your command.
4. Provide clear documentation and comments explaining the purpose and usage of the new command.
5. Thoroughly test your command to ensure it works seamlessly and aligns with the existing features.
6. Submit a pull request from your branch to the main HAWK Eye repository.
7. The maintainers will review your contribution, provide feedback if needed, and merge your changes.

Contribution Guidelines

We welcome contributions from the open-source community to enhance HAWK Eye's capabilities in securing data sources. To contribute:

1. Fork the HAWK Eye repository to your GitHub account.
2. Create a new branch from the main branch for your changes.
3. Adhere to the project's coding standards and style guidelines.
4. Write clear and concise commit messages for your changes.
5. Include appropriate test cases for new features or modifications.
6. Update the "README.md" file to reflect any changes or new features.
7. Submit a pull request from your branch to the main branch of the HAWK Eye repository.
8. The maintainers will review your pull request and work with you to address any concerns.
9. After approval, your contributions will be merged into the main codebase.

Join the HAWK Eye community and contribute to data source security worldwide. For any questions or assistance, feel free to open an issue on the repository.

If you find HAWK Eye useful and would like to support the project, please consider making a donation. All 100% of the donations will be distributed to charities focused on education welfare and animal help.

Conferences and Talks

• Black Hat SecTor 2023 [Arsenal]
• Black Hat Middle East and Africa 2023 [Arsenal]
• Black Hat Europe 2023 [Arsenal]

💪 Contributors

We extend our heartfelt appreciation to all contributors who continuously improve this tool! Your efforts are essential in strengthening the security landscape. 🙏

Donation

How to Donate

Feel free to make a donation directly to the charities of your choice or send it to us, and we'll ensure it reaches the deserving causes. Just reach out to us on LinkedIn or Twitter to let us know about your contribution. Your generosity and support mean the world to us, and we can't wait to express our heartfelt gratitude.

Your donations will play a significant role in making a positive impact in the lives of those in need. Thank you for considering supporting our cause!