Find PII & Secrets like never before across your entire infrastructure with same tool!
Description • Installation • Features • Configuration • Acknowledgements
HAWK Eye is a robust, command-line tool built to safeguard against data breaches and cyber threats. Much like the sharp vision of a hawk, it quickly scans multiple data sources—S3, MySQL, PostgreSQL, MongoDB, CouchDB, Google Drive, Slack, Redis, Firebase, file systems, and Google Cloud buckets (GCS)—for Personally Identifiable Information (PII) and secrets. Using advanced text analysis and OCR techniques, HAWK Eye delves into various document formats like docx, xlsx, pptx, pdf, images (jpg, png, gif), compressed files (zip, tar, rar), and even video files to ensure comprehensive protection across platforms.
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.
For commercial support and help with HAWK Eye, please contact us at LinkedIn or Twitter.
See how this works on Youtube - https://youtu.be/LuPXE7UJKOY
pip3 install hawk-scannerdocker run --rm \
--platform linux/amd64 \
-v /Users/kumarohit/Desktop/Projects/hawk-eye/connection.yml:/app/connection.yml \
-v /Users/kumarohit/Desktop/Projects/hawk-eye/fingerprint.yml:/app/fingerprint.yml \
rohitcoder/hawk-eye \
slack --connection /app/connection.yml --fingerprint /app/fingerprint.yml
Just mount connection.yml and fingerprint.yml file in the container and run the command you want to run.
-
Example working command (Use all/fs/s3/gcs etc...)
hawk_scanner all --connection connection.yml --fingerprint fingerprint.yml --json output.json --debug
-
Pass connection data as CLI input in --connection-json flag, and output in json data (Helpful for CI/CD pipeline or automation)
hawk_scanner fs --connection-json '{"sources": {"fs": {"fs1": {"quick_scan": true, "path": "/Users/rohitcoder/Downloads/data/KYC_PDF.pdf"}}}}' --stdout --quiet --fingerprint fingerprint.yml -
You can also import Hawk-eye in your own python scripts and workflows, for better flexibility
from hawk_scanner.internals import system pii = system.scan_file("/Users/kumarohit/Downloads/Resume.pdf") print(pii)
-
You can also import Hawk-eye with custom fingerprints in your own python scripts like this
from hawk_scanner.internals import system
pii = system.scan_file("/Users/kumarohit/Downloads/Resume.pdf", {
"fingerprint": {
"Email": '[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\\.[A-Za-z]{2,}',
}
)
print(pii)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-binaryYou may get error after running hawk-scanner command on redhat from cv2 dependency . You need to install some extra dependencies
yum install mesa-libGL
HAWK Eye is a Python-based CLI tool that can be installed using the following steps:
- Clone the HAWK Eye repository to your local machine.
git clone https://github.com/rohitcoder/hawk-eye.git
- Navigate to the HAWK Eye directory.
- Run the following command to install the required dependencies:
pip3 install -r requirements.txt
- 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).
- Run the following command to install HAWK Eye:
python3 hawk_scanner/main.py
- 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.
--debugflag 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.
To unleash the power of HAWK Eye, simply follow the steps mentioned in the "Usage" section of the "README.md" file.
Note: If you don't provide any command, it will run all commands (firebase, fs, gcs, mysql, text, couchdb, gdrive, gdrive workspace, slack, 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. |
| text | Scan text or string 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. |
| --connection-json | Provide a connection json as CLI Input, helpful when you want to run this tool in CI/CD pipeline or automation. |
| --fingerprint | Provide a fingerprint file path like --fingerprint fingerprint.yml, this file will override default fingerprints. |
| --debug | Enable Debug mode. |
| --stdout | Print output on stdout or terminal. |
| --quiet | Use --quiet flag if you want to hide all logs from your terminal. |
| --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 😁 |
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.
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
password: YOUR_REDIS_PASSWORD
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
exclude_columns:
- column1
- column2
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:
- usera@amce.org
- userb@amce.org
cache: true
exclude_patterns:
- .pdf
- .docx
text:
profile1:
text: "Hello World HHXXXXX"
slack:
slack_example:
channel_types: "public_channel,private_channel"
token: xoxp-XXXXXXXXXXXXXXXXXXXXXXXXX
channel_types: "public_channel,private_channel"
limit_mins: 15 ## By default 60 mins
channel_ids:
- XXXXXXXXYou 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.
HAWK Eye's extensibility empowers developers to contribute new security commands. Here's how:
- Fork the HAWK Eye repository to your GitHub account.
- Create a new Python file for your security command inside the commands directory, with a descriptive name.
- Define a function execute(args) within the new Python file, containing the logic for your command.
- Provide clear documentation and comments explaining the purpose and usage of the new command.
- Thoroughly test your command to ensure it works seamlessly and aligns with the existing features.
- Submit a pull request from your branch to the main HAWK Eye repository.
- The maintainers will review your contribution, provide feedback if needed, and merge your changes.
We welcome contributions from the open-source community to enhance HAWK Eye's capabilities in securing data sources. To contribute:
- Fork the HAWK Eye repository to your GitHub account.
- Create a new branch from the main branch for your changes.
- Adhere to the project's coding standards and style guidelines.
- Write clear and concise commit messages for your changes.
- Include appropriate test cases for new features or modifications.
- Update the "README.md" file to reflect any changes or new features.
- Submit a pull request from your branch to the main branch of the HAWK Eye repository.
- The maintainers will review your pull request and work with you to address any concerns.
- 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.
- Black Hat SecTor 2023 [Arsenal]
- Black Hat Middle East and Africa 2023 [Arsenal]
- Black Hat Europe 2023 [Arsenal]
We extend our heartfelt appreciation to all contributors who continuously improve this tool! Your efforts are essential in strengthening the security landscape. 🙏
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!
![@dependabot[bot]](https://avatars.githubusercontent.com/in/29110?s=64&v=4){kind=small}