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pyhuntress - An API library for Huntress SIEM and Huntress Managed SAT, written in Python

pyHuntress is a full-featured, type annotated API client written in Python for the Huntress APIs.

This library has been developed with the intention of making the Huntress APIs simple and accessible to non-coders while allowing experienced coders to utilize all features the API has to offer without the boilerplate.

pyHuntress currently supports both Huntress SIEM and Huntress Managed SAT products.

Features:

  • 100% API Coverage. All endpoints and response models.
  • Non-coder friendly. 100% annotated for full IDE auto-completion. Clients handle requests and authentication - just plug the right details in and go!
  • Fully annotated. This library has a strong focus on type safety and type hinting. Models are declared and parsed using Pydantic

pyHuntress is currently in development.

Known Issues:

  • As this project is still a WIP, documentation or code commentary may not always align.
  • Huntress Managed SAT is not built

Road Map:

  • Add Huntress Managed SAT Report

How-to:

Install

Open a terminal and run pip install pyhuntress

Initializing the API Clients

Huntress Managed SAT

from pyhuntress import HuntressSATAPIClient

# init client
sat_api_client = HuntressSATAPIClient(
  mycurricula.com,
  # your api public key,
  # your api private key,
)

Huntress SIEM

from pyhuntress import HuntressSIEMAPIClient

# init client
siem_api_client = HuntressSIEMAPIClient(
  # huntress siem url
  # your api public key,
  # your api private key,
)

Working with Endpoints

Endpoints are 1:1 to what's available for both the Huntress Managed SAT and Huntress SIEM.

For more information, check out the following resources:

Get many

### Managed SAT ###

# sends GET request to /company/companies endpoint
companies = manage_api_client.company.companies.get()

### SIEM ###

# sends GET request to /agents endpoint
agents = siem_api_client.agents.get()

Get one

### Managed SAT ###

# sends GET request to /company/companies/{id} endpoint
accounts = sat_api_client.accounts.id("abc123").get()

### SIEM ###

# sends GET request to /agents/{id} endpoint
agent = siem_api_client.agents.id(250).get()

Get with params

### Managed SAT ###

# sends GET request to /company/companies with a conditions query string
conditional_company = sat_api_client.company.companies.get(params={
  'conditions': 'company/id=250'
})

### SIEM ###
# sends GET request to /agents endpoint with a condition query string
conditional_agent = siem_api_client.clients.get(params={
  'platform': 'windows'
})

Pagination

The Huntress SIEM API paginates data for performance reasons through the page and limit query parameters. limit is limited to a maximum of 500.

To make working with paginated data easy, Endpoints that implement a GET response with an array also supply a paginated() method. Under the hood this wraps a GET request, but does a lot of neat stuff to make working with pages easier.

Working with pagination

# initialize a PaginatedResponse instance for /agents, starting on page 1 with a pageSize of 100
paginated_agents = siem_api_client.agents.paginated(1,100)

# access the data from the current page using the .data field
page_one_data = paginated_agents.data

# if there's a next page, retrieve the next page worth of data
paginated_agents.get_next_page()

# if there's a previous page, retrieve the previous page worth of data
paginated_agents.get_previous_page()

# iterate over all companies on the current page
for agent in paginated_agents:
  # ... do things ...

# iterate over all companies in all pages
# this works by yielding every item on the page, then fetching the next page and continuing until there's no data left
for agent in paginated_agents.all():
  # ... do things ...

Contributing

Contributions to the project are welcome. If you find any issues or have suggestions for improvement, please feel free to open an issue or submit a pull request.

Supporting the project

❤️

Inspiration and Stolen Code

The premise behind this came from the pyConnectWise package and I stole most of the code and adapted it to the Huntress API endpoints.

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