Skip to main content

Python implementation of the FortiSOAR REST API

Reason this release was yanked:

leaked internal ip

Project description

pyfsr

PyPI version Tests Documentation Status codecov

Documentation · Installation · Quick start · AI / agents

pyfsr is a batteries-included Python client for the FortiSOAR REST API. It gives you a typed query/CRUD layer over any module, picklist resolution, connector execution, playbook-run history, safe deletes — and a ready-made AI/agent surface (tool-schema registry + an optional MCP server) so an agent can drive FortiSOAR with no glue code.

Python 3.10+ · Pydantic v2 · MIT.

Installation

pip install pyfsr
# with the optional generic MCP server:
pip install 'pyfsr[mcp]'

Quick start

from pyfsr import FortiSOAR, Query

# API-key auth, or ("username", "password")
client = FortiSOAR("soar.example.com", "your-api-key")

# Generic, typed CRUD for ANY module via client.records(module)
incidents = client.records("incidents")

inc = incidents.get("0d2c...")          # by uuid, "module:uuid", or full IRI
inc["name"], inc.uuid                    # records are dict- AND attribute-accessible

# Structured queries with a fluent builder -> a HydraPage you can iterate
page = incidents.query(
    Query().eq("status.itemValue", "Open").like("name", "phish").limit(50)
)
for inc in incidents.iterate(Query().eq("status.itemValue", "Open")):
    ...                                  # lazily walks every page

# Create / update / delete (soft by default; hard= for permanent)
new = incidents.create({"name": "Suspicious login", "severity": "High"},
                       resolve_picklists=True)   # friendly values -> IRIs
incidents.update(new.uuid, {"status": "Closed"}, resolve_picklists=True)
incidents.delete(new.uuid)               # delete(..., hard=True) to purge

Configure from the environment

from pyfsr import EnvConfig

# reads FSR_BASE_URL (+ FSR_API_KEY or FSR_USERNAME/FSR_PASSWORD),
# FSR_PORT, FSR_VERIFY_SSL, FSR_TIMEOUT
client = EnvConfig.from_env().client()

Features

  • Generic record accessclient.records(module) for CRUD on any module; no hand-built /api/3/... URLs or Hydra unwrapping.
  • Query DSLQuery().eq(...).in_(...).group(...).sort(...).limit(...), compiled to the FortiSOAR query-body shape (pagination handled for you).
  • Typed models — Alert/Incident/Task/Comment come back as Pydantic v2 models that are also dict-compatible; unknown modules fall back to a lenient BaseRecord, so custom fields/modules never break.
  • Picklistsclient.picklists resolves friendly values ("High") to IRIs and discovers which picklist a (module, field) binds to.
  • Connectorsclient.connectors lists configured connectors, runs healthchecks, and executes operations.
  • Playbooksclient.playbooks merges live + historical run history and resumes manual-input steps.
  • Safe deletes — soft-delete/restore + guarded single-row hard delete.
  • Schema discoveryclient.list_modules() / client.describe_module().
  • Resilient transport — configurable timeout=, automatic retry with backoff on idempotent requests (429/5xx), and secrets masked in verbose logs.
  • Bundled OpenAPI specpyfsr.spec.load_spec() for offline reference and drift(client) to compare the spec against a live appliance.

AI / agent-friendly

pyfsr ships a transport-neutral tool registry for the core operations, with token-efficient results and structured (never-raised) errors — feed it to Anthropic tool-use, OpenAI function calling, your own agent loop, or the bundled MCP server.

from pyfsr.tools import to_anthropic_tools, to_openai_tools, dispatch

tools = to_anthropic_tools()             # or to_openai_tools(), or tool_schemas()

# ... your model picks a tool ...
result = dispatch(client, "search_records",
                  {"module": "alerts", "summary": True, "limit": 10})
# result is JSON-safe and trimmed; failures come back as {"error": {...}}

Reads accept summary=True or fields=[...] to keep payloads small:

client.records("alerts").query(Query().limit(20), summary=True)

Generic MCP server

Point any MCP-capable agent at any FortiSOAR with one command:

pip install 'pyfsr[mcp]'
FSR_BASE_URL=soar.example.com FSR_API_KEY=... python -m pyfsr.mcp

It exposes the same registry (record CRUD, schema discovery, picklists, connectors, playbook runs) as MCP tools — generic and dependency-light, distinct from any domain-specific FortiSOAR MCP.

Development

uv sync --extra dev
uv run pytest -q                 # unit tests (live tests deselected by default)
uvx ruff check src tests

Live integration tests run with pytest -m integration and need an examples/config.toml pointing at a FortiSOAR instance.

License

MIT — see LICENSE.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pyfsr-0.6.4.tar.gz (175.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

pyfsr-0.6.4-py3-none-any.whl (204.8 kB view details)

Uploaded Python 3

File details

Details for the file pyfsr-0.6.4.tar.gz.

File metadata

  • Download URL: pyfsr-0.6.4.tar.gz
  • Upload date:
  • Size: 175.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for pyfsr-0.6.4.tar.gz
Algorithm Hash digest
SHA256 b7467479c20c27704537fa02c1294b1244aae1c030db646b765e30153486e65f
MD5 bad9c3ed87c9364b03c081531c8a05a6
BLAKE2b-256 2ecff4cf44c75e4bdc55e6cd387db80de846c801c92e737c047a8b8e86f83919

See more details on using hashes here.

Provenance

The following attestation bundles were made for pyfsr-0.6.4.tar.gz:

Publisher: publish.yml on ftnt-dspille/pyfsr

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file pyfsr-0.6.4-py3-none-any.whl.

File metadata

  • Download URL: pyfsr-0.6.4-py3-none-any.whl
  • Upload date:
  • Size: 204.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for pyfsr-0.6.4-py3-none-any.whl
Algorithm Hash digest
SHA256 cafce8881c24934071bdbf78b056adf260cd79ef63b27c94c8ce20ad505ba120
MD5 c5b934c37ed63ad9c3c46d083470260f
BLAKE2b-256 ae8c949366b73449da3c40f54c31b0d7c7dab2ee438b54e4594f364e78fbd39a

See more details on using hashes here.

Provenance

The following attestation bundles were made for pyfsr-0.6.4-py3-none-any.whl:

Publisher: publish.yml on ftnt-dspille/pyfsr

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page