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Getting StartedTalon Studio v1.0.2-beta

Core Concepts

Workspaces, detection-as-code, evidence, change requests and the release pipeline — the ideas Talon is built on.

What it is

Talon Studio rests on a small set of concepts that show up in every product. Learn these five and the rest of the platform reads naturally: workspaces, detection-as-code, evidence, change requests, and the release pipeline.

Workspace — the Git-backed unit of detection engineering. Each workspace is its own repository.
Detection-as-code — every detection is Sigma or a native SIEM query stored as YAML in Git.
Evidence — what Connect learns from your SIEM about what you can actually detect.
Change request — edits land on a branch and open a CR, reviewed like a pull request.
Release pipeline — converts a detection to each SIEM on deploy, with main as production truth.

How it works

A workspace is a self-contained project: members, SIEM and translation config, sourcetypes, and detections all belong to it, like a GitHub repo with branch protection. Each workspace maps to one Git repo under /data/repos with a predictable layout.

workspace repository layout
# one Git repo per workspace, under /data/repos
Talon/detections/ # detection YAML, one file per detection
Talon/streams/ # sourcetype definitions (from your SIEM)
Talon/targets/ # deployment targets
Talon/blueprints/ # saved Forge blueprints
Talon/standards/ # detection standards
Talon/integrations/siem/ # connected SIEM backends
Talon/threat-scenarios/ # Replay scenarios
Talon/deployments/ # generated SIEM artifacts, per target
Talon/workspace.yaml # workspace manifest: SIEM targets, CR protection
README.md

Workspaces created before this layout keep their detections in detections/ at the repository root; everything else is the same.

Detection-as-code means the YAML file is the contract. It carries the rule — Sigma logic or a native query, plus severity, MITRE mapping, and a per-SIEM queries block — and Postgres only caches it for fast UI reads. Evidence is the other half of the equation: Connect introspects the SIEM's indexes, sourcetypes, and fields so coverage is measured against telemetry you genuinely have, not a theoretical catalogue.

When you edit a detection, the change lands on a branch and opens a change request. RBAC is enforced two ways: per-workspace roles — viewer, engineer, owner — gate who can edit and merge, and org roles — admin, engineer, analyst, readonly — govern the appliance itself.

Setup

There's nothing to install for these concepts — they come with the appliance. To put them to work:

1
Create or open a workspace; it initialises a Git repo with the layout above. The Community Edition allows one workspace.
2
Add members and assign a workspace role: viewer reads, engineer edits and opens change requests, owner approves, merges, and manages settings. The Community Edition allows two users.
3
Connect a SIEM so Evidence is populated and coverage becomes real rather than aspirational.
4
Set the workspace's SIEM target(s) in its settings — Talon serialises them to Talon/workspace.yaml so the pipeline knows which query languages to render.

Usage

In day-to-day use the concepts chain together. An engineer edits a detection in Forge; the save opens a change request on a branch instead of writing straight to main. The CR shows a diff, runs a validation check as a status gate, and waits for an owner. On approval it merges to main, which is the production truth for that workspace.

The release pipeline then deploys from main: it converts the neutral rule to each configured SIEM on the way out (convert-on-deploy), so a detection written once ships to every platform you run. On the Community Edition deploys come from main only; deploying another branch to its own SIEM is an Enterprise feature. If a deploy misbehaves, one-click rollback returns the SIEM to the previous known-good state — on Splunk, Sentinel, Elastic and Chronicle targets alike — while Git keeps the full audit trail.

screenshot
The Workspace → Change Requests screen. Open a change request to review the diff and its auto-run validation status check, then approve and click Merge to land it on main.
Git is the source of truth
Content lives in Git; Postgres caches operational state for speed. That split is why detections stay portable and every change is auditable — you can clone a workspace repo and read the exact YAML that ships to your SIEM.