Deployment Models

Strike48 components run in three deployment models. Same connectors, same tools — what changes is where they run and how they talk to each other. The diagrams below are interactive: drag to pan, use the toolbar to zoom, click any node to open its docs, or go fullscreen for a closer look.

At a Glance

Model Who it's for Transport Topology
Desktop Individuals, local work Unix domain socket (IPC) One workstation
Platform Teams, remote execution gRPC + mTLS Hub + hosted connectors
Distributed Campaigns across networks gRPC + mTLS Many agents, central control

Desktop Model

You run StrikeHub on your machine; it launches and supervises connectors locally. Everything happens on one host, and connectors talk to the shell over Unix domain sockets — nothing is exposed to the network.

UI interaction Unix socket / IPC Unix socket / IPC Unix socket / IPC kubeconfig direct execution You StrikeHubdesktop shell KubeStudioKubernetes Pickpen testing StrikeKitred team Kubernetesclusters Local network
UI interaction Unix socket / IPC Unix socket / IPC Unix socket / IPC kubeconfig direct execution You StrikeHubdesktop shell KubeStudioKubernetes Pickpen testing StrikeKitred team Kubernetesclusters Local network
  • Single window — every connector gets a panel, all sharing one app and one OIDC login.
  • No network exposure — IPC over Unix domain sockets means connectors aren't reachable off-host.
  • Local credentials — KubeStudio uses your local kubeconfig; results stay on your machine.

Get started with StrikeHub →

Platform Model

Connect StrikeHub — or your connectors directly — to Prospector Studio, the hosted backend. Now AI agents and workflows can route jobs to your connectors over gRPC, with mutual TLS and centralized audit logging.

API / UI desktop WebSocket gRPC job routing gRPC job routing gRPC job routing You Prospector Studioagents · workflows · KBs StrikeHubdesktop shell KubeStudioKubernetes Pickpen testing StrikeKitred team Kubernetesclusters Target network
API / UI desktop WebSocket gRPC job routing gRPC job routing gRPC job routing You Prospector Studioagents · workflows · KBs StrikeHubdesktop shell KubeStudioKubernetes Pickpen testing StrikeKitred team Kubernetesclusters Target network
  • Remote execution — trigger tools via the GraphQL API or workflows.
  • Team collaboration — shared engagements, knowledge bases, and a centralized audit trail.
  • mTLS everywhere — connector-to-platform traffic is mutually authenticated; users authenticate via OIDC/OAuth2 with RBAC on every job.

Explore Prospector Studio →

Distributed Model

The platform model, scaled out: many connector agents deployed across different networks, all registered with one Prospector Studio. An agent on each target network executes locally; results aggregate centrally. This is how distributed scanning and multi-network campaigns run.

API / Workflow gRPC gRPC gRPC You Prospector Studioorchestration Pick agent 1network A Pick agent 2network B KubeStudio agentcluster fleet Targets A Targets B K8s clusters
API / Workflow gRPC gRPC gRPC You Prospector Studioorchestration Pick agent 1network A Pick agent 2network B KubeStudio agentcluster fleet Targets A Targets B K8s clusters
  • Deploy agents anywhere — each connector registers with the platform and receives jobs over gRPC.
  • Aggregate results — findings from every agent roll up into one shared intelligence database.
  • Orchestrate campaigns — drive distributed scanning from a single workflow.

Pick remote execution → · Deploying connectors →

Mixing Models

Connectors are independent processes, so you don't have to pick one model for everything. Run KubeStudio locally through StrikeHub while a fleet of Pick agents runs in the platform — they don't need to know about each other. See the Hub & Connector Model for the full picture of communication patterns and security boundaries.

Choosing a Model

Yes No Yes No No Yes Working solo onone machine? Desktop modelStrikeHub + local connectors Need remote executionor team sharing? Across multiplenetworks? Platform modelProspector Studio-hosted Distributed modelagents per network
Yes No Yes No No Yes Working solo onone machine? Desktop modelStrikeHub + local connectors Need remote executionor team sharing? Across multiplenetworks? Platform modelProspector Studio-hosted Distributed modelagents per network

Next Steps