ShinMegamiBoson/OpenPlanterPublic

AI summary: An open-source OSINT framework focused on analyzing and mapping complex threat actor infrastructure.

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PythonMITCreated Feb 20, 2026Last push 7mo agoLatest release v0.1.1+20 stars this week+254 this month

Quick answers

What is OpenPlanter?
An open-source OSINT framework focused on analyzing and mapping complex threat actor infrastructure.
What does OpenPlanter do?
OpenPlanter is a specialized Open Source Intelligence (OSINT) tool designed to help security researchers map out and analyze adversary infrastructure. It automates the collection and correlation of data from various sources, such as DNS records, WHOIS information, and SSL certificates, to build comprehensive profiles of potential threat actors. The framework provides a structured methodology for tracking malicious campaigns across different domains and hosting providers. By aggregating fragmented data points into clear visual representations, it enables security teams to proactively identify and block emerging threats.
Who is OpenPlanter for?
Security researchers, threat intelligence analysts, and incident responders looking for an automated way to map adversary infrastructure.
How do I get started with OpenPlanter?
Review the documentation for setup and usage instructions.
How popular is OpenPlanter on GitHub?
ShinMegamiBoson/OpenPlanter has 2,696 stars and 391 forks on GitHub, and gained 20 stars in the last 7 days.
What license does OpenPlanter use?
ShinMegamiBoson/OpenPlanter is released under the MIT license.

Star history

since Jul 28, 2026
01K2KJul 2026Aug 2026Sep 2026Oct 2026
2.7K stars as of Oct 4, 2026. Measured daily since Jul 28, 2026; GitHub no longer exposes earlier star timestamps.

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Signals and awards

derived from tracked data
  • Permissive license

    MIT

  • Continuous integration

    Automated checks passing

What OpenPlanter does

OpenPlanter is a specialized Open Source Intelligence (OSINT) tool designed to help security researchers map out and analyze adversary infrastructure. It automates the collection and correlation of data from various sources, such as DNS records, WHOIS information, and SSL certificates, to build comprehensive profiles of potential threat actors. The framework provides a structured methodology for tracking malicious campaigns across different domains and hosting providers. By aggregating fragmented data points into clear visual representations, it enables security teams to proactively identify and block emerging threats.

Security researchers, threat intelligence analysts, and incident responders looking for an automated way to map adversary infrastructure.

  • Infrastructure mapping: Automates the discovery and correlation of domains, IP addresses, and hosting providers used by adversaries.
  • Data aggregation: Integrates multiple OSINT sources into a single, unified analysis platform.
  • Campaign tracking: Provides tools to monitor changes in threat actor infrastructure over time.
  • Visual analysis: Generates clear relationship graphs to help analysts understand complex adversary networks.
  • Automated reporting: Produces structured threat intelligence reports based on the collected infrastructure data.

Where teams use it

Threat intelligence research

Security analysts use the framework to map the infrastructure of newly identified threat groups to anticipate future attacks.

Proactive defense

Security operations teams leverage the correlated data to proactively block IP ranges and domains associated with known malicious campaigns.

Incident response

Incident responders trace the origins of an attack by analyzing the historical infrastructure patterns connected to a malicious IP.

Vulnerability discovery

Researchers identify misconfigured or exposed infrastructure belonging to threat actors by analyzing comprehensive domain profiles.

Getting started: Review the documentation for setup and usage instructions.

README

main branch

OpenPlanter

A recursive-language-model investigation agent with a desktop GUI and terminal interface. OpenPlanter ingests heterogeneous datasets — corporate registries, campaign finance records, lobbying disclosures, government contracts, and more — resolves entities across them, and surfaces non-obvious connections through evidence-backed analysis. It operates autonomously with file I/O, shell execution, web search, and recursive sub-agent delegation.

OpenPlanter Desktop

Download

Pre-built binaries are available on the Releases page:

  • macOS — .dmg
  • Windows — .msi
  • Linux — .AppImage

Desktop App

The desktop app (openplanter-desktop/) is a Tauri 2 application with a three-pane layout:

  • Sidebar — Session management, provider/model settings, and API credential status
  • Chat pane — Conversational interface showing the agent's objectives, reasoning steps, tool calls, and findings with syntax-highlighted code blocks
  • Knowledge graph — Interactive Cytoscape.js visualization of entities and relationships discovered during investigation. Nodes are color-coded by category (corporate, campaign-finance, lobbying, contracts, sanctions, etc.). Click a source node to open a slide-out drawer with the full rendered wiki document.

Features

  • Live knowledge graph — Entities and connections render in real time as the agent works. Switch between force-directed, hierarchical, and circular layouts. Search and filter by category.
  • Wiki source drawer — Click any source node to read the full markdown document in a slide-out panel. Internal wiki links navigate between documents and focus the corresponding graph node.
  • Session persistence — Investigations are saved automatically. Resume previous sessions or start new ones from the sidebar.
  • Background wiki curator — A lightweight agent runs in the background to keep wiki documents consistent and cross-linked.
  • Multi-provider support — Switch between OpenAI, Anthropic, OpenRouter, Cerebras, and Ollama (local) from the sidebar.

Building from Source

cd openplanter-desktop

# Install frontend dependencies
cd frontend && npm install && cd ..

# Run in development mode
cargo tauri dev

# Build distributable binary
cargo tauri build

Requires: Rust stable, Node.js 20+, and platform-specific Tauri dependencies (see Tauri prerequisites).

CLI Agent

The Python CLI agent can be used independently of the desktop app.

Quickstart

# Install
pip install -e .

# Configure API keys (interactive prompt)
openplanter-agent --configure-keys

# Launch the TUI
openplanter-agent --workspace /path/to/your/project

Or run a single task headlessly:

openplanter-agent --task "Cross-reference vendor payments against lobbying disclosures and flag overlaps" --workspace ./data

Docker

# Add your API keys to .env, then:
docker compose up

The container mounts ./workspace as the agent's working directory.

Supported Providers

Provider Default Model Env Var
OpenAI gpt-5.2 OPENAI_API_KEY
Anthropic claude-opus-4-6 ANTHROPIC_API_KEY
OpenRouter anthropic/claude-sonnet-4-5 OPENROUTER_API_KEY
Cerebras qwen-3-235b-a22b-instruct-2507 CEREBRAS_API_KEY
Ollama llama3.2 (none — local)

Local Models (Ollama)

Ollama runs models locally with no API key. Install Ollama, pull a model (ollama pull llama3.2), then:

openplanter-agent --provider ollama
openplanter-agent --provider ollama --model mistral
openplanter-agent --provider ollama --list-models

The base URL defaults to http://localhost:11434/v1 and can be overridden with OPENPLANTER_OLLAMA_BASE_URL or --base-url. The first request may be slow while Ollama loads the model into memory; a 120-second first-byte timeout is used automatically.

Additional service keys: EXA_API_KEY (web search), VOYAGE_API_KEY (embeddings).

All keys can also be set with an OPENPLANTER_ prefix (e.g. OPENPLANTER_OPENAI_API_KEY), via .env files in the workspace, or via CLI flags.

Agent Tools

The agent has access to 19 tools, organized around its investigation workflow:

Dataset ingestion & workspace — list_files, search_files, repo_map, read_file, write_file, edit_file, hashline_edit, apply_patch — load, inspect, and transform source datasets; write structured findings.

Shell execution — run_shell, run_shell_bg, check_shell_bg, kill_shell_bg — run analysis scripts, data pipelines, and validation checks.

Web — web_search (Exa), fetch_url — pull public records, verify entities, and retrieve supplementary data.

Planning & delegation — think, subtask, execute, list_artifacts, read_artifact — decompose investigations into focused sub-tasks, each with acceptance criteria and independent verification.

In recursive mode (the default), the agent spawns sub-agents via subtask and execute to parallelize entity resolution, cross-dataset linking, and evidence-chain construction across large investigations.

CLI Reference

openplanter-agent [options]

Workspace & Session

Flag Description
--workspace DIR Workspace root (default: .)
--session-id ID Use a specific session ID
--resume Resume the latest (or specified) session
--list-sessions List saved sessions and exit

Model Selection

Flag Description
--provider NAME auto, openai, anthropic, openrouter, cerebras, ollama
--model NAME Model name or newest to auto-select
--reasoning-effort LEVEL low, medium, high, or none
--list-models Fetch available models from the provider API

Execution

Flag Description
--task OBJECTIVE Run a single task and exit (headless)
--recursive Enable recursive sub-agent delegation
--acceptance-criteria Judge subtask results with a lightweight model
--max-depth N Maximum recursion depth (default: 4)
--max-steps N Maximum steps per call (default: 100)
--timeout N Shell command timeout in seconds (default: 45)

UI

Flag Description
--no-tui Plain REPL (no colors or spinner)
--headless Non-interactive mode (for CI)
--demo Censor entity names and workspace paths in output

Persistent Defaults

Use --default-model, --default-reasoning-effort, or per-provider variants like --default-model-openai to save workspace defaults to .openplanter/settings.json. View them with --show-settings.

Configuration

Keys are resolved in this priority order (highest wins):

  1. CLI flags (--openai-api-key, etc.)
  2. Environment variables (OPENAI_API_KEY or OPENPLANTER_OPENAI_API_KEY)
  3. .env file in the workspace
  4. Workspace credential store (.openplanter/credentials.json)
  5. User credential store (~/.openplanter/credentials.json)

All runtime settings can also be set via OPENPLANTER_* environment variables (e.g. OPENPLANTER_MAX_DEPTH=8).

Project Structure

openplanter-desktop/         Tauri 2 desktop application
  crates/
    op-tauri/                 Tauri backend (Rust)
      src/commands/           IPC command handlers (agent, wiki, config)
    op-core/                  Shared core library
  frontend/                   TypeScript/Vite frontend
    src/components/           UI components (ChatPane, GraphPane, InputBar, Sidebar)
    src/graph/                Cytoscape.js graph rendering
    src/api/                  Tauri IPC wrappers
    e2e/                      Playwright E2E tests

agent/                        Python CLI agent
  __main__.py                 CLI entry point and REPL
  engine.py                   Recursive language model engine
  runtime.py                  Session persistence and lifecycle
  model.py                    Provider-agnostic LLM abstraction
  builder.py                  Engine/model factory
  tools.py                    Workspace tool implementations
  tool_defs.py                Tool JSON schemas
  prompts.py                  System prompt construction
  config.py                   Configuration dataclass
  credentials.py              Credential management
  tui.py                      Rich terminal UI
  demo.py                     Demo mode (output censoring)
  patching.py                 File patching utilities
  settings.py                 Persistent settings

tests/                        Unit and integration tests

Development

Desktop App

cd openplanter-desktop

# Development mode (hot-reload)
cargo tauri dev

# Frontend tests
cd frontend && npm test

# E2E tests (Playwright)
cd frontend && npm run test:e2e

# Backend tests
cargo test

CLI Agent

# Install in editable mode
pip install -e .

# Run tests
python -m pytest tests/

# Skip live API tests
python -m pytest tests/ --ignore=tests/test_live_models.py --ignore=tests/test_integration_live.py

Requires Python 3.10+. Dependencies: rich, prompt_toolkit, pyfiglet.

License

MIT — see LICENSE for details.

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Releases and announcements

1 total
  1. v0.1.1v0.1.1Mar 6, 20261.2K downloads

    **Full Changelog**: https://github.com/ShinMegamiBoson/OpenPlanter/commits/v0.1.1 **Full Changelog**: https://github.com/ShinMegamiBoson/OpenPlanter/commits/v0.1.1 **Full Changelog**: https://github.com/ShinMegamiBoson/OpenPlanter/commits/v0.1.1 **Full Changelog**: https://github.com/ShinMegamiBoson/OpenPlanter/commits/v0.1.1 **Full Changelog**: https://github.com/ShinMegamiBoson/OpenPlanter/commits/v0.1.1

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115 commits in the last 52 weeks.

When work happens

weekday and hour
SunMonTueWedThuFriSat036912151821Sun 0:00 — 1 commitsSun 1:00 — 0 commitsSun 2:00 — 0 commitsSun 3:00 — 0 commitsSun 4:00 — 0 commitsSun 5:00 — 0 commitsSun 6:00 — 0 commitsSun 7:00 — 0 commitsSun 8:00 — 2 commitsSun 9:00 — 0 commitsSun 10:00 — 0 commitsSun 11:00 — 0 commitsSun 12:00 — 0 commitsSun 13:00 — 0 commitsSun 14:00 — 2 commitsSun 15:00 — 0 commitsSun 16:00 — 1 commitsSun 17:00 — 0 commitsSun 18:00 — 0 commitsSun 19:00 — 0 commitsSun 20:00 — 1 commitsSun 21:00 — 3 commitsSun 22:00 — 2 commitsSun 23:00 — 0 commitsMon 0:00 — 0 commitsMon 1:00 — 0 commitsMon 2:00 — 0 commitsMon 3:00 — 0 commitsMon 4:00 — 0 commitsMon 5:00 — 0 commitsMon 6:00 — 0 commitsMon 7:00 — 0 commitsMon 8:00 — 0 commitsMon 9:00 — 0 commitsMon 10:00 — 0 commitsMon 11:00 — 3 commitsMon 12:00 — 1 commitsMon 13:00 — 0 commitsMon 14:00 — 0 commitsMon 15:00 — 0 commitsMon 16:00 — 0 commitsMon 17:00 — 0 commitsMon 18:00 — 0 commitsMon 19:00 — 0 commitsMon 20:00 — 0 commitsMon 21:00 — 0 commitsMon 22:00 — 0 commitsMon 23:00 — 0 commitsTue 0:00 — 0 commitsTue 1:00 — 0 commitsTue 2:00 — 0 commitsTue 3:00 — 0 commitsTue 4:00 — 0 commitsTue 5:00 — 0 commitsTue 6:00 — 0 commitsTue 7:00 — 0 commitsTue 8:00 — 0 commitsTue 9:00 — 0 commitsTue 10:00 — 0 commitsTue 11:00 — 0 commitsTue 12:00 — 1 commitsTue 13:00 — 0 commitsTue 14:00 — 0 commitsTue 15:00 — 0 commitsTue 16:00 — 2 commitsTue 17:00 — 3 commitsTue 18:00 — 0 commitsTue 19:00 — 2 commitsTue 20:00 — 2 commitsTue 21:00 — 2 commitsTue 22:00 — 3 commitsTue 23:00 — 1 commitsWed 0:00 — 2 commitsWed 1:00 — 1 commitsWed 2:00 — 0 commitsWed 3:00 — 0 commitsWed 4:00 — 0 commitsWed 5:00 — 0 commitsWed 6:00 — 0 commitsWed 7:00 — 0 commitsWed 8:00 — 0 commitsWed 9:00 — 0 commitsWed 10:00 — 0 commitsWed 11:00 — 2 commitsWed 12:00 — 0 commitsWed 13:00 — 0 commitsWed 14:00 — 0 commitsWed 15:00 — 0 commitsWed 16:00 — 0 commitsWed 17:00 — 0 commitsWed 18:00 — 1 commitsWed 19:00 — 0 commitsWed 20:00 — 2 commitsWed 21:00 — 1 commitsWed 22:00 — 2 commitsWed 23:00 — 3 commitsThu 0:00 — 0 commitsThu 1:00 — 1 commitsThu 2:00 — 0 commitsThu 3:00 — 0 commitsThu 4:00 — 0 commitsThu 5:00 — 0 commitsThu 6:00 — 0 commitsThu 7:00 — 0 commitsThu 8:00 — 0 commitsThu 9:00 — 0 commitsThu 10:00 — 2 commitsThu 11:00 — 1 commitsThu 12:00 — 2 commitsThu 13:00 — 7 commitsThu 14:00 — 0 commitsThu 15:00 — 3 commitsThu 16:00 — 1 commitsThu 17:00 — 1 commitsThu 18:00 — 5 commitsThu 19:00 — 4 commitsThu 20:00 — 6 commitsThu 21:00 — 3 commitsThu 22:00 — 1 commitsThu 23:00 — 0 commitsFri 0:00 — 0 commitsFri 1:00 — 0 commitsFri 2:00 — 0 commitsFri 3:00 — 0 commitsFri 4:00 — 0 commitsFri 5:00 — 0 commitsFri 6:00 — 0 commitsFri 7:00 — 0 commitsFri 8:00 — 0 commitsFri 9:00 — 0 commitsFri 10:00 — 0 commitsFri 11:00 — 0 commitsFri 12:00 — 0 commitsFri 13:00 — 0 commitsFri 14:00 — 0 commitsFri 15:00 — 0 commitsFri 16:00 — 2 commitsFri 17:00 — 0 commitsFri 18:00 — 0 commitsFri 19:00 — 0 commitsFri 20:00 — 0 commitsFri 21:00 — 0 commitsFri 22:00 — 1 commitsFri 23:00 — 0 commitsSat 0:00 — 5 commitsSat 1:00 — 1 commitsSat 2:00 — 0 commitsSat 3:00 — 0 commitsSat 4:00 — 0 commitsSat 5:00 — 0 commitsSat 6:00 — 0 commitsSat 7:00 — 0 commitsSat 8:00 — 0 commitsSat 9:00 — 0 commitsSat 10:00 — 2 commitsSat 11:00 — 3 commitsSat 12:00 — 1 commitsSat 13:00 — 1 commitsSat 14:00 — 3 commitsSat 15:00 — 0 commitsSat 16:00 — 0 commitsSat 17:00 — 0 commitsSat 18:00 — 0 commitsSat 19:00 — 1 commitsSat 20:00 — 2 commitsSat 21:00 — 8 commitsSat 22:00 — 1 commitsSat 23:00 — 1 commits
Commit volume by weekday and hour (UTC). Larger dots mean more commits.
DateListRankStars gained
Feb 20, 2026daily#12+146