About Hostile‑Command‑Suite
Hostile‑Command‑Suite is a terminal-based OSINT investigation framework. Its AI agent selects tools for names, usernames, emails, and URLs, then analyzes findings using local ollama and can chain investigations based on discovered leads.
Key features
- 01Investigate usernames across 400+ platforms
- 02Analyze email with Mosint
- 03Scrape discovered profiles
- 04Search the web with DuckDuckGo
- 05Use local AI for analysis and decisions
- 06Chain tools based on investigation leads
Use cases
- 01Investigate social accounts linked to a username
- 02Check email breach and domain intelligence
- 03Find public information about names or organizations
- 04Analyze URLs and follow investigation leads
MCP support
The system uses MCP tool servers to provide Sherlock, Mosint, profile scraping, DuckDuckGo search, and link analysis capabilities for its AI agent.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEHostile Command Suite - OSINT Package
Author: cycloarcane
Contact: [email protected]
License: PolyForm Noncommercial License 1.0.0
Intelligent Open Source Intelligence Investigation System
A terminal-based OSINT investigation framework with AI-powered analysis and intelligent agent decision-making. Features automated profile scraping, multi-platform username investigation, and local LLM integration for enhanced intelligence gathering.
🚀 Quick Start
Prerequisites
- Install ollama (for AI analysis):
curl -fsSL https://ollama.ai/install.sh | sh
ollama pull qwen3:8b # recommended model
- Install OSINT tools:
# Arch Linux
yay -S sherlock-git mosint
# Ubuntu/Debian
pip install sherlock-project
# For mosint, download from: https://github.com/alpkeskin/mosint
Installation
git clone https://github.com/cycloarcane/Hostile-Command-Suite.git
cd Hostile-Command-Suite
python -m venv .venv
source .venv/bin/activate # Linux/Mac
pip install -r requirements.txt
Usage
Interactive comprehensive investigation:
python3 HCSO.py --interactive
# Then provide ALL target information: names, usernames, emails, addresses, etc.
Command line investigation:
# Single targets (backward compatibility)
python3 HCSO.py cycloarcane
python3 HCSO.py [email protected]
# Comprehensive targets (multiple data points)
python3 HCSO.py "John Smith, @johnsmith123, [email protected], works at Acme Corp"
python3 HCSO.py --model llama3.2 "Jane Doe [email protected] https://linkedin.com/in/janedoe"
🛠️ Features
Core Capabilities
- 🔍 Username Investigation: Sherlock integration across 400+ social media platforms
- 📧 Email Investigation: Mosint integration for email intelligence and breach analysis
- 🌐 Profile Scraping: Automated extraction of profile details from discovered accounts
- 🔍 Web Search Intelligence: DuckDuckGo search integration for comprehensive OSINT gathering
- 🤖 AI Agent: Local ollama integration for intelligent decision-making and analysis
- ⚡ Intelligent Workflow: Automatic tool chaining and investigation pivoting
- 🎨 Rich Terminal: Professional red/black themed interface with progress indicators
Supported Targets
| Target Type | Primary Tool | Secondary Tools | AI Analysis |
|---|---|---|---|
| Username | Sherlock → Profile Scraper | DuckDuckGo Search, Link Analyzer | ✅ Full Analysis |
| Mosint | DuckDuckGo Search | ✅ Full Analysis | |
| Any Target | DuckDuckGo Search | Context-dependent pivoting | ✅ Full Analysis |
MCP Tool Architecture
The system uses Model Context Protocol (MCP) based tool servers:
sherlock_server.py: Username investigation across platformsmosint_server.py: Email enumeration and breach investigationprofile_scraper_server.py: Intelligent profile content extractionduckduckgo_server.py: Web search for comprehensive intelligence gatheringlink_analyzer_server.py: Deep analysis of URLs and GitHub profiles
AI-Powered Intelligence
The AI agent provides:
- Comprehensive Data Extraction: Uses LLM to parse and categorize all provided target information
- Intelligent Tool Selection: Automatically chooses appropriate tools based on data types:
- Names → DuckDuckGo web search for public records and news
- Usernames → Sherlock for social media platform discovery
- Emails → Mosint for breach data and domain analysis
- Organizations → Web search for corporate intelligence
- URLs → Link analyzer for deep content analysis
- Investigation Pivoting: Discovers new leads and suggests follow-up actions
- Security Risk Assessment: Evaluates exposure levels and security implications
- Pattern Recognition: Identifies connections across platforms and data sources
- Decision Making: Determines when investigations are complete vs need continuation
🏗️ Architecture
Intelligent Agent Design
┌─────────────────┐ ┌──────────────────┐ ┌─────────────────┐
│ HCSO Agent │──▶│ Ollama AI │───▶│ Investigation │
│ │ │ Decision Engine │ │ Recommendations │
└─────────────────┘ └──────────────────┘ └─────────────────┘
│
▼
┌─────────────────┐ ┌──────────────────┐ ┌─────────────────┐
│ MCP Tool │──▶│ Tool Results │───▶│ Profile Scraper │
│ Manager │ │ Analysis │ │ Auto-Trigger │
└─────────────────┘ └──────────────────┘ └─────────────────┘
│
▼
┌─────────────────┐ ┌──────────────────┐ ┌─────────────────┐
│ Sherlock │ │ Mosint │ │ Profile │
│ Username Search │ │ Email Intel │ │ Scraper │
└─────────────────┘ └──────────────────┘ └─────────────────┘
Investigation Workflow
- Comprehensive Input: User provides ALL available target information (names, usernames, emails, addresses, organizations, URLs, etc.)
- AI Data Extraction: LLM parses and categorizes information into structured data types
- Intelligent Tool Selection: System automatically selects appropriate tools for each data type:
- Names → Web search for public intelligence
- Usernames → Social media platform discovery
- Emails → Breach analysis and domain intelligence
- Organizations → Corporate and public records search
- URLs → Deep content and profile analysis
- Parallel Investigation: Multiple tools execute simultaneously based on extracted data
- AI Analysis: Intelligent analysis of all findings and cross-reference discovery
- Decision Point: AI recommends additional investigations or marks complete
- Iterative Enhancement: Follow-up investigations based on discovered leads
📊 Example Output
╔═════════════════════════════════════════════════════════════════════════╗
║ ██ ██ ███████ ██████ ███████ ███████ ██ ███ ██ ████████ ║
║ ██ ██ ██ ██ ██ ██ ██ ██ ████ ██ ██ ║
║ ███████ ███████ ██ █████ ██ ██ ███████ ██ ██ ██ ██ ██ ║
║ ██ ██ ██ ██ ██ ██ ██ ██ ██ ██ ██ ██ ║
║ ██ ██ ███████ ██████ ███████ ███████ ██ ██ ████ ██ ║
╚═════════════════════════════════════════════════════════════════════════╝
Hostile Command Suite - OSINT Package
Intelligent Open Source Intelligence Investigation System
Using AI Model: qwen3:8b
Available Tools: sherlock, mosint, profile_scraper, duckduckgo_search, link_analyzer
──────────────────────────────────────────────────────────────────────────────
═══ COMPREHENSIVE TARGET INFORMATION ═══
Provide ALL available information about your target for intelligent analysis
Include: names, usernames, emails, addresses, organizations, social profiles, etc.
Enter ALL target information: John Smith, @johnsmith123, [email protected], works at TechCorp
Analyzing Provided Information
──────────────────────────────────────────────────────────────────────────────
Extracted Target Intelligence
┏━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ Data Type ┃ Extracted Values ┃
┡━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ Names │ John Smith │
│ Usernames │ johnsmith123 │
│ Emails │ [email protected] │
│ Organizations │ TechCorp │
└────────────────┴───────────────────────────────────────────────────────────────────┘
────────────────────────────────────────────────────────────────
Investigating Name: John Smith
SHERLOCK Investigation Results
┏━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━┓
┃ Metric ┃ Value ┃
┡━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━┩
│ Target │ cycloarcane │
│ Accounts Found │ 17 │
│ Status │ Success │
└────────────────┴─────────────┘
────────────────────────────────────────────────────────────
Found 17 profiles, scraping for additional intelligence...
PROFILE_SCRAPER Investigation Results
┏━━━━━━━━━━━━━━━━━━┳━━━━━━━━━┓
┃ Metric ┃ Value ┃
┡━━━━━━━━━━━━━━━━━━╇━━━━━━━━━┩
│ Total Scraped │ 5 │
│ Successful │ 4 │
│ With Useful Info │ 4 │
│ Status │ Success │
└──────────────────┴─────────┘
────────────────────────────────────────────────────────────
AI Agent Analyzing...
╭─ AI Investigation Analysis ──────────────────────────────────────────────╮
│ ANALYSIS: Investigation revealed GitHub profile with security research │
│ interests (LLMs + red team). High-value intelligence gathered from │
│ multiple platforms. Profile scraping provided sufficient context. │
│ │
│ RECOMMENDATION: Investigation complete - sufficient intelligence gathered │
│ TOOL: NONE │
│ TARGET: N/A │
│ REASONING: Profile analysis reveals technical expertise and security │
│ focus. No additional tools needed for current investigation scope. │
╰───────────────────────────────────────────────────────────────────────────╯
🛡️ Security & Ethics
Responsible Use
- Legal Compliance: All investigations must comply with applicable laws
- Authorization: Only investigate targets you have permission to research
- Rate Limiting: Respects platform rate limits and implements delays
- Local Processing: All AI analysis happens locally via ollama (no cloud)
Privacy & Security
- No Data Persistence: Investigation results are not stored long-term
- Local LLM: AI analysis never leaves your machine
- Tool Isolation: Each OSINT tool runs independently
- Professional Focus: Designed for defensive security and legitimate research
🔧 Configuration
AI Model Selection
# Use different ollama models
python3 HCSO.py --model llama3.2 target
python3 HCSO.py --model qwen3:8b target
python3 HCSO.py --model mixtral target
Configurable Prompts
Agent behavior is configurable via YAML files:
prompts/agent_system.yaml: Core agent instructions and tool selection logicprompts/tool_prompts.yaml: Tool-specific analysis templates
Tool Capabilities
| Tool | Input | Capabilities | Auto-Trigger |
|---|---|---|---|
| DuckDuckGo Search | Names, Organizations | Web intelligence, news, public records | Auto for names |
| Sherlock | Username | 400+ platform search | Auto for usernames |
| Mosint | Breach data, domain intel | Auto for emails | |
| Link Analyzer | URLs | GitHub profiles, web content analysis | Auto for URLs |
| Profile Scraper | URLs | Bio, followers, verification | After Sherlock |
🚧 Development
Adding New OSINT Tools
- Create MCP server in
mcp_tools/new_tool_server.py - Add tool detection in
MCPToolManager.check_available_tools() - Implement tool calling in
MCPToolManager.call_tool() - Add result display in
display_investigation_result() - Update agent prompts for tool selection logic
Architecture Benefits
Previous Complex Architecture:
- 15+ microservices with FastMCP
- PostgreSQL database requirement
- Web UI and API complexity
- Multiple authentication layers
Current Intelligent Agent Architecture:
- Single intelligent agent with MCP tools
- No database required
- Pure terminal interface with AI
- Local ollama for decision-making
- Automatic tool chaining and pivoting
📈 Roadmap
Phase 1: Core Intelligence ✅
- Sherlock username investigation with AI analysis
- Mosint email investigation with AI analysis
- Intelligent profile scraping from social media
- AI-powered investigation decision making
- MCP-based tool architecture
Phase 2: Enhanced Analysis 🚧
- Link analyzer for deep GitHub/social media analysis
- Domain investigation capabilities
- Phone number OSINT integration
- Correlation analysis across findings
Phase 3: Advanced Intelligence 📋
- Investigation session management
- Custom tool integration framework
- Automated investigation workflows
- Advanced AI reasoning and pivoting
🤝 Contributing
- Fork the repository
- Create a feature branch (
git checkout -b feature/new-tool) - Add your MCP tool server following existing patterns
- Update agent prompts for tool integration
- Test with various target types
- Submit a pull request
Development Setup
git clone https://github.com/cycloarcane/Hostile-Command-Suite.git
cd Hostile-Command-Suite
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
python3 HCSO.py --interactive
📄 License
This project is licensed under the PolyForm Noncommercial License 1.0.0 - see the LICENSE file for details.
Copyright © cycloarcane ([email protected])
Intelligent. Terminal. Effective.
Advanced OSINT investigation with AI-powered decision making
For questions or feature requests, contact [email protected]
Comments
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An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.