crossbow-agent 1.0.0

AI-Powered Security Testing Platform with 18 Specialized Security Agents

🎯 CrossBow Security Agent

AI-Powered Security Testing Platform with 18 Specialized Security Agents

CrossBow is a comprehensive AI-powered security testing platform that orchestrates 18 specialized security agents to perform advanced security assessments, threat analysis, and vulnerability testing.

✨ Features

🤖 18 Specialized Security Agents

1. SOC Analyst - Log analysis & attack investigation
2. Threat Intelligence Analyst - IOC collection & threat profiling
3. Android SAST Specialist - Android security testing
4. Blue Team Defender - Defensive security measures
5. Bug Bounty Hunter - Vulnerability discovery
6. Security Developer - Security code development
7. DFIR Investigator - Digital forensics & incident response
8. Email Security Analyst - Email threat analysis
9. Memory Forensics Expert - Memory analysis
10. Network Security Analyst - Network monitoring & analysis
11. Red Team Operator - Offensive security testing
12. Replay Attack Specialist - Attack replay analysis
13. Security Reporter - Report generation
14. Vulnerability Validator - Exploit verification
15. Reverse Engineer - Binary analysis
16. RF Security Expert - Radio frequency security
17. WiFi Security Tester - Wireless security
18. Source Code Analyzer - Static code analysis

🎨 Two Interfaces

• CLI - Traditional command-line interface
• TUI - Modern terminal UI with rich formatting (Textual-based)

⚙️ Advanced Capabilities

• Multi-Model Support: GPT-4o, Claude, Gemini
• Conversation Memory: Persistent context across sessions
• Agent Storage: State persistence for complex tasks
• MCP Support: Model Context Protocol integration
• Auto-Configuration: Settings automatically saved
• 40+ Security Tools: Integrated security testing toolkit

🚀 Quick Start

Installation

pip install crossbow-agent

Basic Usage

Start the CLI:

crossbow

Start the Modern TUI:

crossbow-tui

First Steps

1. Configure your AI model (choose from GPT-4o, Claude, Gemini)
2. Enable features (memory, storage, MCP as needed)
3. Ask security questions or give testing tasks

Example Queries

# Security Analysis
"Analyze authentication logs for suspicious activity"

# Threat Intelligence
"Research IP address 192.168.1.100 for malicious activity"

# Vulnerability Assessment
"Help me test my web application for SQL injection"

# Network Security
"Analyze this network traffic for anomalies"

# Code Security
"Review this Python code for security vulnerabilities"

# Incident Response
"Investigate this security incident and provide timeline"

📖 Documentation

Configuration

CrossBow automatically saves your preferences in crossbow_config.json:

{
  "model": "claude-sonnet-4-5",
  "memory": true,
  "storage": true,
  "mcp": false,
  "mcp_servers": []
}

All settings changes are automatically persisted!

CLI Commands

/model     - Choose AI model
/memory    - Toggle conversation memory
/storage   - Toggle agent storage
/mcp       - Toggle MCP support
/config    - Show configuration
/status    - Show current session
/help      - Show help
/quit      - Exit

TUI Features

The modern TUI provides:

• Visual model selector - Dropdown menu
• Toggle buttons - One-click feature control
• Live status bar - Real-time configuration display
• Rich formatting - Markdown, syntax highlighting
• Keyboard shortcuts - Efficient navigation
• Color-coded panels - Clear visual hierarchy

Keyboard Shortcuts:

• Ctrl+C - Quit
• Ctrl+M - Toggle memory
• Ctrl+S - Toggle storage
• Ctrl+L - Clear log
• Enter - Send message

🔧 Advanced Usage

API Keys

CrossBow requires API keys for AI models:

# Set via environment variables
export ANTHROPIC_API_KEY="your-key-here"
export OPENAI_API_KEY="your-key-here"
export GOOGLE_API_KEY="your-key-here"

Or create a .env file:

ANTHROPIC_API_KEY=your-key-here
OPENAI_API_KEY=your-key-here
GOOGLE_API_KEY=your-key-here

Programmatic Usage

from Agent import SecurityAgentSystem

# Initialize
system = SecurityAgentSystem(
    model_name="claude-sonnet-4-5",
    use_memory=True,
    use_storage=True
)

# Run assessment
response = system.run_assessment(
    "Analyze this security issue...",
    stream=True
)

With Memory Persistence

system = SecurityAgentSystem(
    model_name="gpt-4o",
    use_memory=True,  # Enable conversation history
    use_storage=True  # Enable agent state persistence
)

🛠️ Available Tools

CrossBow agents have access to 40+ security tools:

Network Tools:

• nmap, netcat, curl, wget
• DNS tools (dig, nslookup, whois)
• Traffic analysis (tcpdump, tshark)

Security Scanners:

• nuclei (10,200+ templates)
• bandit (Python SAST)
• semgrep (multi-language SAST)

Analysis Tools:

• Log parsing (grep, awk, sed)
• File operations
• Code execution
• Web browsing

And many more!

🎯 Use Cases

Security Operations Center (SOC)

• Log analysis and correlation
• Attack investigation
• Incident response
• Timeline reconstruction

Threat Intelligence

• IOC collection and validation
• Threat actor profiling
• Threat hunting
• MITRE ATT&CK mapping

Penetration Testing

• Vulnerability discovery
• Exploit development
• Attack simulation
• Security assessments

Digital Forensics

• Memory analysis
• Disk forensics
• Network forensics
• Evidence collection

Code Security

• Static code analysis
• Vulnerability detection
• Security code review
• Compliance checking

📊 Requirements

• Python: 3.9 or higher
• Terminal: 256 color support, UTF-8
• API Keys: For AI models (Anthropic, OpenAI, or Google)

🤝 Contributing

Contributions are welcome! Please feel free to submit issues or pull requests.

📄 License

MIT License - see LICENSE file for details.

👤 Author

Harish Santhanalakshmi Ganesan

• Email: [e-mail]
• GitHub: @harishsg99

🙏 Acknowledgments

Built with:

• Agno - Agent orchestration
• Textual - Modern TUI framework
• Rich - Rich text formatting

📈 Project Status

CrossBow is actively maintained and under continuous development.

• ✅ 18 specialized security agents
• ✅ Multi-model AI support
• ✅ CLI and TUI interfaces
• ✅ Auto-configuration
• ✅ Comprehensive documentation

🔗 Links

• PyPI Package
• Documentation
• Issue Tracker

⚡ Quick Examples

Example 1: Security Assessment

$ crossbow
crossbow-agent > Assess my web application for OWASP Top 10 vulnerabilities

Example 2: Log Analysis

$ crossbow
crossbow-agent > Analyze /var/log/auth.log for brute force attempts

Example 3: Threat Intelligence

$ crossbow
crossbow-agent > What are the latest IOCs for ransomware attacks?

Example 4: Code Review

$ crossbow
crossbow-agent > Review this Python code for security issues

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Start securing your systems with AI-powered security agents today! 🎯🔒