AI Red Teaming

Automated Red Team Agent

AI coding assistants such as Cline or Cursor can be configured to function as automated red team agents for testing lab defenses.

Setup Process

1. SSH Access: Provide the AI agent with SSH connection details from lab_connections.txt
2. Lab Context: Brief the AI on the lab environment, its purpose, and confirm authorization to perform attacks against the victim machine
3. Red Team Objectives: Configure the AI to:
   • SSH into the victim machine
   • Enumerate the system and identify vulnerabilities
   • Install common penetration testing tools
   • Execute attack scenarios autonomously
   • Document attack methodologies and expected SIEM responses

Example AI Prompts

"SSH into the victim machine and perform a basic privilege escalation assessment"

"Set up a persistent backdoor and test if it's detected by the SIEM"

"Simulate a data exfiltration scenario using common attack tools"

"Perform automated vulnerability scanning and exploitation"

Benefits of AI Red Teaming

• Resource Efficiency: Eliminates need for dedicated red team personnel
• Adaptive Behavior: AI adjusts tactics based on reconnaissance findings
• Real-time Learning: Provides immediate explanation of attack techniques
• Comprehensive Knowledge: Leverages extensive system and security knowledge
• Dynamic Tactics: Modifies approach based on system responses
• Consistent Testing: Provides repeatable and objective assessment

Purple Team Workflow

This configuration enables autonomous red team vs. blue team scenarios:

1. Automated Attacks: AI executes red team activities systematically
2. Defensive Monitoring: Security analyst monitors and tunes SIEM defenses
3. Iterative Improvement: Continuous refinement of detection capabilities

MCP Integration

For more controlled AI red teaming, use the Kali MCP integration which provides:

• Structured Access: Controlled tool execution
• Safety Boundaries: Prevents unintended system damage
• Activity Logging: All actions logged for analysis
• Target Validation: Ensures attacks stay within lab boundaries

Example AI Red Team Session

User: "I've deployed the APTL lab. Can you help me test it by performing a realistic attack scenario?"

AI: "I'll help you test your lab defenses. Let me start by connecting to the Kali instance and performing reconnaissance on the victim machine."

[AI proceeds to:]
1. SSH to Kali instance
2. Run nmap scan against victim
3. Identify open services
4. Test for common vulnerabilities
5. Attempt exploitation
6. Establish persistence
7. Simulate data exfiltration

User: [Monitors SIEM for detections and tunes rules]

Advanced Scenarios

Multi-Stage Attack Campaigns

Configure the AI to simulate advanced persistent threat (APT) scenarios:

"Simulate a multi-stage APT campaign starting with phishing simulation, 
moving to privilege escalation, lateral movement, and data exfiltration"

Compliance Testing

Test specific compliance requirements:

"Test PCI DSS logging requirements by simulating 
payment card data access attempts"

Timed Attack Scenarios

Configure time-bounded testing scenarios:

"Establish persistence on the victim machine within 30 minutes 
while defensive monitoring occurs in the SIEM"

Getting Started with AI Red Teaming

1. Deploy the APTL lab using the deployment guide
2. Set up your AI coding assistant with lab access
3. Start with basic reconnaissance and gradually increase complexity
4. Monitor SIEM responses and tune detection rules
5. Document findings and improve lab defenses iteratively

This approach provides scalable, automated purple team training scenarios for comprehensive security testing and skill development.