Loading...
🎼
MAESTRO Multi-Agent Security Pattern(MAS)
Comprehensive threat modeling for multi-agent environments with security orchestration
Complexity: highSecurity & Privacy Patterns
🎯 30-Second Overview
Pattern: Orchestrates multiple specialized security agents for comprehensive threat detection
Why: Single agents have blind spots; coordinated ensemble provides defense-in-depth
Key Insight: Specialized roles + Byzantine consensus + reputation weighting = robust security
⚡ Quick Implementation
1Trust Topology:Define agent relationships & trust levels
2Role Assignment:Set specialized security roles per agent
3Coordinate Checks:Orchestrate multi-angle validations
4Consensus Protocol:Aggregate decisions across agents
5Conflict Resolution:Handle disagreements & escalations
Example: trust_matrix → role_delegation → parallel_validation → consensus_aggregation → decision_output
📋 Do's & Don'ts
✅Implement Byzantine fault tolerance for agent consensus
✅Use specialized security agents for different threat types
✅Apply reputation scoring to weight agent contributions
✅Maintain audit trails across all agent interactions
✅Design for graceful degradation if agents fail
❌Trust single agent decisions for critical operations
❌Allow unrestricted agent communication
❌Skip consensus verification in emergencies
❌Ignore agent collusion possibilities
❌Deploy without kill switch capabilities
🚦 When to Use
Use When
- • Complex multi-agent deployments
- • High-stakes decision systems
- • Adversarial environments
- • Cross-organizational AI systems
Avoid When
- • Simple single-agent tasks
- • Low-risk applications
- • Latency-critical operations
- • Resource-constrained environments
📊 Key Metrics
Consensus Time
ms to reach multi-agent agreement
Detection Coverage
% threats caught by ensemble
False Positive Rate
Incorrect consensus decisions
Agent Availability
Uptime across security agents
Collusion Detection
Coordinated attack attempts found
Decision Quality
Accuracy vs single-agent baseline
💡 Top Use Cases
Financial Trading: Multiple agents validate trades before execution
Autonomous Vehicles: Safety agents coordinate perception & decision validation
Healthcare Diagnosis: Specialist agents cross-verify treatment recommendations
Critical Infrastructure: Security agents monitor different attack vectors
Content Moderation: Diverse agents check for different policy violations
References & Further Reading
Deepen your understanding with these curated resources
Contribute to this collection
Know a great resource? Submit a pull request to add it.
🎼
MAESTRO Multi-Agent Security Pattern(MAS)
Comprehensive threat modeling for multi-agent environments with security orchestration
Complexity: highSecurity & Privacy Patterns
🎯 30-Second Overview
Pattern: Orchestrates multiple specialized security agents for comprehensive threat detection
Why: Single agents have blind spots; coordinated ensemble provides defense-in-depth
Key Insight: Specialized roles + Byzantine consensus + reputation weighting = robust security
⚡ Quick Implementation
1Trust Topology:Define agent relationships & trust levels
2Role Assignment:Set specialized security roles per agent
3Coordinate Checks:Orchestrate multi-angle validations
4Consensus Protocol:Aggregate decisions across agents
5Conflict Resolution:Handle disagreements & escalations
Example: trust_matrix → role_delegation → parallel_validation → consensus_aggregation → decision_output
📋 Do's & Don'ts
✅Implement Byzantine fault tolerance for agent consensus
✅Use specialized security agents for different threat types
✅Apply reputation scoring to weight agent contributions
✅Maintain audit trails across all agent interactions
✅Design for graceful degradation if agents fail
❌Trust single agent decisions for critical operations
❌Allow unrestricted agent communication
❌Skip consensus verification in emergencies
❌Ignore agent collusion possibilities
❌Deploy without kill switch capabilities
🚦 When to Use
Use When
- • Complex multi-agent deployments
- • High-stakes decision systems
- • Adversarial environments
- • Cross-organizational AI systems
Avoid When
- • Simple single-agent tasks
- • Low-risk applications
- • Latency-critical operations
- • Resource-constrained environments
📊 Key Metrics
Consensus Time
ms to reach multi-agent agreement
Detection Coverage
% threats caught by ensemble
False Positive Rate
Incorrect consensus decisions
Agent Availability
Uptime across security agents
Collusion Detection
Coordinated attack attempts found
Decision Quality
Accuracy vs single-agent baseline
💡 Top Use Cases
Financial Trading: Multiple agents validate trades before execution
Autonomous Vehicles: Safety agents coordinate perception & decision validation
Healthcare Diagnosis: Specialist agents cross-verify treatment recommendations
Critical Infrastructure: Security agents monitor different attack vectors
Content Moderation: Diverse agents check for different policy violations
References & Further Reading
Deepen your understanding with these curated resources
Contribute to this collection
Know a great resource? Submit a pull request to add it.