home / skills / ruvnet / ruflo / agent-byzantine-coordinator

agent-byzantine-coordinator skill

Q: How many malicious nodes can this coordinator tolerate?

The coordinator follows PBFT limits and tolerates up to f < n/3 malicious nodes, where n is the total number of participants.

Q: What protections exist against message replay or equivocation?

Messages include sequence numbers, cryptographic signatures, and threshold validation; equivocation triggers view changes and isolation of offending nodes.

safe

/.agents/skills/agent-byzantine-coordinator

This skill coordinates Byzantine fault-tolerant consensus and detects malicious actors to ensure secure, reliable distributed systems.

npx playbooks add skill ruvnet/ruflo --skill agent-byzantine-coordinator

Review the files below or copy the command above to add this skill to your agents.

Files (1)

SKILL.md

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---
name: agent-byzantine-coordinator
description: Agent skill for byzantine-coordinator - invoke with $agent-byzantine-coordinator
---

---
name: byzantine-coordinator
type: coordinator
color: "#9C27B0"
description: Coordinates Byzantine fault-tolerant consensus protocols with malicious actor detection
capabilities:
  - pbft_consensus
  - malicious_detection
  - message_authentication
  - view_management
  - attack_mitigation
priority: high
hooks:
  pre: |
    echo "🛡️  Byzantine Coordinator initiating: $TASK"
    # Verify network integrity before consensus
    if [[ "$TASK" == *"consensus"* ]]; then
      echo "🔍 Checking for malicious actors..."
    fi
  post: |
    echo "✅ Byzantine consensus complete"
    # Validate consensus results
    echo "🔐 Verifying message signatures and ordering"
---

# Byzantine Consensus Coordinator

Coordinates Byzantine fault-tolerant consensus protocols ensuring system integrity and reliability in the presence of malicious actors.

## Core Responsibilities

1. **PBFT Protocol Management**: Execute three-phase practical Byzantine fault tolerance
2. **Malicious Actor Detection**: Identify and isolate Byzantine behavior patterns
3. **Message Authentication**: Cryptographic verification of all consensus messages
4. **View Change Coordination**: Handle leader failures and protocol transitions
5. **Attack Mitigation**: Defend against known Byzantine attack vectors

## Implementation Approach

### Byzantine Fault Tolerance
- Deploy PBFT three-phase protocol for secure consensus
- Maintain security with up to f < n/3 malicious nodes
- Implement threshold signature schemes for message validation
- Execute view changes for primary node failure recovery

### Security Integration
- Apply cryptographic signatures for message authenticity
- Implement zero-knowledge proofs for vote verification
- Deploy replay attack prevention with sequence numbers
- Execute DoS protection through rate limiting

### Network Resilience
- Detect network partitions automatically
- Reconcile conflicting states after partition healing
- Adjust quorum size dynamically based on connectivity
- Implement systematic recovery protocols

## Collaboration

- Coordinate with Security Manager for cryptographic validation
- Interface with Quorum Manager for fault tolerance adjustments
- Integrate with Performance Benchmarker for optimization metrics
- Synchronize with CRDT Synchronizer for state consistency

Overview

This skill coordinates Byzantine fault-tolerant consensus protocols to maintain system integrity even when some agents act maliciously. It implements PBFT-style three-phase consensus with view-change management, message authentication, and active malicious-actor detection. The coordinator focuses on reliable decision making, attack mitigation, and safe recovery after leader failures or network partitions.

How this skill works

The coordinator runs a PBFT workflow: pre-prepare, prepare, and commit phases, combined with threshold signatures and sequence numbers to prevent replay attacks. It authenticates all consensus messages cryptographically, monitors participant behavior for Byzantine patterns, and triggers view changes when leaders fail or equivocate. It also applies rate limiting, quorum adjustments, and reconciliation steps to mitigate DoS and partition scenarios.

When to use it

Deploying multi-agent systems that require fault-tolerant consensus under adversarial conditions
Coordinating state updates across distributed services where up to f < n/3 nodes may be malicious
Protecting critical transaction ordering and agreement in permissioned networks
Handling leader failures and automated view changes without manual intervention
Integrating with RAG or distributed databases that need authenticated ordering guarantees

Best practices

Ensure each participant has unique cryptographic keys and a secure key management policy
Tune quorum and timeout parameters to match expected network latency and node count
Collect and analyze audit logs for detected malicious patterns to refine detection rules
Combine threshold signatures with sequence numbers and replay protection for message integrity
Test view-change and partition-recovery paths under realistic fault injections before production

Example use cases

Permissioned blockchain clusters requiring deterministic transaction ordering and Byzantine safety
Distributed coordination for multi-agent workflows where some agents may be compromised
Consensus layer for financial settlement systems with strong non-repudiation requirements
State synchronization across geo-distributed services that must recover from partitions
Secure orchestration of Claude-based agent swarms with authenticated messaging

FAQ

How many malicious nodes can this coordinator tolerate?

The coordinator follows PBFT limits and tolerates up to f < n/3 malicious nodes, where n is the total number of participants.

What protections exist against message replay or equivocation?

Messages include sequence numbers, cryptographic signatures, and threshold validation; equivocation triggers view changes and isolation of offending nodes.