Trust Infrastructure for AI Agents - Like SSL/TLS for agent-to-agent communication. 77 security tests, cryptographic certificates, and Trust Handshake Protocol for establishing secure channels between agents.
Trust Infrastructure for AI Agents - Like SSL/TLS for agent-to-agent communication. 77 security tests, cryptographic certificates, and Trust Handshake Protocol for establishing secure channels between agents.
AgentShield - Trust Infrastructure for AI Agents
The trust layer for the agent economy. Like SSL/TLS, but for AI agents.
🔐 Cryptographic Identity - Ed25519 signing keys
🤝 Trust Handshake Protocol - Mutual verification before communication
📋 Public Trust Registry - Reputation scores & track records
✅ 77 Security Tests - Comprehensive vulnerability assessment
🔒 Privacy Disclosure: See PRIVACY.md for detailed data handling information.
🎯 The Problem
Agents need to communicate with other agents (API calls, data sharing, task delegation). But how do you know if another agent is trustworthy?
Has it been compromised?
Is it leaking data?
Can you trust its responses?
Without a trust layer, agent-to-agent communication is like HTTP without SSL - unsafe and unverifiable.
💡 The Solution: Trust Infrastructure
AgentShield provides the trust layer for agent-to-agent communication:
# Step 1: Both agents get certified
python3 initiate_audit.py --auto
# Step 2: Agent A initiates handshake with Agent B
python3 handshake.py --target agent_B_id
# Step 3: Both agents sign challenges# (Automatic in v1.0.13+)# Step 4: Receive shared session key# → Now you can communicate securely!
What you get:
✅ Mutual verification (both agents are who they claim to be)
Revocation list (CRL) - Compromised agents get flagged
🚀 Quick Start
Install
clawhub install agentshield
cd ~/.openclaw/workspace/skills/agentshield*/
Get Certified (77 Security Tests)
# Auto-detect agent name from IDENTITY.md/SOUL.md
python3 initiate_audit.py --auto
# Or manual:
python3 initiate_audit.py --name "MyAgent" --platform telegram
Output:
✅ Agent ID: agent_xxxxx
✅ Security Score: XX/100
✅ Tier: PATTERNS_CLEAN / HARDENED / etc.
✅ Certificate (90-day validity)
Verify Another Agent
python3 verify_peer.py agent_yyyyy
Trust Handshake with Another Agent
# Initiate handshake
python3 handshake.py --target agent_yyyyy
# Result: Shared session key for encrypted communication
📋 Use Cases
1. Agent-to-Agent API Calls
Before: Agent A calls Agent B's API - no way to verify B's integrity With AgentShield: Agent A checks Agent B's certificate + handshake → Verified communication
2. Multi-Agent Task Delegation
Before: Orchestrator spawns sub-agents - can't verify they're safe With AgentShield: All sub-agents certified → Orchestrator knows they're trusted
3. Agent Marketplaces
Before: Download random agents from the internet - no trust guarantees With AgentShield: Browse Trust Registry → Only hire VERIFIED agents
4. Data Sharing Between Agents
Before: Share sensitive data with another agent - hope it doesn't leak With AgentShield: Handshake → Encrypted session key → Secure data transfer
🛡️ Security Architecture
Privacy-First Design
✅ All 77 tests run locally - Your system prompts NEVER leave your device
✅ Private keys stay local - Only public keys transmitted
✅ Human-in-the-Loop - Explicit consent before reading IDENTITY.md/SOUL.md
✅ No environment scanning - Doesn't scan for API tokens
What goes to the server:
Public key (Ed25519)
Agent name & platform
Test scores (passed/failed summary)
What stays local:
Private key
System prompts
Configuration files
Detailed test results
Environment Variables (Optional)
AGENTSHIELD_API=https://agentshield.live # API endpoint
AGENT_NAME=MyAgent # Override auto-detection
OPENCLAW_AGENT_NAME=MyAgent # OpenClaw standard