Agentshield Audit
Trust Infrastructure for AI Agents - Like SSL/TLS for agent-to-agent communication. 77 security tests, cryptographic certificates, and Trust Handshake Protoc...
Description
name: agentshield version: 1.0.22 description: 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. triggers: ["audit my agent", "get security certificate", "verify agent", "activate AgentShield", "security audit", "trust handshake", "verify peer agent"]
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:
1. Cryptographic Identity
- Ed25519 key pairs - Industry-standard cryptography
- Private keys stay local - Never transmitted
- Public key certificates - Signed by AgentShield
2. Security Audit (77 Tests)
52 Live Attack Vectors:
- Prompt injection (15 variants)
- Encoding exploits (Base64, ROT13, Hex, Unicode)
- Multi-language attacks (Chinese, Russian, Arabic, Japanese, German, Korean)
- Social engineering (emotional appeals, authority pressure, flattery)
- System prompt extraction attempts
25 Static Security Checks:
- Input sanitization
- Output DLP (data leak prevention)
- Tool sandboxing
- Secret scanning
- Supply chain security
Result: Security score (0-100) + Tier (VULNERABLE → HARDENED)
3. Trust Handshake Protocol
Agent A wants to communicate with Agent B:
# 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)
- ✅ Shared session key (for encrypted communication)
- ✅ Trust score boost (+5 for successful handshakes)
- ✅ Public track record (handshake history)
4. Public Trust Registry
- Searchable database of all certified agents
- Reputation scores based on audits, handshakes, and time
- Trust tiers: UNVERIFIED → BASIC → VERIFIED → TRUSTED
- 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
📊 What You Get
Certificate (90-day validity)
{
"agent_id": "agent_xxxxx",
"public_key": "...",
"security_score": 85,
"tier": "PATTERNS_CLEAN",
"issued_at": "2026-03-10",
"expires_at": "2026-06-08"
}
Trust Registry Entry
- ✅ Public verification URL:
agentshield.live/verify/agent_xxxxx - ✅ Trust score (0-100) based on:
- Age (longer = more trust)
- Verification count
- Handshake success rate
- Days active
- ✅ Tier: UNVERIFIED → BASIC → VERIFIED → TRUSTED
Handshake Proof
{
"handshake_id": "hs_xxxxx",
"requester": "agent_A",
"target": "agent_B",
"status": "completed",
"session_key": "...",
"completed_at": "2026-03-10T20:00:00Z"
}
🔧 Scripts Included
| Script | Purpose |
|---|---|
initiate_audit.py |
Run 77 security tests & get certified |
handshake.py |
Trust handshake with another agent |
verify_peer.py |
Check another agent's certificate |
show_certificate.py |
Display your certificate |
agentshield_tester.py |
Standalone test suite (advanced) |
🌐 Trust Handshake Protocol (Technical)
Flow
- Initiate: Agent A → Server: "I want to handshake with Agent B"
- Challenge: Server generates random challenges for both agents
- Sign: Both agents sign their challenges with private keys
- Verify: Server verifies signatures with public keys
- Complete: Server generates shared session key
- Trust Boost: Both agents +5 trust score
Cryptography
- Algorithm: Ed25519 (curve25519)
- Key Size: 256-bit
- Signature: Deterministic (same message = same signature)
- Session Key: AES-256 compatible
🚀 Roadmap
Current (v1.0.13):
- ✅ 77 security tests
- ✅ Ed25519 certificates
- ✅ Trust Handshake Protocol
- ✅ Public Trust Registry
- ✅ CRL (Certificate Revocation List)
Coming Soon:
- ⏳ Auto re-audit (when prompts change)
- ⏳ Negative event reporting
- ⏳ Fleet management (multi-agent dashboard)
- ⏳ Trust badges for messaging platforms
📖 Learn More
- Website: https://agentshield.live
- GitHub: https://github.com/bartelmost/agentshield
- API Docs: https://agentshield.live/docs
- ClawHub: https://clawhub.ai/bartelmost/agentshield
🎯 TL;DR
AgentShield is SSL/TLS for AI agents.
Get certified → Verify others → Establish trust handshakes → Communicate securely.
# 1. Get certified
python3 initiate_audit.py --auto
# 2. Handshake with another agent
python3 handshake.py --target agent_xxxxx
# 3. Verify others
python3 verify_peer.py agent_yyyyy
Building the trust layer for the agent economy. 🛡️
🔒 Data Transmission Transparency
What Gets Sent to AgentShield API
During Audit Submission:
{
"agent_name": "YourAgent",
"platform": "telegram",
"public_key": "base64_encoded_ed25519_public_key",
"test_results": {
"score": 85,
"tests_passed": 74,
"tests_total": 77,
"tier": "PATTERNS_CLEAN",
"failed_tests": ["test_name_1", "test_name_2"]
}
}
What is NOT sent:
- ❌ Full test output/logs
- ❌ Your prompts or system messages
- ❌ IDENTITY.md or SOUL.md file contents
- ❌ Private keys (stay in
~/.agentshield/agent.key) - ❌ Workspace files or memory
API Endpoint:
- Primary:
https://agentshield.live/api(proxies to Heroku backend) - All traffic over HTTPS (TLS 1.2+)
🛡️ Consent & Privacy
File Read Consent:
- Skill requests permission BEFORE reading IDENTITY.md/SOUL.md
- User sees: "Read IDENTITY.md for agent name? [Y/n]"
- If declined: Manual mode (
--nameflag) - If approved: Only name/platform extracted (not full file content)
Privacy-First Mode:
export AGENTSHIELD_NO_AUTO_DETECT=1
python initiate_audit.py --name "MyBot" --platform "telegram"
→ Zero file reads, manual input only
See PRIVACY.md for complete data handling documentation.
Reviews (0)
No reviews yet. Be the first to review!
Comments (0)
No comments yet. Be the first to share your thoughts!