SkillHub

agentshield-audit

v1.0.22

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.

Sourced from ClawHub, Authored by bartelmost

Installation

Please help me install the skill `agentshield-audit` from SkillHub official store. npx skills add bartelmost/agentshield-audit

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

  1. Initiate: Agent A → Server: "I want to handshake with Agent B"
  2. Challenge: Server generates random challenges for both agents
  3. Sign: Both agents sign their challenges with private keys
  4. Verify: Server verifies signatures with public keys
  5. Complete: Server generates shared session key
  6. 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+)


File Read Consent: 1. Skill requests permission BEFORE reading IDENTITY.md/SOUL.md 2. User sees: "Read IDENTITY.md for agent name? [Y/n]" 3. If declined: Manual mode (--name flag) 4. 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.