A comprehensive Python framework for managing agent identities, authentication, authorization, and trust in multi-agent systems.
This framework provides a complete solution for agent identity management with enterprise-grade security features, compliance support, and intelligent trust scoring.
System Architecture
┌─────────────────────────────────────────────────────────────┐
│ Web Dashboard (Streamlit) │
├─────────────────────────────────────────────────────────────┤
│ REST API Layer (FastAPI) │
├─────────────────────────────────────────────────────────────┤
│ Core IAM Engine │
│ ┌─────────────┬─────────────┬─────────────┬─────────────┐ │
│ │ Agent │ Authentication│ Authorization│ Session │ │
│ │ Identity │ Manager │ Manager │ Manager │ │
│ └─────────────┴─────────────┴─────────────┴─────────────┘ │
│ ┌─────────────┬─────────────┬─────────────┬─────────────┐ │
│ │ Federated │ Credential │ Agent │ Transport │ │
│ │ Identity │ Manager │ Registry │ Security │ │
│ └─────────────┴─────────────┴─────────────┴─────────────┘ │
│ ┌─────────────┬─────────────┬─────────────────────────────┐│
│ │ Audit & │ Intelligence│ Trust Scoring & ││
│ │ Compliance │ Engine │ Behavioral Analytics ││
│ └─────────────┴─────────────┴─────────────────────────────┘│
├─────────────────────────────────────────────────────────────┤
│ Data Layer (SQLite/PostgreSQL) │
└─────────────────────────────────────────────────────────────┘
Key Components:
- Frontend: Streamlit web dashboard for management
- API Layer: FastAPI REST endpoints for integration
- Core Engine: 10 integrated security modules
- Data Layer: Persistent storage with encryption
- Agent Identity: UUID-based identities with metadata and cryptographic keys
- Digital Signatures: Ed25519 and RSA support for identity verification
- DID Support: Decentralized Identifier document generation
- JWT Authentication: Secure token-based authentication
- Cryptographic Auth: Challenge-response with digital signatures
- mTLS Support: Mutual TLS certificate-based authentication
- Multi-Factor Auth: Configurable multi-factor authentication flows
- RBAC: Role-Based Access Control with inheritance
- ABAC: Attribute-Based Access Control with policy engine
- PBAC: Policy-Based Access Control with custom rules
- Hybrid Engine: Combine multiple authorization approaches
- Secure Sessions: Token lifecycle with TTL and refresh
- Audit Trails: Comprehensive session activity logging
- Rate Limiting: Configurable limits and security policies
- Multi-Session Support: Agent session limits and management
- OIDC Support: OpenID Connect integration
- SAML Integration: SAML 2.0 identity provider support
- DIDComm: Decentralized identity communication
- Trust Brokers: Cross-domain trust relationships
- Secure Storage: Encrypted credential vault with rotation
- Key Rotation: Automated and policy-based rotation
- Multiple Backends: In-memory and file-based storage
- Credential Types: API keys, passwords, certificates, tokens
- Discovery Service: Agent registration and lookup
- Persistent Storage: SQLite and in-memory backends
- Search & Filter: Advanced query capabilities
- Audit Logging: Complete registry operation tracking
- Multi-Protocol: HTTP/HTTPS, gRPC, WebSocket, STDIO support
- Security Enforcement: Transport-layer security policies
- Identity Extraction: Automatic identity binding from requests
- Rate Limiting: Per-agent and per-transport limits
- Comprehensive Logging: All identity operations tracked
- Compliance Frameworks: GDPR, HIPAA, SOX, PCI-DSS support
- Integrity Verification: Cryptographic audit trail protection
- Automated Reports: Compliance violation detection
- Trust Scoring: ML-based trust and reputation scoring
- Anomaly Detection: Behavioral pattern analysis
- Risk Assessment: Dynamic risk level calculation
- Behavioral Profiling: Agent activity pattern learning
pip install -r requirements.txtfrom agent_identity import AgentIdentity, AgentMetadata, IdentityClaims
from authentication import JWTAuthentication, AuthenticationManager
from authorization import RBACEngine, Role
from session_manager import SessionManager, InMemorySessionStore, AuditLogger
# Create an agent identity
metadata = AgentMetadata(
name="My Agent",
agent_type="service_bot",
version="1.0.0",
organization="MyOrg"
)
claims = IdentityClaims(
role="agent",
permissions=["read", "write"],
scopes=["user_data"]
)
agent = AgentIdentity(metadata=metadata, claims=claims)
# Set up authentication
auth_manager = AuthenticationManager()
jwt_auth = JWTAuthentication(secret_key="your-secret-key")
auth_manager.register_method("jwt", jwt_auth, is_default=True)
# Generate and verify token
token = jwt_auth.generate_token(agent)
result = auth_manager.authenticate({'token': token}, 'jwt')
print(f"Authentication successful: {result.success}")
print(f"Agent ID: {result.agent_id}")from authorization import HybridAuthorizationEngine, Policy, PolicyRule, Effect
from session_manager import SessionManager
from agent_registry import AgentRegistry, InMemoryAgentStorage, RegistryAuditor
from credential_manager import CredentialManager, InMemoryCredentialStore, FernetEncryption
from audit_compliance import AuditManager, SQLiteAuditStorage, ComplianceFramework
from agent_intelligence import AgentIntelligenceEngine
# Set up comprehensive system
session_store = InMemorySessionStore()
session_manager = SessionManager(session_store)
registry_storage = InMemoryAgentStorage()
registry = AgentRegistry(registry_storage)
credential_store = InMemoryCredentialStore()
credential_encryption = FernetEncryption()
credential_manager = CredentialManager(credential_store, credential_encryption)
audit_storage = SQLiteAuditStorage("audit.db")
audit_manager = AuditManager(audit_storage)
intelligence_engine = AgentIntelligenceEngine()
# Register agent
registry.register_agent(
agent,
endpoints=["https://my-agent.example.com"],
capabilities=["text_processing", "data_analysis"]
)
# Create session
from authentication import AuthenticationResult
auth_result = AuthenticationResult(success=True, agent_id=agent.agent_id, auth_method="jwt")
session_id = session_manager.create_session(agent, auth_result)
# Store credentials
api_key_id = credential_manager.store_credential(
name="External API Key",
credential_data="secret_api_key_123",
credential_type=CredentialType.API_KEY,
owner_agent_id=agent.agent_id
)
# Log audit event
audit_manager.log_event(
AuditEventType.AUTH_SUCCESS,
agent_id=agent.agent_id,
session_id=session_id,
details={"method": "jwt"}
)
# Calculate trust score
events = audit_manager.query_events(AuditQuery(agent_id=agent.agent_id))
trust_score = intelligence_engine.calculate_trust_score(agent.agent_id, events)
print(f"Trust Score: {trust_score.overall_score:.3f}")
print(f"Risk Level: {trust_score.risk_level.value}")- AgentIdentity: Core identity representation with cryptographic keys
- Authentication: Multi-method authentication with JWT, signatures, mTLS
- Authorization: Flexible policy-based access control
- SessionManager: Secure session lifecycle management
- FederatedIdentity: Cross-domain identity federation
- CredentialManager: Secure credential storage and rotation
- AgentRegistry: Agent discovery and registration service
- TransportBinding: Protocol-agnostic identity binding
- AuditCompliance: Comprehensive audit logging and compliance
- AgentIntelligence: ML-based trust scoring and anomaly detection
- End-to-End Encryption: All sensitive data encrypted at rest and in transit
- Digital Signatures: Cryptographic verification of agent actions
- Zero Trust Architecture: Never trust, always verify approach
- Audit Trails: Immutable audit logs with integrity verification
- Anomaly Detection: ML-based behavioral analysis
- Compliance: Built-in support for regulatory frameworks
- Modular Design: Use only the components you need
- Pluggable Backends: Support for various storage systems
- Async Support: Non-blocking operations where applicable
- Caching: Intelligent caching for performance
- Federation: Scale across trust domains
# Database configuration
AGENT_IDENTITY_DB_PATH=/path/to/database
AGENT_IDENTITY_ENCRYPTION_KEY=your-encryption-key
# Authentication configuration
JWT_SECRET_KEY=your-jwt-secret
JWT_TOKEN_TTL=3600
# Session configuration
SESSION_TTL=3600
MAX_SESSIONS_PER_AGENT=5
# Audit configuration
AUDIT_LOG_PATH=/path/to/audit.log
ENABLE_AUDIT_ENCRYPTION=true
# Compliance configuration
COMPLIANCE_FRAMEWORKS=gdpr,hipaa
DATA_RETENTION_DAYS=2555 # 7 yearsFor production deployments, consider:
- Database Backend: Use PostgreSQL or MySQL instead of SQLite
- Redis Sessions: Use Redis for distributed session storage
- HSM Integration: Hardware Security Module for key management
- Load Balancing: Distribute across multiple instances
- Monitoring: Integrate with Prometheus/Grafana
- Backup Strategy: Regular encrypted backups
- Disaster Recovery: Multi-region deployment
- Key Management: Use HSM or cloud KMS for production keys
- Secret Rotation: Implement automated credential rotation
- Network Security: Use TLS 1.3 for all communications
- Access Control: Follow principle of least privilege
- Monitoring: Implement real-time security monitoring
- Incident Response: Have procedures for security incidents
- Regular Audits: Conduct security assessments
The framework protects against:
- Identity Spoofing: Cryptographic verification prevents impersonation
- Credential Theft: Encrypted storage and rotation limit exposure
- Session Hijacking: Secure session management with integrity checks
- Privilege Escalation: Fine-grained authorization controls
- Insider Threats: Comprehensive audit trails and anomaly detection
- Compliance Violations: Automated compliance monitoring
# Install development dependencies
pip install pytest pytest-asyncio coverage
# Run tests
pytest tests/
# Run with coverage
coverage run -m pytest tests/
coverage report# Format code
black agent_identity/
# Check linting
flake8 agent_identity/
# Type checking
mypy agent_identity/- Fork the repository
- Create a feature branch
- Implement your changes with tests
- Ensure code quality checks pass
- Submit a pull request
This framework is inspired by and implements concepts from the following research:
A Novel Zero-Trust Identity Framework for Agentic AI: Decentralized Authentication and Fine-Grained Access Control
Ken Huang, Vineeth Sai Narajala, John Yeoh, Ramesh Raskar, Youssef Harkati, Jerry Huang, Idan Habler, Chris Hughes
arXiv:2505.19301 [cs.CR] - https://arxiv.org/abs/2505.19301
Agent Name Service (ANS): A Universal Directory for Secure AI Agent Discovery and Interoperability
Ken Huang, Vineeth Sai Narajala, Idan Habler, Akram Sheriff
arXiv:2505.10609 [cs.CR] - https://arxiv.org/abs/2505.10609
These papers provide the theoretical foundation for the zero-trust identity architecture, decentralized authentication mechanisms, and fine-grained access control systems implemented in this framework.
This project is licensed under the MIT License - see the LICENSE file for details.
For support and questions:
- Documentation: Framework Docs
- Issues: GitHub Issues
- Security:
- Initial release with all core components
- Full authentication and authorization support
- Comprehensive audit and compliance framework
- Agent intelligence and trust scoring
- Multi-protocol transport binding
- Federated identity support
- GraphQL API interface
- Kubernetes operator
- Enhanced ML models for trust scoring
- Additional compliance frameworks
- Performance optimizations
- Mobile agent support