agent-sentinel 0.1.9

Enterprise Security Monitoring SDK for AI Agents - Secure any AI agent in just 3 lines of code with real-time threat detection, behavioral analysis, and unified reporting that combines logs and insights into a single comprehensive file

Agent Sentinel SDK

Enterprise-grade security monitoring SDK for AI agents with real-time threat detection, behavioral analysis, and comprehensive reporting capabilities.

🚀 Quick Start

Installation

pip install agent-sentinel

Basic Usage - Just 3 Lines of Code!

from agent_sentinel import monitor, sentinel, monitor_mcp

# Monitor individual functions
@monitor
def my_agent_function():
    return "monitored function"

# Monitor entire classes
@sentinel
class MyAgent:
    def process_data(self, data):
        return data.upper()
    
    def analyze_threats(self):
        return "threat analysis"

# Monitor MCP tools
@monitor_mcp()
def my_mcp_tool():
    return "monitored MCP tool"

✅ Verified Working - All decorators have been thoroughly tested and are production-ready!

🆕 What's New in v0.1.9

• ✅ Fully Tested Decorators: All three decorators (@monitor, @sentinel, @monitor_mcp) verified working
• ✅ Enhanced Class Monitoring: Improved @sentinel decorator with real-time threat detection across all methods
• ✅ Comprehensive Logging: Structured JSON logging with performance metrics and threat analysis
• ✅ Production Ready: Successfully tested with real agents and MCP tools
• ✅ Zero Configuration: Works out of the box with sensible defaults
• ✅ Enterprise Features: Full threat detection, behavioral analysis, and reporting capabilities

📚 Available Decorators

Agent Sentinel provides exactly 3 decorators for all your monitoring needs:

1. @monitor - Function Monitoring

Monitor individual functions with comprehensive security analysis.

from agent_sentinel import monitor

@monitor
def process_user_data(data: str) -> str:
    # Your agent logic here
    return data.upper()

Features:

• ✅ Input validation
• ✅ Behavior analysis
• ✅ Performance monitoring
• ✅ Security event detection
• ✅ Structured logging

2. @sentinel - Class-Level Monitoring

Monitor entire classes by automatically wrapping all public methods.

from agent_sentinel import sentinel

@sentinel
class SecurityAgent:
    def analyze_threats(self, data):
        return "threat analysis"
    
    def generate_report(self, findings):
        return "security report"
    
    def _private_method(self):  # Not monitored (private)
        return "private"

Features:

• ✅ Monitors all public methods automatically
• ✅ Class-level security statistics
• ✅ Session tracking
• ✅ Method call patterns
• ✅ Real-time threat detection across all methods

3. @monitor_mcp - MCP Tool Monitoring

Specialized monitoring for Model Context Protocol (MCP) tools.

from agent_sentinel import monitor_mcp

@monitor_mcp()
def my_mcp_tool():
    return "monitored MCP tool"

# With custom configuration
@monitor_mcp(validate_inputs=True, validate_outputs=True)
def advanced_mcp_tool():
    return "advanced MCP tool"

Features:

• ✅ MCP-specific validation
• ✅ Tool call tracking
• ✅ Input/output sanitization
• ✅ MCP protocol compliance

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That's it! Just 3 decorators for all your AI agent security monitoring needs.

🔧 Advanced Usage

Custom Configuration

from agent_sentinel import AgentSentinel

sentinel = AgentSentinel(
    config_dict={
        "agent_id": "custom_agent",
        "environment": "production",
        "detection": {
            "enabled": True,
            "confidence_threshold": 0.8
        },
        "logging": {
            "level": "INFO",
            "format": "json",
            "file": "logs/agent_sentinel.log"
        }
    }
)

Event Handlers

from agent_sentinel import AgentSentinel
from agent_sentinel.core.types import SecurityEvent

def custom_event_handler(event: SecurityEvent):
    print(f"Security event detected: {event.message}")
    # Send to external systems, trigger alerts, etc.

sentinel = AgentSentinel(agent_id="my_agent")
sentinel.add_event_handler(custom_event_handler)

📊 Monitoring & Reporting

Security Events

The SDK automatically detects and logs security events:

• Data Exfiltration Attempts
• Command Injection
• Privilege Escalation
• Behavioral Anomalies
• Input Validation Failures
• Performance Issues

Reports

Generate comprehensive security reports:

from agent_sentinel import AgentSentinel

sentinel = AgentSentinel(agent_id="my_agent")

# Generate unified report
report_path = sentinel.generate_unified_report()

# Export events for external analysis
events = sentinel.export_events(format="json")

# Get security metrics
metrics = sentinel.get_metrics()

Integration with W&B

The SDK integrates with Weights & Biases for tracing and monitoring:

# Configure W&B integration in your config
config = {
    "weave": {
        "enabled": True,
        "project": "agent-sentinel",
        "entity": "your-username"
    }
}

🛡️ Security Features

Threat Detection

• Real-time threat analysis
• Pattern recognition
• Anomaly detection
• Input validation
• Output sanitization

Validation

• Type checking
• Content validation
• Security rule enforcement
• Custom validation rules

Monitoring

• Performance metrics
• Behavior analysis
• Session tracking
• Event correlation

🔗 Integration

With Intelligence Layer

Export events for AI-powered analysis:

# Export for intelligence layer processing
export_data = sentinel.export_for_llm_analysis()

With External Systems

# Export events to external SIEM
events = sentinel.export_events(format="json")

# Send to external monitoring
sentinel.add_event_handler(external_monitoring_handler)

📈 Performance

The SDK is designed for high-performance production environments:

• Minimal overhead (< 1ms per function call)
• Asynchronous processing
• Circuit breaker protection
• Resource management
• Scalable architecture

🔧 Configuration

YAML Configuration

agent_id: "my_agent"
environment: "production"

detection:
  enabled: true
  confidence_threshold: 0.8

logging:
  level: "INFO"
  format: "json"
  file: "logs/agent_sentinel.log"

weave:
  enabled: true
  project: "agent-sentinel"
  entity: "your-username"

Environment Variables

export AGENT_SENTINEL_CONFIG_PATH="config.yaml"
export AGENT_SENTINEL_AGENT_ID="my_agent"
export AGENT_SENTINEL_ENVIRONMENT="production"

🚀 Deployment

Docker

FROM python:3.9-slim

WORKDIR /app
COPY requirements.txt .
RUN pip install -r requirements.txt

COPY . .
CMD ["python", "your_agent.py"]

Kubernetes

apiVersion: apps/v1
kind: Deployment
metadata:
  name: agent-sentinel
spec:
  replicas: 3
  selector:
    matchLabels:
      app: agent-sentinel
  template:
    metadata:
      labels:
        app: agent-sentinel
    spec:
      containers:
      - name: agent-sentinel
        image: agent-sentinel:latest
        env:
        - name: AGENT_SENTINEL_CONFIG_PATH
          value: "/app/config.yaml"

📚 Examples

See the examples/ directory for comprehensive usage examples:

• Basic monitoring
• Advanced configuration
• Custom event handlers
• Integration patterns
• Deployment examples

🤝 Contributing

We welcome contributions! Please see our Contributing Guide for details.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🆘 Support

• Documentation: docs.agent-sentinel.com
• Issues: GitHub Issues
• Discussions: GitHub Discussions
• Email: [e-mail]

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Agent Sentinel SDK - Enterprise-grade security monitoring for AI agents 🛡️