Zero Trust Security Agent 🔒

Cloudflare Workers application implementing an autonomous security agent for API protection with Shadow AI detection and honeypot deception capabilities.

🎯 Overview

This project demonstrates a sophisticated Zero Trust Security Agent that autonomously protects APIs from threats including:

🤖 Shadow AI Detection - Identifies LLM-driven automated attacks
🛡️ Real-time Threat Analysis - Uses Cloudflare's AI models for intelligent decisions
🍯 Deception Honeypots - Wastes attacker time with convincing fake responses
📊 Dynamic Trust Scoring - Maintains IP reputation using Durable Objects
⚡ High Performance - Optimized for speed with parallel processing

🏗️ Architecture

┌─────────────────┐    ┌──────────────────┐    ┌─────────────────┐
│   Client        │────│  Security Agent  │────│  Origin API     │
│   Request       │    │  (Worker)        │    │  (Protected)    │
└─────────────────┘    └──────────────────┘    └─────────────────┘
                              │
                              ├── Durable Objects (Trust Tracking)
                              ├── Workers AI (Threat Analysis)
                              ├── AI Gateway (Enterprise Controls)
                              ├── KV Storage (Security Logs)
                              └── Honeypot Service (Deception)

Core Components

src/index.ts - Main entry point with optimized request routing
src/securityAgent.ts - Autonomous security analysis and decision engine
src/durableObjects.ts - Trust tracking and persistent state management
src/aiGateway.ts - Enterprise AI integration with observability
src/honeypot.ts - Deceptive response generation system
src/types.ts - TypeScript definitions and interfaces

🚀 Quick Start

Prerequisites

Bun installed (https://bun.sh)
Cloudflare account with Workers and AI enabled
Wrangler CLI configured (npx wrangler login)

Installation

# Clone or download the project
cd cf_ai_job_appl

# Install dependencies (minimal - Bun has most built-in)
bun install

# Verify setup
bun run test-all

Local Development

# Run all tests (unit + integration)
bun run test-all

# Build the project
bun run build

# Type checking
bun run type-check

# Test standalone logic (no deployment needed)
bun run test-standalone

# Start local development server
bun run dev

🧪 Testing

The project includes comprehensive testing without requiring your Cloudflare credentials:

Unit Tests

bun test

Tests the core security agent logic with mocked services.

Standalone Integration Tests

bun run test-standalone

Tests the complete security flow including:

✅ Legitimate request processing
✅ Suspicious bot detection
✅ Malicious path blocking
✅ XSS attempt prevention

All Tests

bun run test-all

Runs both unit and integration tests.

📦 Deployment

1. Configure Cloudflare Resources

Update wrangler.toml with your actual resource IDs:

# Replace these mock values with your actual IDs
[[ai.bindings]]
type = "ai_gateway"
name = "AI_GATEWAY"
gateway_id = "your-actual-gateway-id"        # ← Replace this
gateway_token = "your-actual-gateway-token"  # ← Replace this

[[kv_namespaces]]
binding = "SECURITY_LOGS"
id = "your-actual-kv-namespace-id"           # ← Replace this
preview_id = "your-preview-kv-namespace-id"  # ← Replace this

2. Create Required Resources

# Create KV namespace for security logs
npx wrangler kv:namespace create "SECURITY_LOGS"
npx wrangler kv:namespace create "SECURITY_LOGS" --preview

# Create AI Gateway (via Cloudflare dashboard)
# Go to AI > AI Gateway > Create Gateway

3. Deploy

# Deploy to Cloudflare Workers
bun run deploy

# Or with Wrangler directly
npx wrangler deploy

🛡️ Security Features

Autonomous Decision Making

The agent makes intelligent, autonomous decisions based on real-time analysis:

Decision	Trigger	Response
Allow	Low risk (0-35)	Process normally
Monitor	Low-moderate risk (35-60)	Enhanced logging
Honeypot	Moderate risk (60-80)	Deploy deception
Block	High risk (80+)	Deny access

Risk Factors Analyzed

User Agent Patterns - Detects automated tools, bots, scripts
Path Analysis - Identifies suspicious endpoints (/admin, /wp-admin, etc.)
Payload Inspection - Scans for XSS, SQL injection, command injection
Request Patterns - Analyzes frequency, headers, behavior
Trust History - Maintains per-IP reputation scores

Honeypot Strategies

When deploying deception, the agent can:

Fake Data Response - Convincing but fabricated API data
Fake Errors - Realistic error messages with delays
Slow Response - Artificial processing delays
Redirect Loops - Waste computational resources
AI-Generated - Custom deceptive responses via LLM

🔧 Configuration

Environment Variables

Set these in your wrangler.toml:

[vars]
HONEYPOT_MODE = "true"        # Enable/disable honeypot responses
LOG_LEVEL = "debug"           # Logging: debug, info, warn, error
THREAT_THRESHOLD = "5"        # Score threshold for auto-blocking (0-100)

Development vs Production

# Development
[env.development]
vars = { HONEYPOT_MODE = "true", LOG_LEVEL = "debug" }

# Production  
[env.production]
vars = { HONEYPOT_MODE = "true", LOG_LEVEL = "info" }

📊 Monitoring & Observability

Security Event Logging

All security events are logged to multiple destinations:

KV Namespace - Long-term storage (30 days retention)
AI Gateway - AI call observability and usage tracking
Durable Objects - Real-time state and trust scores

Log Types

monitor:ip:timestamp - Enhanced monitoring events
honeypot:ip:timestamp - Deception activations
ai_request:request_id - AI analysis calls
ai_error:request_id - AI service failures

Metrics Dashboard

Access through Cloudflare dashboard:

Request volume and patterns
Security decision distribution
AI Gateway usage and costs
Durable Object performance

🧪 Testing Your Deployment

Once deployed, test the security agent:

Legitimate Request

curl -H "User-Agent: Mozilla/5.0" https://your-worker.your-subdomain.workers.dev/api/users
# Expected: 200 OK with normal response

Suspicious Bot

curl -H "User-Agent: python-requests/2.28.0" https://your-worker.your-subdomain.workers.dev/admin
# Expected: 403 Blocked or honeypot response

Malicious Path

curl https://your-worker.your-subdomain.workers.dev/wp-admin
# Expected: 403 Blocked immediately

XSS Attempt

curl -X POST -H "Content-Type: application/json" \
  -d '{"query":"<script>alert(\"xss\")</script>"}' \
  https://your-worker.your-subdomain.workers.dev/search
# Expected: 403 Blocked or honeypot

⚡ Performance Optimizations

The application is optimized for production use:

Speed Optimizations

Quick Pre-checks - Obviously malicious requests blocked in <1ms
Smart AI Usage - AI only called for moderate+ risk requests
Parallel Processing - Multiple operations run concurrently
Efficient Risk Scoring - Fast pattern matching algorithms

Cost Optimizations

Minimal Dependencies - Uses Bun's built-in tools
Selective AI Calls - Reduces AI Gateway costs
Optimized Durable Objects - Efficient state management
Smart Caching - Reduces redundant calculations

Resource Usage

Memory - ~10MB typical usage
CPU - ~5ms average processing time
AI Calls - Only for requests scoring >30 risk points
Storage - Automatic cleanup with TTL

🔍 Troubleshooting

Common Issues

Tests Failing

# Verify TypeScript compilation
bun run type-check

# Run standalone tests
bun run test-standalone

Deployment Issues

# Check Wrangler authentication
npx wrangler whoami

# Verify resource IDs in wrangler.toml
npx wrangler kv:namespace list

Performance Issues

# Monitor via Cloudflare dashboard
# Adjust THREAT_THRESHOLD in wrangler.toml
# Review AI Gateway usage patterns

Debug Mode

Enable debug logging:

[vars]
LOG_LEVEL = "debug"

View logs:

npx wrangler tail

🛣️ Development Roadmap

Immediate Enhancements

Custom risk scoring rules
Geographic threat analysis
Rate limiting integration
Custom honeypot templates

Advanced Features

Machine learning model training
Threat intelligence feeds
Multi-tenant support
Advanced analytics dashboard

🤝 Contributing

Development Setup

git clone <repository>
cd cf_ai_job_appl
bun install
bun run test-all

Code Style

Use TypeScript for all new code
Follow the existing patterns
Add tests for new features
Update documentation

Testing Requirements

All changes must pass:

bun run test-all      # Unit + integration tests
bun run type-check    # TypeScript validation
bun run build         # Compilation check

📄 License

MIT License - See LICENSE file for details.

🔗 Resources

Built with ❤️ for Cloudflare's Zero Trust Security platform

Name		Name	Last commit message	Last commit date
Latest commit History 1 Commit
dist		dist
src		src
test		test
.gitignore		.gitignore
PROMPTS.md		PROMPTS.md
README.md		README.md
bun.lock		bun.lock
package.json		package.json
test-deployment.js		test-deployment.js
test-standalone.js		test-standalone.js
tsconfig.json		tsconfig.json
wrangler.toml		wrangler.toml

aqilc/cf-ai-malicious-req-security

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