Security Coverage Matrix

Mon, 01 Jan 0001 00:00:00 +0000

The following table shows the protection applied at each stage of the agent pipeline and the threat each control is designed to mitigate.

Pipeline Step	Protection Applied	Threat Mitigated
Input	Discovery and Tokenization	Secret/PII in prompts
Reasoning	Guardrails monitoring	Prompt injection
Tool Calls	Intent validation and Authentication	Unauthorized actions
Cross-Agent	Re-tokenization	Data leakage between agents
Output	PII scanning and Re-protect	Sensitive data in responses
Logs	Anonymization	Identity exposure in debug
Storage	Tokenization	PII at rest
Continuous	Semantic Guardrails	Policy violations, anomalies

Sample Code

Mon, 01 Jan 0001 00:00:00 +0000

This section covers the full working implementation of the Privacy-Safe Employee Insights Agent, including project structure, module reference, and language-specific examples. Each code snippet includes a brief description, sample prompt for Cursor, and implementation details.

Project Structure

employee-insights-agent/
├── main.py # End-to-end demo (run this)
├── config.py # Configuration
├── requirements.txt # Dependencies
├── modules/
│ ├── synthetic_data.py # Step 1: Generate data
│ ├── discovery.py # Step 2: Classify fields
│ ├── anonymization.py # Step 3: Anonymize for training
│ ├── masking.py # Step 4: Mask for operations
│ ├── tokenization.py # Step 5: Tokenize for storage
│ ├── unprotect.py # Step 6: Authorized access
│ └── guardrails.py # Step 7: Semantic guardrails
├── webapp/
│ ├── app.py # Flask web portal
│ └── templates/index.html # Dashboard UI
├── samples/
│ ├── synthetic_data/ # Domain-specific generation
│ ├── guardrails/ # Attack scenario tests
│ ├── discovery/ # Codebase scanning
│ ├── protection/ # Tokenization workflows
│ ├── anonymization/ # RAG + debugging
│ └── agentic_workflows/ # Multi-agent protection
└── docs/ # This documentation

Running the Demo

# Install dependencies
pip install -r requirements.txt
# Run complete end-to-end demo
python main.py
# Launch web portal
python webapp/app.py
# Open: http://localhost:5000

Module Reference

Each module covers a distinct stage of the data protection pipeline, from generating synthetic data and classifying sensitive fields to tokenizing, masking, anonymizing, and controlling access to real values.

Protecting Agentic Workflows on

Security Coverage Matrix

Sample Code

Project Structure

Running the Demo

Module Reference