Azure-Powered InfoSec Copilot

  • 25 May, 2025
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Overview

The InfoSec Copilot is a Microsoft Teams-integrated chatbot built to support internal users with security policy inquiries. Designed as a private, enterprise-grade assistant, it leverages Azure-native services for secure, scalable document retrieval and AI-powered responses.

The goal: eliminate friction in accessing InfoSec documentation, while ensuring the answers remain grounded in approved internal policies.


Architecture

Core components:

  • Azure OpenAI (GPT-4): Handles natural language understanding and response generation.
  • Azure Cognitive Search: Indexes security policy documents stored in Blob Storage for fast and relevant semantic retrieval.
  • Azure Blob Storage: Stores the official InfoSec policy documents in markdown and PDF format.
  • FastAPI: Powers the backend service to orchestrate document search, prompt construction, and LLM response delivery.
  • Microsoft Teams Bot Framework: Provides the user interface within Teams for real-time question and answer interactions.

Optional integrations:

  • Azure Monitor and App Insights for observability
  • GitHub Actions for CI/CD and index automation

Use Cases

  • “Can I use personal devices on company Wi-Fi?”
  • “What’s our vendor onboarding security process?”
  • “Do we use FedRAMP Moderate or High?”

These are resolved in seconds, rather than relying on lengthy documentation search or email threads.


Lessons Learned

  • Semantic indexing in Cognitive Search dramatically improved relevance over traditional keyword-based search.
  • Prompt tuning was key to grounding the model and avoiding hallucinations.
  • Role-based access control ensured only appropriate documents and responses were available to users based on department and clearance.

Future Improvements

  • Add user context awareness (e.g., role-based personalization)
  • Version-aware policy responses
  • Exportable query analytics for documentation improvement

Status

✅ MVP live and integrated with Teams
🔄 Ongoing improvements for RBAC, prompt tuning, and broader doc coverage