Protecting Sensitive Data Under NDA with Microsoft Presidio

Microsoft Presidio is an open-source framework for detecting and anonymizing Personally Identifiable Information (PII) in text, images, audio, and more. It uses natural language processing and rule-based logic to identify names, credit card numbers, social security numbers, phone numbers, and other sensitive data before it’s stored, logged, or shared.

When working under an NDA with Microsoft, or building software that processes NDA-bound data, controlling the flow of sensitive information is essential. Presidio can scan raw data streams, redact keywords, and return anonymized versions that still preserve structure for debugging, analytics, and machine learning. It integrates into Python applications, microservices, and cloud pipelines with minimal overhead.

Key components include:

• Presidio Analyzer: Detects predefined and custom PII entities.
• Presidio Anonymizer: Masks or replaces detected data.
• Recognizer Registry: Enables domain-specific patterns that go beyond defaults.
• Extensible Architecture: Supports new recognizers and anonymizers as your use cases expand.

For teams working under a Microsoft NDA, Presidio is not just about compliance—it’s about enforcing security guarantees in code. Instead of depending solely on developer discipline or post-processing filters, you can shift left, embedding detection and redaction at the ingestion point.

You can deploy Microsoft Presidio locally via Docker, in Kubernetes, or directly in cloud functions. Bind it to your message queues, API gateways, or data ingestion layer. Since it’s open source, you can audit the code base and adapt it to internal requirements.

Whether you are protecting client data in log files, anonymizing user feedback, or enforcing contractual secrecy for NDA-protected projects, Presidio gives you precise, testable controls over data exposure.

See how this works in minutes. Run Microsoft Presidio inside a secure, auto-provisioned pipeline at hoop.dev and watch sensitive data vanish before it ever leaves your systems.