Local Pii Anonymization Before Llm Transmission

via “pii detection and anonymization with stateful vault storage”

Open-source LLM input/output security scanner toolkit.

Unique: Integrates stateful Vault class for PII storage and recovery, enabling reversible anonymization workflows; combines regex pattern matching for structured PII (SSN, credit card) with NER models for unstructured PII (names, organizations), supporting both detection and remediation in a single component

vs others: More comprehensive than simple regex-based PII detection because it includes NER for context-aware entity recognition; unlike external PII masking services, runs locally with no API calls, enabling offline operation and compliance with data residency requirements; Vault system enables de-anonymization, supporting workflows where original values must be recovered

via “local-pii-anonymization-before-llm-transmission”

A zero-trust SDK for anonymizing PII locally before sending prompts to LLMs and seamlessly rehydrating the response.

Unique: Implements client-side anonymization with zero transmission of raw PII to external services, using deterministic token mapping that enables perfect rehydration without storing plaintext on remote servers. Combines regex-based pattern matching with optional NER integration for context-aware detection, all executed locally before API calls.

vs others: Unlike cloud-based PII masking services (e.g., AWS Macie, Azure Purview) that require uploading data for scanning, rehydra performs all detection and anonymization locally, eliminating the trust boundary problem and reducing latency by avoiding round-trip API calls.

via “prompt anonymization and pii stripping”