data-masking

Database governance built for humans and agents — controlling changes and access across every major database.

An open-source framework for detecting, redacting, masking, and anonymizing sensitive data (PII) across text, images, and structured data. Supports NLP, pattern matching, and customizable pipelines.

SQL 审核查询平台

Database anonymization and test data management

Privacy proxy for your OpenAI requests

BENERATOR is a leading software solution to generate, obfuscate, pseudonymize and migrate data for development, testing, and training purposes with a model-driven approach.

Never give AI companies your secrets! A local LLM-based privacy filter for LLM users. Seamless integration with your existing AI tools as a Python library / OpenAI SDK replacement / API Gatetway / Web Server.

A free data masking and/or anonymizer library

Clonio is a GDPR and PII compliant CLI that clones production databases into your test, dev and CI stages with automatic anonymization.

A mysqldump anonymizer

Discover, mask, and verify sensitive data in SQL databases — an auditable scan → mask → validate workflow for safe database copies.

Examples scripts that showcase how to use Private AI Text to de-identify, redact, hash, tokenize, mask and synthesize PII in text.

Find and redact sensitive data before it leaks — a fast, offline CLI and Go library that detects PII, secrets, and credentials in files and streams, scores them with context-aware confidence, and redacts them format-preserving. Nothing leaves your host.

Ready-to-run examples showing NoPII PII protection with OpenAI, Anthropic, LangChain, LlamaIndex, and more

已经合入(apache/incubator-kyuubi) ACL Management for Apache Spark SQL with Apache Ranger.

Rust derive macro for redacting sensitive data in std::fmt::Debug

Zero-dependency TypeScript secret and PII redaction for any SDK, logs, HTTP, LLM prompts, and scoped MCP tool boundaries.

Model-driven synthetic test data for CI/CD and analytics - deterministic, privacy-preserving, and domain-aware. Includes Python APIs, XML pipelines, and MCP/IDE integration to orchestrate realistic datasets for finance, healthcare, and other regulated environments.

Go library that detects personally identifiable information in text and structured data and replaces it with deterministic, format-preserving substitutes.

A disposable copy of your production stack for every pull request: masked Postgres, contained third-party APIs, and agents that use your app like people.