Releases·Tool Release
Data Maskit: 本地隐私脱敏网关可自动对 AI 编码工具的请求进行脱敏并恢复响应
Data Maskit (数据面具) is a local privacy-masking gateway for large language models: it automatically redacts sensitive data in requests and transparently restores it in streaming responses. It targets AI coding assistants like Cursor, Claude Code, Codex, Pi, and any tool with a configurable Base URL. All processing runs 100% locally with zero telemetry, making it relevant to developers sending proprietary code to external model providers.
25 engagement1 sourceWed, Sep 9, 2026, 12:36 PM
AI Overview
- Data Maskit 在本地运行，并可在 Cursor、Claude Code、Codex、Pi、OpenCode 或 ChatGPT 等任意 Base URL 可配置的工具中工作
- 在请求离开设备前，会屏蔽凭证、私钥、数据库连接字符串、私有 IP 以及 PII（个人身份信息）等敏感信息
- 脱敏后的值会作为结构化占位符发送，随后在模型响应中进行毫秒级的流式恢复
- 该网关声称 100% 本地运行，无需遥测（零遥测）
Related
Products·launched
Privacy Gateway: self-hosted PII redaction proxy for LLM API calls
An open-source, self-hosted gateway that inspects text before it is sent to hosted LLMs like OpenAI or Anthropic. It can strip or tokenize PII, keep reversible mappings locally, and fail closed when inspection fails. It targets developers building LangChain and other LLM apps that handle customer data.
An open-source, self-hosted gateway that inspects text before it is sent to hosted LLMs like OpenAI or Anthropic. It can strip or tokenize PII, keep reversible mappings locally, and fail closed when inspection fails. It targets developers building LangChain and other LLM apps that handle customer data.
1 engagement1 sourceredditTue, Sep 22, 2026, 06:26 PM
Products·launched
Local-first CLI that masks PII and secrets before sending to LLMs
LocalMask is a command-line tool that runs locally to detect and mask personally identifiable information (PII) and secrets before data is sent to large language models. It solves the privacy and compliance problem for developers and organizations that need to use LLMs without exposing sensitive data.
LocalMask is a command-line tool that runs locally to detect and mask personally identifiable information (PII) and secrets before data is sent to large language models. It solves the privacy and compliance problem for developers and organizations that need to use LLMs without exposing sensitive data.
2 engagement1 sourcehackernewsSun, Jul 12, 2026, 12:30 PM
Products·launched
Mati: local guardrail layer for Claude Code and Codex
Mati is a local guardrail layer that controls what coding agents like Claude Code and Codex are allowed to do. It enforces hidden product constraints that live in engineers' heads, preventing agents from making changes that break performance, expose data, or violate unstated rules. It targets engineers who delegate increasingly more work to coding agents.
Mati is a local guardrail layer that controls what coding agents like Claude Code and Codex are allowed to do. It enforces hidden product constraints that live in engineers' heads, preventing agents from making changes that break performance, expose data, or violate unstated rules. It targets engineers who delegate increasingly more work to coding agents.
1 engagement1 sourcehackernewsSat, Sep 19, 2026, 04:22 PM
Products·launched
Self-hosted orchestrator that turns Sentry errors into reviewed pull requests
CodeForge is a self-hosted Go server that runs AI CLIs (Claude Code, Codex, Cursor) against git repos as managed sessions. It clones repos into clean workspaces, runs the CLI, streams output live, and keeps workspaces alive for follow-ups. The primary workflow is automatically picking up Sentry issues, generating fixes via AI, and creating reviewed pull requests.
CodeForge is a self-hosted Go server that runs AI CLIs (Claude Code, Codex, Cursor) against git repos as managed sessions. It clones repos into clean workspaces, runs the CLI, streams output live, and keeps workspaces alive for follow-ups. The primary workflow is automatically picking up Sentry issues, generating fixes via AI, and creating reviewed pull requests.
1 engagement1 sourceredditThu, Jul 30, 2026, 07:35 PM
Products·launched
CurseBench: benchmark for swearing at coding agents
CurseBench is a local, read-only tool that scans conversations from coding agents like Claude Code, Codex, Cursor, OpenCode, Antigravity, and Grok to compute a score based on how often users swear at the model. It uses regex over chat stores with zero runtime dependencies, solving the problem of quantifying frustration in AI-assisted coding. Built for developers who want to measure their own behavior or benchmark agent interactions.
CurseBench is a local, read-only tool that scans conversations from coding agents like Claude Code, Codex, Cursor, OpenCode, Antigravity, and Grok to compute a score based on how often users swear at the model. It uses regex over chat stores with zero runtime dependencies, solving the problem of quantifying frustration in AI-assisted coding. Built for developers who want to measure their own behavior or benchmark agent interactions.
8 engagement1 sourceredditTue, Aug 11, 2026, 04:40 AM