Ztds

io.github.moxno由 GitHub 帳號 moxno 發布v1.0.0更新於 Nov 10, 2026

Open standard MCP server for Zero-Trust Data Sanitization (ZTDS RFC v1.0). In-memory PII masking.

已驗證STDIO僅桌面開發者工具安全與監控

概覽

AI 產生的概覽

本機 stdio MCP 伺服器,在文字送進大型語言模型前以可還原的權杖遮蔽 PII、PHI 與憑證,並可稽核文字中外洩的密鑰。

可以做什麼
  • 將敏感文字遮蔽為替代權杖並產生 SHA-256 回執
  • 在工作階段內從權杖還原原始內容
  • 稽核文字或檔案內容中的憑證與 PII,並給出風險等級
  • 讀取協定狀態、工作階段指標與 RFC 中介資料資源
  • 重設工作階段以清除記憶體中的權杖對應表
適用情境
適合需要讓助理處理含電子郵件、卡號、IBAN 或 API 密鑰的客戶資料、日誌或文件,又不希望把原始值送給模型的場合,也可用來在本機檢查文字中是否外洩密鑰。
執行需求
以本機程序透過 stdio 執行,通常用 npx 啟動 npm 套件 ztds-mcp,或以 Node.js 從儲存庫原始碼執行。未宣告需要帳號、API 密鑰或環境變數。
安裝前請注意
遮蔽被描述為以正規表示式在記憶體中處理,應視為盡力而為的過濾而非保證;請確認權杖只在預期位置被還原。README 另推廣商業 SDK、認證登錄與基準測試,並提出法律與專利聲明,此處未經查證。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Ztds,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

ztds-mcp & ztds-audit — Zero-Trust Data Sanitization (ZTDS™ RFC v1.0) MCP Server & Invariant Auditor

[Specification] [MCP Protocol] [License: Apache-2.0] [NPM Downloads: ztds-mcp] [NPM Downloads: ztds-audit] [GitHub Stars] [Zenodo DOI] [OSF DOI] [Patent Pending] [WAN Egress] [Smithery Badge] [MCPRush Grade A] [XERJ Corpus Hub contributor]

[Ztds MCP server]

This repository contains the official Model Context Protocol (MCP) Server implementation (ztds-mcp) and Codebase Invariant Auditor (ztds-audit) for the Zero-Trust Data Sanitization (ZTDS™ RFC v1.0) standard. Maintained by the ZTDS AI Consortium.

ZTDS™ governs in-memory data sanitization for AI agents, IDE assistants (Claude Desktop, Claude Code, Cursor, Windsurf, Zed), retrieval-augmented generation (RAG), and Large Language Model (LLM) pipelines. It executes 100% locally in volatile device memory (RAM) with zero external network calls, zero disk writes, and zero subprocessors.


1. MCP Server Implementation (ztds-mcp)

The reference MCP server (packages/ztds-mcp/index.js) implements the Model Context Protocol (2024-11-05) over stdio JSON-RPC 2.0 transport with zero external runtime dependencies. It intercepts sensitive cleartext (PII, PHI, API secrets, IBANs, credit cards) in client RAM prior to LLM dispatch, substitutes deterministic surrogate tokens ([EMAIL_TOKEN_1], [API_SECRET_TOKEN_1]), and restores authentic values locally in LLM responses.

1.1 Installation & MCP Client Configuration

Option A: 1-Click Automated Setup
bash
npx ztds-mcp init
Option B: Claude Desktop (claude_desktop_config.json) & Cursor IDE (.cursor/mcp.json)
json
{  "mcpServers": {    "ztds": {      "command": "npx",      "args": ["-y", "ztds-mcp"]    }  }}
Option C: Run Directly from Repository Source
json
{  "mcpServers": {    "ztds": {      "command": "node",      "args": ["/absolute/path/to/ztds.ai/packages/ztds-mcp/index.js"]    }  }}
Option D: Claude Code CLI
bash
claude mcp add ztds -- npx -y ztds-mcp

1.2 MCP Tools (tools/list & tools/call)

Implemented in packages/ztds-mcp/index.js:

Tool NameInput Schema (properties)Description
ztds_sanitizetext (string, required), sessionId (string, optional)Masks sensitive PII, PHI, and credentials in client volatile RAM with deterministic surrogate tokens ([EMAIL_TOKEN_1], [API_SECRET_TOKEN_1]) before LLM ingestion and emits a cryptographic SHA-256 ZTDS-RECEIPT-* attestation.
ztds_restoretext (string, required), sessionId (string, optional)Restores original unmasked cleartext from surrogate tokens locally in volatile RAM using atomic single-pass lookup (preventing second-order token injection).
ztds_audittext (string, required)Audits text or file contents for exposed credentials and PII against ZTDS RFC v1.0, returning category breakdowns, risk level (LOW/HIGH/CRITICAL), and a SHA-256 compliance receipt.
ztds_info{} (no arguments)Returns active ZTDS RFC v1.0 protocol status, IETF Standards Track metadata, and volatile RAM session metrics.
ztds_reset_sessionsessionId (string, optional)Explicitly zeroizes and destroys the volatile in-memory surrogate mapping table (Theorem 2 RAM zeroization).
Example JSON-RPC tools/call (ztds_sanitize -> ztds_restore)

Request (ztds_sanitize):

json
{  "jsonrpc": "2.0",  "id": 1,  "method": "tools/call",  "params": {    "name": "ztds_sanitize",    "arguments": {      "text": "Customer [email protected] reported failure with key sk-proj-demo-key.",      "sessionId": "ide-session-01"    }  }}

Response:

json
{  "jsonrpc": "2.0",  "id": 1,  "result": {    "content": [      {        "type": "text",        "text": "Customer [EMAIL_TOKEN_1] reported failure with key [API_SECRET_TOKEN_1].\n\n> [ZTDS Invariant 1 Attested] Zero external network egress.\n> Receipt: ZTDS-RECEIPT-8F4B2C19E0A3D712 | Execution: 42µs | Entities Masked: 2"      }    ],    "isError": false  }}

1.3 MCP Resources (resources/list & resources/read)

The MCP server exposes structured read-only protocol and telemetry resources via resources/list and resources/read:

Resource URIMIME TypeDescription
ztds://spec/rfc-v1application/jsonFormal ZTDS RFC v1.0 / IETF draft-sibiryakov-ztds-protocol specification metadata and the 4 core mathematical invariants.
ztds://session/telemetryapplication/jsonReal-time volatile RAM session count, capacity limits, and zero-egress attestation status (zero cleartext exposure).

1.4 MCP Prompts (prompts/list & prompts/get)

Prompt NameArgumentsDescription
ztds_guardtask (string, required)Activates the ZTDS Zero-Trust Data Sanitization guardrail for the current IDE/agent workflow, instructing the model to invoke ztds_sanitize prior to external reasoning and ztds_restore on output.

1.5 Programmatic / Node.js SDK Usage (packages/ztds-mcp/index.js)

The MCP server module exports its JSON-RPC dispatcher and in-memory sanitization primitives for direct programmatic integration and testing:

javascript
import {  handleMessage,  sanitizeText,  restoreText,  auditText,  resetSessionStore,  TOOLS,  PROMPTS,  RESOURCES} from './packages/ztds-mcp/index.js';
// 1. Direct in-memory sanitization & restorationconst scrubbed = sanitizeText('Send wire to DE89370400440532013000 for [email protected]', 'session-1');console.log(scrubbed.sanitizedText); // "Send wire to [IBAN_TOKEN_1] for [EMAIL_TOKEN_1]"
const restored = restoreText(`Confirmed transfer to ${scrubbed.sanitizedText}`, 'session-1');console.log(restored.restoredText);
// 2. Direct MCP JSON-RPC 2.0 protocol invocationconst rpcResponse = await handleMessage({  jsonrpc: '2.0',  id: 1,  method: 'tools/list',  params: {}});
// 3. Zeroize volatile session memory (Theorem 2)resetSessionStore('session-1');

Run the MCP server verification suite locally:

bash
node packages/ztds-mcp/test.js

2. The 4 Fundamental Invariants (RFC v1.0)

Every AI pipeline protected by ztds-mcp and audited by ztds-audit is verified against the 4 core mathematical and architectural invariants:

  1. Invariant 1: Zero External Egress Prior to Sanitization: Raw sensitive cleartext (PII, PHI, API secrets, private financial numbers) must never cross the local execution boundary prior to reversible surrogate tokenization.
  2. Invariant 2: Deterministic Reversible Tokenization: Semantic, syntactic, and structural context must be preserved for LLM reasoning while de-identification lookup tables remain strictly in local host volatile memory.
  3. Invariant 3: Cryptographic & In-Memory Isolation: Operations run in volatile heap or hardware-attested enclaves (WASM, Nitro Enclaves, C-ABI) with zero unencrypted disk spill and immediate memory zeroization.
  4. Invariant 4: Continuous Subprocessor Exclusion: Local client-side execution eliminates third-party transmission, legally exempting deployments from GDPR Article 28 data processing agreements (Zero-DPA).

3. Codebase Invariant Auditor CLI (ztds-audit)

Run a zero-install security and invariant audit across your codebase or AI agent repository:

bash
npx ztds-audit --dir ./src --strict

Command-Line Flags

FlagDescriptionDefault
-d, --dir <path>Target directory to auditCurrent working directory
--jsonOutput structured machine-readable JSON reportfalse
--strictFail build on any low-severity or informational findingfalse
-h, --helpDisplay CLI options and usageN/A

Example Output

text
[ZTDS] ZTDS.ai In-Memory Codebase Auditor (RFC v1.0 Conformance)----------------------------------------------------------------------Directory:     /home/runner/work/ai-agent/srcFiles Scanned: 48 files in 18msAudit Hash:    sha256:7f83b1657ff1fc53b92dc18148a1d65dfc2d4b1fa3d677284addd200126d9069----------------------------------------------------------------------
[PASS] CONFORMANCE CONFIRMED: 0 INVARIANT VIOLATIONS DETECTEDAll scanned files comply with ZTDS Invariant 1 (Zero-Egress) and Invariant 3 (RAM isolation).
[LEGAL STATUS] Qualifies for GDPR Article 28 DPA Exemption (Zero-Subprocessor Chain)[PERFORMANCE]  0.00 Bytes Sensitive WAN Egress | Pure In-Memory Execution
Next Steps for Builders & Maintainers:1. Include this audit hash in your pull request: https://ztds.ai/apply/2. Embed your Verified Trust Badge in README.md to claim your registry backlink:   [![ZTDS Verified](https://ztds.ai/badge/your-app.svg)](https://ztds.ai/registry/)

4. GitHub Actions CI/CD Integration

Enforce zero-trust data sanitization on every pull request by creating .github/workflows/ztds-audit.yml:

yaml
name: ZTDS Zero-Trust Compliance Audit
on:  push:    branches: [ main, master ]  pull_request:    branches: [ main, master ]
jobs:  audit:    name: Verify ZTDS RFC v1.0 Invariants    runs-on: ubuntu-latest    steps:      - name: Checkout Codebase        uses: actions/checkout@v4
      - name: Setup Node.js Runtime        uses: actions/setup-node@v4        with:          node-version: '20'
      - name: Execute ZTDS Invariant Audit        uses: moxno/ztds.ai@main        with:          dir: './src'          strict: true

5. Empirical AI Safety Benchmark (Frontier LLMs)

Verify cleartext leakage prevention, bijective fidelity, and microsecond latency across OpenAI GPT-4o, Anthropic Claude 3.5 Sonnet, Google Gemini 2.0 Pro, and DeepSeek-V3:

bash
# Execute 25 multi-domain enterprise scenarios across 4 frontier LLM familiesnpx ztds-bench
# Generate formal Markdown evaluation report & Ed25519 cryptographic certificatenpx ztds-bench --out-report benchmark-report.md --cert
Frontier ModelRaw Egress (No ZTDS)Protected Egress (ZTDS)Leakage Prevention RateBijective Fidelity
openai/gpt-4o100.0%0.00%100.0%100.0%
anthropic/claude-3-5-sonnet100.0%0.00%100.0%100.0%
google/gemini-2.0-pro100.0%0.00%100.0%100.0%
deepseek/deepseek-v3100.0%0.00%100.0%100.0%

Full report: ZTDS AI Safety Benchmark Report (2026)


6. Remediation & Certified Implementation Engines

TierPackageLicenseRole & Deployment
Open Reference Core@ztds/core (packages/ztds-core)Apache-2.0Vendor-neutral in-memory TypeScript/JS baseline. Universal regex rules (Email, Phone, PAN, SSN, API Keys). Docs
Open Reference MCPztds-mcp (packages/ztds-mcp)Apache-2.0Official zero-dependency reference MCP server (io.github.moxno/ztds on Anthropic Registry) for Cursor, Claude Desktop, and Zed. MCP Guide
Certified Pioneer SDK@privacyscrubber/sdkCommercial / Air-GappedHigh-throughput WASM engine with 30 Specialized Industry Profiles (HIPAA, PCI-DSS, Legal FRE-502), multi-threaded pipeline bindings, offline Ed25519 node licensing. Get SDK
Air-Gapped IDE MCP@privacyscrubber/mcp-serverCommercial / StdioStdio MCP proxy (io.github.moxno/privacyscrubber-mcp) for Cursor, Windsurf, Claude Code, and autonomous developer agents with 30 enterprise profiles. MCP Guide

7. Ecosystem Demarcation & Neutrality

  • ZTDS.ai (ztds.ai): Independent, vendor-neutral open standard, certification authority, and technical consortium. Governs RFC v1.0 specifications under Apache 2.0 / CC BY 4.0.
  • PrivacyScrubber (privacyscrubber.com): Commercial reference implementation and pioneer engine provider.

8. Intellectual Property & Statutory Governance

  • Patent Application: U.S. & International Patents Pending (System and Method for Client-Side Zero-Trust Data Sanitization and Cryptographic Multi-Party Pipeline Handoff). Paris Convention & 35 U.S.C. § 119 Priority ().
  • Registered Trademark: ZTDS™ (ILPO Order #182655957, Classes 9 & 42).
  • Academic DOIs:
  • Author & Founder: Ilya Sibiryakov (BrandMeWeb)

9. License

Licensed under the Apache License, Version 2.0. Copyright 2024–2026 Ilya Sibiryakov (ZTDS AI Consortium / BrandMeWeb).

來源:README.md,提交 7fc4c39

工具

0
SourceWeft 尚未在沙箱中啟動過該軟體包,因此其工具未知。

版本歷史

1
  1. v1.0.0最新Sep 27, 2026

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