LGD Crypto Guard（隐私计算守门）

Check whether an AI system handling sensitive data meets the three-law standard of registered, evidenced and gated before it is deployed. lgd-crypto-guard — 把 LGD 三律（有籍·有证·有门禁）翻译进隐私计算 / 数据加密与最小化 AI 应用（联邦·密文·脱敏）的合规守门器，对 AI 系统做三律自评与门禁判定（零依赖）。

zhaoxinghua09-cell@zhaoxinghua09-cell

Install

openclaw skills install @zhaoxinghua09-cell/lgd-crypto-guard

凡自治之物 · LGD 治理学 · 创造术家族｜评测协议：见平台质量门禁规范

English

When to use

Call it before an AI model deployment, to verify that data flows meet the LGD "registered · evidenced · gated" standard.
Enable it when a system handles sensitive data in privacy-computing, federated-learning or ciphertext-transmission scenarios and must satisfy the data-minimization principle.
Use it when an AI interface shows log-leakage risk or flawed permission tiers, triggering automatic desensitization and gate blocking.

Usage

In a Python runtime, import the core classes and functions from the crypto_guard.py module. Configure the inputs as the data source under check, the model path and the compliance policy level (e.g. HIGH). Recommended invocation:

python

from crypto_guard import GuardianEngine, LGD_POLICY
guard = GuardianEngine(policy=LGD_POLICY.STRICT)
result = guard.check_model(ai_model_path="local/model.pkl")

Workflow

Environment prep: load the crypto_guard module; confirm no dependency conflicts.
Data assembly: organize the AI model file, training dataset and access-request context into a standardized input object.
Compliance scan: run the evaluation engine for an LGD three-law self-check on data lineage and encryption strategy.
Report generation: emit a structured report with the "registered / evidenced / gated" status verdicts.
Execution control: if the check fails, automatically issue encryption, desensitization or access-denial instructions; on pass, open the service.

Evidence & safety statement

Evidence: TBD (no evaluation / badge link yet; update here once it is produced)
Version: 1.0.1
Security: no independent security scan has been performed (TBD); the conclusion is pending and no endorsement is given until it is completed.

中文

何时用

在 AI 模型部署前需验证数据流转是否符合 LGD“有籍·有证·有门禁”标准时调用。当系统处理敏感数据，涉及隐私计算、联邦学习或密文传输场景且需满足最小化原则时启用。若检测到 AI 接口存在日志泄露风险或权限分级错误，需触发自动脱敏与门禁拦截机制时使用。

用法

在 Python 执行环境中，直接导入 crypto_guard.py 模块中的核心类与函数。需配置输入参数为待检数据源、模型路径及合规策略等级（如 HIGH）。实际调用推荐通过以下结构初始化并发送请求：

python

from crypto_guard import GuardianEngine, LGD_POLICY
guard = GuardianEngine(policy=LGD_POLICY.STRICT)
result = guard.check_model(ai_model_path="local/model.pkl")

流程

环境准备：加载 crypto_guard 模块，确认无依赖冲突。
数据构建：组织 AI 模型文件、训练数据集及访问请求上下文为标准化输入对象。
合规扫描：调用评估引擎对数据血缘与加密策略进行 LGD 三律自检。
报告生成：输出包含“有籍/有证/门禁”状态判定结果的结构化报告。
执行控制：若校验未通过，自动触发数据加密、脱敏或访问拒绝指令；通过后开放服务。

证据与安全声明

证据：TBD（暂无评测/徽章链接；产生后在此更新实际链接）
版本：1.0.1
安全：未做独立安全扫描（TBD），结论待补；补全前不作推荐背书。

Triggers / 触发词

这些是用户真实会说的话（中 / 英对照），命中任一即应加载本技能：

「训练数据要出境，先过隐私检查」 / "check privacy before training data leaves"
「联邦学习方案能不能上线」 / "can this federated learning setup go live"
「日志里会不会漏出用户信息」 / "will our logs leak user data"
「密文传输还需要做合规自评吗」 / "do we still need review for encrypted transfer"
「做数据最小化，怎么判断够不够」 / "is our data minimization enough"
「模型部署前帮我跑一遍门禁」 / "run the gate check before model deployment"

Trigger when the user says any of the above, in Chinese or English.

Ecosystem / 生态入口

This skill is one door of the LGD ecosystem — every entry below is publicly reachable. 本技能是 LGD 生态 的一个入口，下列地址均对公网可达。

Ecosystem hub / 生态总入口: https://zhaoxinghua09-cell.github.io/lgd-hub/
LGD theory (canonical) / 理论正本: https://github.com/zhaoxinghua09-cell/LGD
Formal paper (DOI) / 形式化论文: https://doi.org/10.5281/zenodo.22456647
Protocol & reference implementation / 协议与参考实现: https://github.com/zhaoxinghua09-cell/uibc-core
Source of this skill / 本包源码: https://github.com/zhaoxinghua09-cell/agent-skills/tree/main/skills/lgd-crypto-guard
All published skills / 全部已发布技能: https://github.com/zhaoxinghua09-cell/agent-skills
AI-readable index / AI 说明书: https://github.com/zhaoxinghua09-cell/agent-skills/tree/main/skills/lgd-crypto-guard/llms.txt

Looking for something else? / 还想要别的？

Tell your AI assistant: "Find me an LGD skill that can " — the hub lists every published skill with a one-line purpose. 跟你的 AI 助手说一句「去 LGD 生态超市找能……的技能」，总入口按用途列全了所有已发布技能。

Data handling / 数据处理边界

默认不向任何外部地址发送数据：扫描结果、报告、命中明细一律只写本地或只打印到当前会话。
如需外发（告警、工单、邮件、IM），必须由人先明确指定接收方，并在每次发送前逐次确认；本技能不预设、也不硬编码任何接收端。
只处理调用者明确指定的目标路径，不遍历无关目录，不跟随符号链接，不读取目标之外的凭据文件。
命中内容在输出时按需脱敏，避免把敏感原值写进日志或对话记录。