スキル personal-information-protection-expert

📦

personal-information-protection-expert

Name: personal-information-protection-expert
Author: 图灵数盟

コンテンツリビジョン r1 安全 📁 ファイルシステムへのアクセス⚙️ 外部コマンド🌐 ネットワークアクセス

Audit Personal Information Protection Compliance

Organizations need structured reviews of personal information processing under Chinese privacy requirements. This skill creates practical inventories, assessments, controls, and remediation plans.

対応: Claude Codex Code(CC)

🥉 77 ブロンズ

Maintain this Skill? Claim it 🥉 77 ブロンズ

自分のエージェントでインストール

このリクエストをエージェントにコピーしてください。正規の Skill ページとマニフェストが含まれています。

エージェントリクエスト

Review the Skillstore skill "personal-information-protection-expert" from https://skillstore.io/skills/dhturing-personal-information-protection-expert.md and its manifest at https://skillstore.io/api/skills/dhturing-personal-information-protection-expert/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.

エージェントは引き続き計画を提示し、セキュリティポリシーで必要な確認を求める必要があります。

エージェントが読めるリソース

AI エージェント、クローラー、スクリプトがページ全体ではなく整理されたコンテキストを必要とする場合は、これらのリンクを使ってください。

Markdown詳細 GET /skills/dhturing-personal-information-protection-expert.md 署名済み manifest GET /api/skills/dhturing-personal-information-protection-expert/manifest 署名済み lockfile GET /api/skills/dhturing-personal-information-protection-expert/lockfile

テストする

「personal-information-protection-expert」を使用しています。 Review a mobile application that collects phone numbers, precise location, and facial images.

期待される結果:

Data classification: phone number is personal information; precise location and facial images are sensitive personal information.
Priority checks: necessity, separate consent, impact assessment, retention, access controls, and withdrawal methods.
Next step: collect the privacy notice, interface screenshots, processing records, and consent logs before reaching a conclusion.

「personal-information-protection-expert」を使用しています。 Create an audit plan for a retailer processing information about 1.2 million customers.

期待される結果:

Scope: customer applications, membership systems, marketing platforms, service providers, and cross-border transfers.
Evidence: processing inventory, notices, consent logs, contracts, impact assessments, rights requests, incidents, and security records.
Deliverables: control checklist, evidence register, finding ratings, corrective actions, owners, and due dates.

「personal-information-protection-expert」を使用しています。 Recommend a protection approach for sharing customer analytics with a research partner.

期待される結果:

First determine whether the partner needs record-level data or only aggregate statistics.
Compare suppression, generalization, pseudonymization, and formal anonymization against utility and re-identification risk.
Require validation, contractual controls, access restrictions, retention limits, and documented residual-risk acceptance.

セキュリティ監査

安全

v1 • 2026/9/27 バージョン別レポートを開く

All 12 static findings are false positives caused by Markdown syntax, documented installation paths, public website links, or entropy heuristics on Chinese text. The reviewed files contain no executable behavior, network requests, obfuscated payloads, or prompt injection attempts.

スキャンされたファイル

471

解析済み行数

レビュー項目

誤検知を無視

リスク要因

📁 ファイルシステムへのアクセス (2)

profile.md:38 profile.md:38

⚙️ 外部コマンド (3)

SKILL.md:20 SKILL.md:26 SKILL.md:33

🌐 ネットワークアクセス (2)

SKILL.md:6 SKILL.md:12

最新の完了済み静的・セマンティック監査では、確認済みのセキュリティ検出事項は見つかりませんでした。これは、スキルに副作用がないことを証明するものではありません。

監査者: codex

このレポートを共有・引用

バージョン付き評価レポート、中立的なバッジ、埋め込みカード、引用を共有できます。Skillstore は証拠を報告しますが、この Skill が安全かどうかは判断しません。

バージョン別レポートを開く

レポートリンクをコピー

https://skillstore.io/skills/dhturing-personal-information-protection-expert/audits/1?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report

Markdownバッジ

[![Skillstore security assessment](https://skillstore.io/badges/skills/dhturing-personal-information-protection-expert/security.svg)](https://skillstore.io/skills/dhturing-personal-information-protection-expert?utm_source=security_passport_badge)

HTMLバッジ

<a href="https://skillstore.io/skills/dhturing-personal-information-protection-expert?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/dhturing-personal-information-protection-expert/security.svg" alt="Skillstore security assessment" loading="lazy"></a>

埋め込みカード

<iframe src="https://skillstore.io/embed/skills/dhturing-personal-information-protection-expert.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>

学術引用 (APA · BibTeX · CFF)

APA形式の引用

图灵数盟. (2026). personal-information-protection-expert security audit report (audit version 1) [Author version unspecified]. Skillstore. https://skillstore.io/skills/dhturing-personal-information-protection-expert/audits/1

BibTeX形式の引用

@techreport{dhturing-personal-information-protection-expert-2026,
  author = {图灵数盟},
  title = {personal-information-protection-expert security audit report (audit version 1)},
  institution = {Skillstore},
  year = {2026},
  number = {1},
  url = {https://skillstore.io/skills/dhturing-personal-information-protection-expert/audits/1},
  note = {Author version unspecified}
}

CITATION.cff

cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "personal-information-protection-expert security audit report (audit version 1)"
version: "unspecified"
type: report
authors:
  - name: "图灵数盟"
date-released: "2026-09-27"
url: "https://skillstore.io/skills/dhturing-personal-information-protection-expert/audits/1"
identifiers:
  - type: other
    value: "skillstore:dhturing-personal-information-protection-expert:audit:1"
    description: "Skillstore immutable audit report identifier"

Skillstore スコア

このスコアの理由証拠の信頼度: 中

アーキテクチャ

保守性

コンテンツ

コミュニティ

仕様準拠

作成できるもの

Review a Product Launch

Assess planned data collection, lawful bases, notices, consent flows, sensitive information, and required impact assessments before launch.

Prepare a Compliance Audit

Build an evidence request, control checklist, findings register, and remediation plan for a personal information compliance audit.

Design Data Protection Controls

Compare de-identification and anonymization options, document residual risks, and define validation steps for an analytics dataset.

これらのプロンプトを試す

Classify Personal Information

Classify these data fields as general personal information, sensitive personal information, or non-personal data. Explain each classification and list missing context: [fields].

Review Notice and Consent

Review this privacy notice and consent flow: [materials]. Identify missing notices, invalid consent patterns, separate-consent triggers, withdrawal gaps, and prioritized corrections.

Build an Impact Assessment

Create a personal information protection impact assessment for [processing activity]. Cover necessity, proportionality, rights impacts, security controls, residual risk, and approval evidence.

Plan a Full Compliance Audit

Design an evidence-based audit for [organization and scope]. Map processing activities, test controls, rank findings, assign owners, and create a phased remediation roadmap.

ベストプラクティス

Provide processing purposes, data fields, systems, recipients, retention periods, and evidence with each request.
Verify legal thresholds and effective dates against current official sources before acting.
Separate confirmed facts, assumptions, legal interpretation, technical testing, and recommended actions.

回避

Do not submit real personal information when representative field names or synthetic samples are sufficient.
Do not treat a revised privacy notice as proof that operational processing is compliant.
Do not claim anonymization without testing re-identification risk and documenting the assessment.

よくある質問

Does this skill provide legal advice?

No. It structures compliance analysis and deliverables, but qualified counsel should confirm legal conclusions for the specific facts.

Can it review a privacy policy?

Yes. Provide the policy, relevant interfaces, processing purposes, data categories, recipients, retention terms, and consent flow.

Can it determine whether separate consent is required?

It can identify likely triggers from the provided facts. Current law, sector rules, and implementation details still require verification.

Can it perform a personal information protection impact assessment?

It can structure the assessment, risks, controls, evidence, approvals, and remediation. The organization must validate facts and control effectiveness.

Can it confirm that data is anonymous?

No. It can propose methods and tests, but confirmation requires representative data, technical evaluation, and documented re-identification analysis.

What information should I provide for an audit?

Provide scope, processing inventories, policies, notices, consent records, contracts, impact assessments, rights requests, incidents, and security evidence.