2,365 件 ・ 関連度順
概要と使いどころ
Implements NIST SP 800-88 Rev. 1 media sanitization procedures including Clear, Purge, and Destroy methods for all media types. Covers certificate of destruction generation, verification procedures, vendor management for third-party destruction, and chain of custody documentation. Activate for data destruction, media sanitization, secure erasure, certificate of destruction queries.
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Guides privacy program effectiveness measurement including leading and lagging indicators, KPI definition, benchmarking methodology, executive reporting formats, board-level privacy dashboards, and metric-driven program improvement. Covers operational, compliance, risk, and strategic privacy metrics across the program lifecycle. Keywords: privacy metrics, KPIs, benchmarking, executive reporting, dashboard, program effectiveness.
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Guide for managing consent for children's personal data under GDPR Article 8 and COPPA. Covers parental consent mechanisms, age verification methods, country-specific age thresholds (ranging from 13 to 16), parental authorization workflows, and age-appropriate design per the UK ICO Children's Code.
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Guides privacy impact assessment for emerging technologies including IoT, blockchain, AR/VR, quantum computing, and digital twins. Covers risk identification methodology, proportionality assessment, and technology-specific privacy challenges. Activate when evaluating new technology adoption, innovation projects, or emerging tech procurement. Keywords: PIA, emerging technology, IoT, blockchain, AR/VR, quantum computing, digital twins, innovation privacy.
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Conducts HIPAA risk analysis per 45 CFR §164.308(a)(1) following OCR guidance methodology. Covers threat identification, vulnerability assessment, likelihood and impact determination, risk scoring, and mitigation planning for electronic protected health information. Keywords: HIPAA risk analysis, OCR guidance, threat assessment, vulnerability, risk management, ePHI.
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Provides a structured risk scoring methodology for Data Protection Impact Assessments aligned with ENISA threat taxonomy and ISO 29134. Covers likelihood and severity assessment, risk matrix construction, inherent vs residual risk calculation, and risk appetite thresholds per EDPB WP248rev.01 guidance. Keywords: risk scoring, DPIA risk matrix, likelihood, severity, ENISA, ISO 29134, residual risk, risk appetite.
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Guides data subject and stakeholder consultation requirements during Data Protection Impact Assessments under GDPR Article 35(9). Covers consultation planning, data subject engagement methods, DPO involvement per Art. 35(2), and documentation of views received. Keywords: DPIA consultation, stakeholder engagement, Art. 35(9), data subject views, DPO advice, public consultation, representative groups.
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Guides comprehensive controller self-assessment covering GDPR Articles 5-49 with scoring methodology and reporting format. Activate when conducting internal reviews or benchmarking maturity. Keywords: self-assessment, controller assessment, compliance questionnaire, scoring.
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Comprehensive methodology for auditing website cookies and tracking technologies. Covers automated scanning, cookie categorization, lifecycle documentation, and compliance gap analysis referencing the Planet49 CJEU ruling (C-673/17).
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Complete guide to LINDDUN privacy threat modeling methodology covering seven threat categories: Linking, Identifying, Non-repudiation, Detecting, Data Disclosure, Unawareness, and Non-compliance. Includes DFD-based analysis, threat tree catalogs, mitigation mapping to privacy design patterns, and step-by-step process.
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Implements Children's Online Privacy Protection Act (COPPA) compliance under 16 CFR Part 312. Covers verifiable parental consent methods including signed forms, credit card verification, government ID, knowledge-based authentication, and video call. Includes FTC safe harbor programs and enforcement actions. Keywords: COPPA, FTC, children, parental consent, safe harbor, verifiable consent.
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Framework for evaluating and selecting Consent Management Platforms (CMPs). Covers TCF v2.2 certification requirements, Global Privacy Control support, multi-regulation compliance (GDPR, CCPA, LGPD), A/B testing capabilities, API integration options, reporting features, and a structured vendor comparison methodology.
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Determines whether a personal data breach triggers notification obligations under GDPR Articles 33 and 34 using structured risk assessment methodology. Covers breach type classification (CIA triad), data sensitivity scoring, volume assessment, identifiability analysis, and consequence severity evaluation. References EDPB Guidelines 01/2021 with 18 breach scenarios. Keywords: breach risk assessment, GDPR, Article 33, Article 34, EDPB, notification threshold.
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Guides systematic mapping of international personal data flows across an organisation. Covers system-by-system inventory methodology, third-party identification, transfer mechanism assignment, gap analysis, and data flow visualisation. Keywords: data flow mapping, international transfers, data inventory, transfer register, cross-border data flows.
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Guides the end-to-end GDPR Data Protection Impact Assessment process under Article 35, including mandatory trigger identification per Art. 35(3), DPIA content requirements per Art. 35(7), and EDPB WP248rev.01 methodology. Activate for systematic profiling, large-scale special category processing, or large-scale public monitoring. Keywords: DPIA, Article 35, impact assessment, WP248, data protection, risk assessment.
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Assesses AI bias risks for GDPR Art. 9 special category data and AI Act Art. 10 data governance. Covers fairness metrics, bias detection methods, mitigation strategies, and documentation requirements for protected characteristics. Keywords: AI bias, special category, fairness metrics, discrimination, Art. 9, Art. 10.
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Systematic application of the eight privacy design patterns per Hoepman: minimize, hide, separate, abstract, inform, control, enforce, and demonstrate. Covers pattern selection methodology per processing activity, mapping to GDPR principles, and practical implementation guidance for privacy-by-design system architecture.
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Conducts Data Protection Impact Assessments for AI and ML systems per EDPB Guidelines 04/2025 on AI processing. Covers training data lawfulness evaluation, model risk assessment, automated decision triggers, and AI-specific DPIA methodology. Keywords: AI DPIA, machine learning impact assessment, EDPB AI guidelines, model risk, training data.
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Evaluates and implements age estimation and verification technologies for online services. Covers facial age estimation, digital ID verification, self-declaration with risk assessment, AI-based age estimation, and the accuracy versus privacy tradeoff. Includes ICO guidance and euCONSENT framework. Keywords: age verification, age estimation, facial analysis, digital ID, children, online safety.
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Authorized security assessment of REST, GraphQL, WebSocket, and SOAP APIs: discovery, authentication and authorization flaws (BOLA/IDOR, JWT/OAuth), rate-limit testing, and a structured multi-phase methodology.
日本語の概要は準備中です。原文の説明を表示しています。
Validates whether an API request is correct based on provided inputs (method, URL, headers, body, auth, query params).
日本語の概要は準備中です。原文の説明を表示しています。
Designs and develops specs following the spec-driven method. Asks clarifying questions before proposing structure, and builds the spec section by section. Use it when starting a large feature, before writing code.
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Use when an application issues and validates its own first-party JWT access and refresh tokens, including authentication filters, password encoding, RBAC, and method security. For JWTs issued by Keycloak, Auth0, Okta, Cognito, or another authorization server, use oauth2-resource-server.
日本語の概要は準備中です。原文の説明を表示しています。
Create professional, consultant-grade PowerPoint presentations from scratch using MckEngine (python-pptx wrapper) with McKinsey-style design. Use when user asks to create slides, pitch decks, business presentations, strategy decks, quarterly reviews, board meeting slides, or any professional PPTX. AI calls eng.cover(), eng.donut(), eng.timeline() etc — 67 high-level methods across 12 categories (structure, data, framework, comparison, narrative, timeline, team, charts, images, advanced viz, dashboards, visual storytelling), consistent typography, zero file-corruption issues, BLOCK_ARC native shapes for circular charts (donut, pie, gauge), production-hardened guard rails for spacing, overflow, legend consistency, title style uniformity, dynamic sizing for variable-count layouts, horizontal item overflow protection, chart rendering, and AI-generated cover images via Tencent Hunyuan 2.0 with professional cutout, cool grey-blue tint, and McKinsey-style Bézier ribbon decoration.
日本語の概要は準備中です。原文の説明を表示しています。