KVKK and GDPR compliance patterns - consent management, right to erasure, breach notification, audit logging, cookie consent, and data classification.
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概要と使いどころ
KVKK and GDPR compliance patterns - consent management, right to erasure, breach notification, audit logging, cookie consent, and data classification.
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。
Collaborative purple-team operations — threat-informed adversary emulation planning (ATT&CK, CTID, Atomic Red Team, CALDERA), the detect-tune-validate loop, detection coverage measurement (DeTT&CT/Navigator), safe execution and deconfliction, and MTTD/coverage reporting
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Use when reviewing, designing, or modifying Java enterprise systems that process personal data and need GDPR-aware engineering controls. This should trigger for requests such as Review a Java service for GDPR privacy controls; Design data-subject rights workflows; Add retention, deletion, pseudonymization, or privacy-safe logging; Assess data transfer, DPIA, breach evidence, or processor/controller boundary concerns before production release. Part of Plinth Toolkit
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。
Guide rapid triage and initial response to security incidents following NIST SP 800-61 methodology. Use when the user mentions 'incident response,' 'security incident,' 'triage,' 'we've been hacked,' 'breach,' 'compromised,' 'malware detected,' 'suspicious activity,' 'IOC,' 'indicators of compromise,' or needs help handling a security event.
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Use when mapping a target's external attack surface or gathering OSINT — subdomain enumeration, attack-surface mapping (httpx/katana/JS secrets), subdomain takeover, multi-cloud/Azure tenant recon, GitHub secret dorking, breach/infostealer credential intel, CVE prioritization (EPSS/KEV)
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Vendor privacy risk tiering methodology for processor management. Covers scoring factors including data volume, sensitivity, transfer locations, certifications, breach history, and control maturity with weighted risk calculation and tier assignment.
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Guides the periodic DPIA review lifecycle including trigger identification for regulatory changes, new data categories, technology changes, and breach incidents. Covers version control, stakeholder sign-off procedures, and DPIA register management per Art. 35(11). Keywords: DPIA review, PIA update, review cadence, version control, Art. 35(11), periodic review, trigger events, stakeholder sign-off.
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Addresses HIPAA compliance for mobile health (mHealth) applications, wearable devices, and remote patient monitoring. Covers OCR guidance on mobile device PHI, FDA-regulated mobile medical applications, FTC Health Breach Notification Rule for non-HIPAA apps, BYOD policies, and encryption requirements for ePHI on mobile platforms. Keywords: mHealth, mobile health, HIPAA mobile, wearable, remote monitoring, BYOD, mobile device management, app privacy.
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。
Nigeria Data Protection Regulation (NDPR) and Nigeria Data Protection Act (NDPA) 2023 compliance. Covers lawful basis for processing, data subject rights, cross-border transfer mechanisms, Data Protection Compliance Organisation (DPCO) registration, mandatory DPIA filing, and breach notification. Keywords: NDPR, NDPA, Nigeria, NITDA, DPCO, Africa data protection, cross-border transfer.
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Manages HIPAA Business Associate Agreements under 45 CFR §164.502(e) and §164.504(e). Covers required BAA provisions, business associate vs subcontractor obligations, breach notification chain, downstream BA requirements, and termination remedies. Keywords: BAA, business associate, subcontractor, HIPAA compliance, PHI disclosure, termination.
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。
Guides implementation of the GDPR accountability principle under Articles 5(2) and 24, including documentation requirements for policies, DPIAs, RoPA, training records, and breach logs. Activate when establishing or reviewing accountability measures, preparing evidence portfolios, or demonstrating compliance to supervisory authorities. Keywords: accountability, Article 5(2), Article 24, documentation, compliance evidence, governance.
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。
Implements data lineage tracking for privacy compliance including origin tracking, transformation logging, access auditing, deletion verification, and cross-system lineage graphs. Covers source-to-sink mapping, GDPR Art. 30 RoPA integration, automated lineage discovery, and breach impact scoping. Keywords: data lineage, data provenance, data flow mapping, transformation logging, deletion verification.
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。
Guides managing conflicting privacy requirements across jurisdictions. Covers data localisation vs transfer freedom, consent standards variation, age thresholds, breach timelines, and resolution frameworks for incompatible obligations. Keywords: conflicting laws, data localisation, consent variation, age thresholds, resolution framework.
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 original short videos using the 地下轨迹破土|尺度反转、追逐穿越与空场余波 Creative DNA for MiniMax H3 or Seedance 2.0. Use when the user wants this causal, camera, motion, rhythm, or payoff structure with new subjects and surfaces.
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 original short videos using the 纸页角色越界|原画基线、实体脱离与双媒介互证 Creative DNA for MiniMax H3 or Seedance 2.0. Use when the user wants this causal, camera, motion, rhythm, or payoff structure with new subjects and surfaces.
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 original short videos using the 踏面异变|重复触点到基底破裂 Creative DNA for MiniMax H3 or Seedance 2.0. Use when the user wants this causal, camera, motion, rhythm, or payoff structure with new subjects and surfaces.
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 original short videos using the 非对称突破|密集阻力到空间制度改变 Creative DNA for MiniMax H3 or Seedance 2.0. Use when the user wants this causal, camera, motion, rhythm, or payoff structure with new subjects and surfaces.
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 original short videos using the 延迟转身惊变|固定走廊、轮廓污染与贴镜突破 Creative DNA for MiniMax H3 or Seedance 2.0. Use when the user wants this causal, camera, motion, rhythm, or payoff structure with new subjects and surfaces.
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。
Think and work like an expert Horticulturist. Use when a task calls for Horticulturist judgment. Reasons from plant-environment-cultural coupling, source-sink carbon partitioning, and chilling/photoperiod thresholds through rootstock-scion matching, DLI/VPD and substrate EC/pH targets, Dynamic/Utah chill models, and CA/MA postharvest setpoints while treating blossom-end rot, bitter pit, tipburn, storage scald, and MRL/PHI breaches as first-class failure modes.
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。
Think and work like an expert Fire Protection Engineer. Use when a task calls for Fire Protection Engineer judgment. Reasons from NFPA 13 Hazen-Williams hydraulics (K-factor, remote area, hose stream) and NFPA 101 egress (occupant load, travel distance, capacity factors) through NFPA 92 smoke containment/management, ASET/RSET PBD, and FDS/CFAST/CONTAM/PyroSim modeling while treating breached compartmentation, C-factor/fitting errors, and supply-curve shortfall as first-class failure modes.
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。
Think and work like an expert Clinical Data Manager. Use when a task calls for Clinical Data Manager judgment. Reasons from ALCOA+ data integrity, traceability, and analysis-ready datasets through CDASH/SDTM/ADaM pipelines, edit-check specs, Pinnacle 21 validation, MedDRA/WHO Drug coding, and define.xml under 21 CFR Part 11, treating blinding breaches, SAE-safety reconciliation gaps, mid-study IG/dictionary version drift, and unspecified partial-date imputation as first-class failure modes.
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Warren Buffett said he looks for "economic castles protected by unbreachable moats." A moat is a sustainable competitive advantage that protects your business from competitors. Without a moat, success attracts competition that erodes your margins to zero. This skill covers identifying, building, and deepening moats. Network effects, switching costs, brand, scale economies, and the rarer moats like regulatory capture and counter-positioning. Use when "moat, defensibility, competitive advantage, network effects, switching costs, barrier to entry, unfair advantage, protect from competition, sustainable advantage, winner take all, flywheel, lock-in, moat, defensibility, strategy, network-effects, switching-costs, competitive-advantage, seven-powers" mentioned.
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。
Use when implementing GDPR compliance, handling data subject requests, conducting DPIAs, managing consent, or responding to data breaches - covers all key GDPR requirementsUse when ", " mentioned.
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。
Troubleshoots Monte Carlo AI agent alerts and traces — eval score drops, latency/token spikes, trajectory and validation breaches. Not for data incidents (monte-carlo-analyze-root-cause) or monitor creation (monte-carlo-monitoring-advisor).
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。