「cnil」の検索結果

Implementation guide for CNIL cookie guidelines compliance. References the EUR 150M Google fine and EUR 60M Meta fine. Covers equal prominence accept/reject buttons, cookie wall prohibition, 6-month reconsent intervals, essential cookies exemption, and detailed CNIL Deliberation No. 2020-091 requirements.

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Audits Records of Processing Activities against supervisory authority templates from CNIL, ICO, and BfDI. Provides completeness scoring, gap identification, and remediation tracking. Activate for RoPA audit, completeness check, supervisory authority readiness, CNIL template, ICO template, BfDI template, gap analysis.

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Designing and implementing CNIL-compliant cookie consent banners for French and EU audiences. References the EUR 100M Google LLC fine and EUR 150M Meta Platforms fine for non-compliant cookie practices. Covers equal prominence, reject-all buttons, cookie walls prohibition, and 6-month reconsent cycles.

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Compares PIA/DPIA methodologies: CNIL PIA tool, ICO DPIA template, NIST Privacy Framework, and ISO 29134. Provides methodology selection criteria based on regulatory jurisdiction, organisation maturity, processing complexity, and resource availability. Covers regulatory acceptance, tool features, and cross-methodology mapping. Keywords: PIA methodology, CNIL, ICO, NIST Privacy Framework, ISO 29134, DPIA comparison, assessment.

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Auditing cookie lifetimes against regulatory recommendations and browser policies. Covers CNIL 13-month maximum recommendation, session vs persistent classification, third-party cookie phase-out impact, and Safari ITP duration caps.

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Methodology for auditing A/B testing of consent banners to ensure compliance with equal ease of acceptance and rejection. Covers CNIL enforcement patterns including the EUR 150M Google fine, dark pattern detection methodology, manipulative design identification, and regulatory-compliant experimentation boundaries.

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Apply GDPR-compliant engineering practices across your codebase. Use this skill whenever you are designing APIs, writing data models, building authentication flows, implementing logging, handling user data, writing retention/deletion jobs, designing cloud infrastructure, or reviewing pull requests for privacy compliance. Trigger this skill for any task involving personal data, user accounts, cookies, analytics, emails, audit logs, encryption, pseudonymization, anonymization, data exports, breach response, CI/CD pipelines that process real data, or any question framed as "is this GDPR-compliant?". Inspired by CNIL developer guidance and GDPR Articles 5, 25, 32, 33, 35.

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Guide for (a) auditing an existing whistleblower system or (b) drafting a compliant reporting policy from a provided template. Covers EU Directive 2019/1937, the amended Sapin II law (Waserman 2022), Decree 2022-1284, CNIL guidelines, public sector requirements, and duty of vigilance.

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GDPR Transfer Impact Assessment for Chapter V transfers under the EDPB Recommendations 01/2020 six-step methodology, the CNIL TIA Guide (January 2025), and EDPB essential guarantees. Handles transfer qualification, Art. 45 adequacy fast-tracks, Art. 46 full assessments with country profiles for 12 jurisdictions, and balanced Art. 49 derogation analysis. Outputs a Markdown report, a .docx formal TIA, and a JSON delta for RoPA interchange.

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Guide for drafting privacy policies compliant with GDPR. Includes CNIL 2020 recommendations, a reference template, and best practices. Use when drafting or revising a privacy policy for a website or application.

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Search and cite French case law and statutes with the LibreJustice MCP tools. Use whenever the user asks about French or European court decisions (Cour de cassation, Conseil d'État, cours d'appel, TJ/TA, CNDA, Conseil constitutionnel, CNIL, CEDH, CJUE), needs authorities for a brief, requête, référé or consultation, wants to check how courts rule on an issue, needs counts of decisions on a point, or asks what a code article says at a given date, even if they never mention LibreJustice.

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GDPR Legitimate Interest Assessment (LIA) — Guided assessment for Art. 6(1)(f) GDPR using the EDPB three-step test. Based on EDPB Guidelines 1/2024, EDPB Opinion 28/2024 (AI models), the OSS Case Digest on Legitimate Interest (McIntyre 2026), CNIL AI guidance (June 2025), ICO guidance, and key CJEU case law. Use when: (1) user needs to assess whether legitimate interest is appropriate, (2) user asks about Art. 6(1)(f), "Interessenabwägung", "berechtigtes Interesse", "balancing test", or "LIA", (3) user wants to document a legitimate interest assessment, (4) user mentions the three-step test, (5) user evaluates necessity or proportionality under Art. 6(1)(f), (6) user discusses direct marketing, fraud prevention, IT security, employee monitoring, AI training, web scraping, or credit checks in context of legal basis, (7) user handles a right to object (Art. 21), (8) user asks about children's data, profiling, or cross-border data sharing under legitimate interest, (9) user compares legitimate interest against other legal bases. Do NOT use for: consent assessments (Art. 6(1)(a)), contract performance (Art. 6(1)(b)), DPIA workflows, or pure ePrivacy/cookie compliance questions — though the skill does address the ePrivacy/GDPR overlap where relevant.

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Guide for drafting cookie policies compliant with GDPR and the ePrivacy Directive. Includes CNIL 2020 recommendations, a reference template, and best practices. Use when drafting or revising a cookie policy for a website or application.

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Conducts Data Protection Impact Assessments for biometric identification and authentication systems under GDPR Article 35 and Article 9 special category rules. Covers facial recognition, fingerprint, iris scanning, voice recognition, and behavioural biometrics. Applies EDPB Guidelines 3/2019, CNIL Reglement Type Biometrie, and ISO/IEC 24745 biometric template protection. Keywords: DPIA biometric, facial recognition, fingerprint, Art. 35, Art. 9, biometric template, special category.

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。

Apply GDPR-compliant engineering practices across your codebase. Use this skill whenever you are designing APIs, writing data models, building authentication flows, implementing logging, handling user data, writing retention/deletion jobs, designing cloud infrastructure, or reviewing pull requests for privacy compliance. Trigger this skill for any task involving personal data, user accounts, cookies, analytics, emails, audit logs, encryption, pseudonymization, anonymization, data exports, breach response, CI/CD pipelines that process real data, or any question framed as "is this GDPR-compliant?". Inspired by CNIL developer guidance and GDPR Articles 5, 25, 32, 33, 35.

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。