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Merge pull request #207 from LLM-Coding/copilot/prepare-linddun-semantic-anchor
feat: Add LINDDUN as semantic anchor
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docs/anchors/linddun.adoc

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= LINDDUN
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:categories: testing-quality
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:roles: software-architect, software-developer, qa-engineer, business-analyst, consultant, devops-engineer
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:related: owasp-top-10, regulated-environment
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:proponents: Kim Wuyts, Riccardo Scandariato, Wouter Joosen
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:tags: privacy, threat-modeling, privacy-engineering, GDPR, data-protection, threat-analysis, privacy-by-design
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:tier: 3
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[%collapsible]
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====
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Full Name:: LINDDUN Privacy Threat Modeling Framework
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Also known as:: LINDDUN GO, Privacy Threat Modeling, Privacy STRIDE
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[discrete]
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== *Core Concepts*:
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Linkability:: Attacker can link two items of interest (e.g., data items, messages, or actions) without knowing the identity of the data subject
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Identifiability:: Attacker can identify a data subject from a set of data subjects through items of interest
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Non-repudiation:: Data subject cannot deny having performed an action or having sent a message; system logs become a liability
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Detectability:: Attacker can deduce the existence or absence of a data item or communication, even without access to its content
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Disclosure of Information:: Unauthorized exposure of data to a party without the data subject's consent; classical confidentiality breach from a privacy perspective
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Unawareness:: Data subjects are not sufficiently informed about the collection, processing, storage, and sharing of their personal data; violates transparency principles
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Non-compliance:: System does not comply with privacy legislation, regulations, or organizational privacy policies (e.g., GDPR, CCPA, HIPAA)
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Key Proponents:: Kim Wuyts, Riccardo Scandariato, Wouter Joosen (KU Leuven / DistriNet Research Group, published 2014)
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[discrete]
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== *When to Use*:
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* Conducting privacy threat modeling during the design or architecture phase
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* Performing privacy impact assessments (PIA) or data protection impact assessments (DPIA)
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* Identifying privacy risks in systems that handle personal data
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* Evaluating compliance with GDPR, CCPA, HIPAA, and other privacy regulations
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* Integrating Privacy by Design into the software development lifecycle
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* Training development teams on privacy engineering concepts
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[discrete]
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== *Related Anchors*:
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* <<owasp-top-10,OWASP Top 10>>
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* <<regulated-environment,Regulated Environment>>
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====

docs/anchors/linddun.de.adoc

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= LINDDUN
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:categories: testing-quality
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:roles: software-architect, software-developer, qa-engineer, business-analyst, consultant, devops-engineer
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:related: owasp-top-10, regulated-environment
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:proponents: Kim Wuyts, Riccardo Scandariato, Wouter Joosen
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:tags: privacy, threat-modeling, privacy-engineering, GDPR, data-protection, threat-analysis, privacy-by-design
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:tier: 3
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[%collapsible]
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====
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Vollständiger Name:: LINDDUN Privacy Threat Modeling Framework
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Auch bekannt als:: LINDDUN GO, Privacy Threat Modeling, Privacy STRIDE
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[discrete]
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== *Kernkonzepte*:
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Linkability (Verknüpfbarkeit):: Angreifer kann zwei interessante Datenpunkte (z. B. Datensätze, Nachrichten oder Aktionen) miteinander verknüpfen, ohne die Identität der betroffenen Person zu kennen
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Identifiability (Identifizierbarkeit):: Angreifer kann eine betroffene Person aus einer Menge von Personen anhand vorhandener Daten identifizieren
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Non-repudiation (Nichtabstreitbarkeit):: Betroffene Person kann eine durchgeführte Aktion oder gesendete Nachricht nicht abstreiten; Systemlogs werden zur Datenschutzlast
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Detectability (Erkennbarkeit):: Angreifer kann das Vorhandensein oder Fehlen eines Datensatzes oder einer Kommunikation ableiten, auch ohne Zugriff auf den Inhalt
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Disclosure of Information (Informationsoffenbarung):: Unbefugte Weitergabe von Daten an Dritte ohne Einwilligung der betroffenen Person; klassische Vertraulichkeitsverletzung aus Datenschutzsicht
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Unawareness (Mangelndes Bewusstsein):: Betroffene Person wird nicht ausreichend über Erhebung, Verarbeitung, Speicherung und Weitergabe ihrer personenbezogenen Daten informiert; verletzt den Transparenzgrundsatz
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Non-compliance (Nichteinhaltung):: System entspricht nicht den Datenschutzgesetzen, Vorschriften oder organisationsinternen Datenschutzrichtlinien (z. B. DSGVO, CCPA, HIPAA)
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Schlüsselvertreter:: Kim Wuyts, Riccardo Scandariato, Wouter Joosen (KU Leuven / DistriNet Research Group, veröffentlicht 2014)
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[discrete]
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== *Wann zu verwenden*:
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* Durchführung von Privacy Threat Modeling in der Design- oder Architekturphase
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* Erstellung von Datenschutz-Folgenabschätzungen (DSFA/DPIA) und Datenschutz-Impact-Analysen
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* Identifikation von Datenschutzrisiken in Systemen, die personenbezogene Daten verarbeiten
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* Bewertung der Compliance mit DSGVO, CCPA, HIPAA und anderen Datenschutzvorschriften
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* Integration von Privacy by Design in den Software-Entwicklungslebenszyklus
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* Schulung von Entwicklungsteams zu Privacy Engineering
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[discrete]
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== *Verwandte Anker*:
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* <<owasp-top-10,OWASP Top 10>>
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* <<regulated-environment,Reguliertes Umfeld>>
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====

skill/semantic-anchor-translator/references/catalog.md

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- **Proponents:** International Electrotechnical Commission
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- **Core:** Safety integrity levels for safety-critical systems
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### LINDDUN
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- **Also known as:** LINDDUN GO, Privacy Threat Modeling, Privacy STRIDE
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- **Proponents:** Kim Wuyts, Riccardo Scandariato, Wouter Joosen (KU Leuven)
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- **Core:** Privacy threat modeling framework; acronym for seven threat categories — Linkability, Identifiability, Non-repudiation, Detectability, Disclosure of information, Unawareness, Non-compliance; used for DPIA, Privacy by Design, GDPR compliance
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### STRIDE Threat Model
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- **Proponents:** Loren Kohnfelder, Praerit Garg (Microsoft), Adam Shostack
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- **Core:** Spoofing, Tampering, Repudiation, Information Disclosure, Denial of Service, Elevation of Privilege — structured threat categorization for security design

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