Frameworks
in context.
A practical guide to complementary threat modelingFrameworks in context
A public guide to choosing complementary perspectives, asking useful questions and keeping human judgment central.
Read the whitepaper ↗RESEARCH & INSIGHTS
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10 resources
Frameworks
A practical guide to complementary threat modelingChoosing a framework starts with context
Architecture, privacy, adversary behavior and verification answer different questions. Start with the one your team needs to resolve.
Read the insight ↗From architecture to accountable action
A system diagram becomes more useful when every security decision can be connected to its context, evidence and owner.
Read the insight ↗Human judgment belongs inside the workflow
Clear assumptions, reviewable recommendations and meaningful challenge make security discussions more accountable.
Read the insight ↗EXTERNAL RESEARCHCarnegie Mellon University Software Engineering Institute
Threat Modeling: A Summary of Available Methods
A comparison of twelve approaches that helps teams select complementary methods for their project’s security, privacy and risk concerns.
Read the original ↗EXTERNAL RESEARCHMITRE
MITRE ATT&CK: Design and Philosophy
An account of how ATT&CK organizes adversary behavior and why its knowledge base is designed and maintained the way it is.
Read the original ↗EXTERNAL RESEARCHNIST
Secure Software Development Framework (SSDF) Version 1.1: Recommendations for Mitigating the Risk of Software Vulnerabilities
High-level secure development practices for integrating security into software lifecycles and improving shared expectations between producers and consumers.
Read the original ↗EXTERNAL RESEARCHNIST
Guide to Data-Centric System Threat Modeling
Foundational principles for examining threats and defensive choices around selected data within a system; the linked publication remains a draft.
Read the original ↗EXTERNAL RESEARCHKU Leuven, Department of Computer Science
LINDDUN privacy threat modeling: a tutorial
A worked introduction to using system models and privacy threat categories to move from privacy concerns toward requirements and mitigations.
Read the original ↗EXTERNAL RESEARCHUSENIX, SOUPS 2026
AI’ve Got a Bad Feeling About This: A Privacy Threat Modeling Framework for GenAI
Research extending LINDDUN with generative-AI privacy concerns, illustrated through chatbot and agent-based case studies.
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