Three CISA Senior Advisers on Secure by Design
Secure by Design means different things to different people. As part of Lawfare’s ongoing project to understand what Secure by Design might mean in practice, we are trying to identify the open questions—areas where research or inquiry might help our collective understanding of the concept and how it might work. Lawfare Contributing Editor Paul Rosenzweig sat down with three Senior Advisers to CISA—Lauren Zabierek, Jack Cable, and Bob Lord—who work on the cutting edge of SbD design and implementation, to get their thoughts on research that would be of ongoing value to their efforts to define an SbD standard.
You can watch a video version of their conversation here.
For more information, including the resources mentioned in this episode:
- CISA, U.S. and International Partners Announce Updated Secure by Design Principles Joint Guide | CISA
- CISA, NSA, FBI and International Cybersecurity Authorities Publish Guide on The Case for Memory Safe Roadmaps | CISA
- Blog: The Next Chapter of Secure by Design | CISA
- Expanded Secure by Design Publication: Secure-by-Design | CISA
- White Paper: https://www.cisa.gov/resources-tools/resources/secure-by-design (English and Spanish versions available)
- Blog on Memory Safety: The Urgent Need for Memory Safety in Software Products | CISA
- Applying Secure By Design to events : Applying “Secure By Design” Thinking to Events in the News | CISA
- RFI on secure software attestation form: CISA Requests Comment on Draft Secure Software Development Attestation Form | CISA
- Director Jen Easterly on updated Secure by Design in Singapore (start 2:12): SICW Opening Ceremony & SICW High-Panels - Opening Plenary - YouTube
- Rosenzweig on Auto/Cyber Liability: https://tcg-website-prod.azurewebsites.net/the-evolving-landscape-of-cybersecurity-liability/
- Unsafe At Any Speed: CISA's Plan to Foster Tech Ecosystem Security (youtube.com)
Support this show http://supporter.acast.com/lawfare.
Hosted on Acast. See acast.com/privacy for more information.
Available Results
Generated results are saved to your library for reuse and search.
Choose Template
Pick the result you want. You can review provider and model before generating.
A concise first-pass summary for understanding the episode quickly.
A comprehensive, source-grounded extraction of the reusable knowledge in an episode.
Scientific findings, mechanisms, studies, hypotheses, and the limits of the evidence discussed.
A dedicated analysis of warnings, limitations, trade-offs, weak evidence, and uncertainty.
Memorable statements and important claims with attribution and source context.
Technologies, AI models, technical methods, capabilities, limitations, and adoption implications.
A concise first-pass summary for understanding the episode quickly.
A detailed readable summary organized by chapter or topic.
A navigable map of subjects, topic flow, and suggested chapters.
A comprehensive, source-grounded extraction of the reusable knowledge in an episode.
Reusable atomic knowledge units extracted from the episode.
A comprehensive extraction focused on health practices, protocols, claims, and safety caveats.
A comprehensive extraction focused on opportunities, strategy, markets, and company building.
Explicit actions, next steps, habits, recommendations, and things to avoid.
A dedicated inventory of concrete resources named in the episode.
A dedicated analysis of warnings, limitations, trade-offs, weak evidence, and uncertainty.
A concise first-pass summary for understanding the episode quickly.
A detailed readable summary organized by chapter or topic.
A navigable map of subjects, topic flow, and suggested chapters.
A comprehensive, source-grounded extraction of the reusable knowledge in an episode.
Reusable atomic knowledge units extracted from the episode.
A comprehensive extraction focused on health practices, protocols, claims, and safety caveats.
A comprehensive extraction focused on opportunities, strategy, markets, and company building.
Scientific findings, mechanisms, studies, hypotheses, and the limits of the evidence discussed.
Technologies, AI models, technical methods, capabilities, limitations, and adoption implications.
Investment theses, assets, catalysts, valuation reasoning, time horizons, and risks.
Chronologies, actors, causes, consequences, turning points, and competing historical interpretations.
Policies, proposals, stakeholders, arguments, implementation constraints, and predicted effects.
Career paths, skills, hiring signals, workplace decisions, transitions, and limitations of the advice.
Behavioral mechanisms, biases, motivation, habits, emotions, interventions, and evidence limitations.
Economic mechanisms, incentives, indicators, market structure, forecasts, and uncertainty.
Leadership principles, team systems, organizational design, culture, feedback, and failure modes.
Audience, positioning, messaging, acquisition, retention, experiments, metrics, and failed approaches.
Teaching methods, learning strategies, practice, feedback, assessment, and effectiveness evidence.
Theses, premises, arguments, objections, values, thought experiments, and unresolved questions.
Communication patterns, conflict, boundaries, expectations, repair methods, and contextual limitations.
Books, papers, authors, courses, and other learning resources mentioned in the episode.
Repeatable methods, frameworks, mental models, processes, and systems.
Explicit actions, next steps, habits, recommendations, and things to avoid.
Memorable statements and important claims with attribution and source context.
A dedicated inventory of concrete resources named in the episode.
A dedicated analysis of warnings, limitations, trade-offs, weak evidence, and uncertainty.