If you're running a red team, let someone know it's a drill. Apache patches Struts. Another exposed AWS bucket. Remcos abused by hackers. DPRK goes after Macs. Dark Tequila runs in Mexico.
In today's podcast, we hear that a phishing attempt against the Democratic National Committee turned out to have been a poorly coordinated red-team exercise. Apache patches a remote code execution vulnerability in Struts. Another exposed AWS bucket. Remcos remote administration tool is being abused by black hats. Dark Tequila goes after customers of Mexican financial institutions. The Lazarus Group is back, and it's getting into Macs for the first time. Joe Carrigan from JHU ISI on Android vs. iOS data privacy. Guest is Oren Falkowitz from Area 1 Security on protection against phishing attempts.
For links to all of today's stories check our our CyberWire daily news brief:
https://thecyberwire.com/issues/issues2018/August/CyberWire_2018_08_23.html
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.
Technologies, AI models, technical methods, capabilities, limitations, and adoption implications.
Repeatable methods, frameworks, mental models, processes, and systems.
A dedicated analysis of warnings, limitations, trade-offs, weak evidence, and uncertainty.
A dedicated inventory of concrete resources named in the episode.
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.