The cybercriminal labor market and the campaigns it’s supporting. Russia’s Killnet is running DDoS attacks against US hospitals, but Russia says, hey, it’s the real victim here.
Some perspective on the cybercriminal labor market. DocuSign is impersonated in a credential-harvesting campaign. Social engineering pursues financial advisors. Killnet is active against the US healthcare sector. Mr. Security Answer Person John Pescatore has thoughts on cryptocurrency. Ben Yelin and I debate the limits of section 230. And, hey, who’s the real victim in cyberspace? A hint: probably not you, Mr. Putin.
For links to all of today's stories check out our CyberWire daily news briefing:
https://thecyberwire.com/newsletters/daily-briefing/12/20
Perspectives on the cybercriminal labor market. (CyberWire).
IT specialists search and recruitment on the dark web (Securelist)
Cybercrime job ads on the dark web pay up to $20k per month (BleepingComputer)
Report on hackers' salaries shows poor wages for developers (Register)
Cybercrime groups offer six-figure salaries, bonuses, paid time off to attract talent on dark web (CyberScoop)
Application security risks. (CyberWire)
Survey gives insight into new app security challenges (Cisco App Dynamics)
DocuSign impersonated in credential phishing attack. (CyberWIre)
Breaking the Impersonation: Armorblox Stops DocuSign Attack (Armorblox)
"Pig butchering" and financial advisor impersonation scams. (CyberWire)
No Blocking, No Issue: The Curious Ecosystem of Financial Advisor Impersonation Scams (Domain Tools)
Ukraine at D+341: Killnet hits US hospitals.(CyberWire)
HC3 TLP Clear Analyst Note: Pro-Russian Hacktivist Group Threat to HPH Sector (American Hospital Association)
HHS, AHA Warn of Surge in Russian DDoS Attacks on Hospitals (Gov Info Security)
Russian hackers allegedly take down Duke University Hospital’s website (Carolina Journal)
The Evolution of DDoS: Return of the Hacktivist (FSISAC)
Russia becomes target of West’s coordinated aggression in cyberspace — MFA (TASS)
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.
A comprehensive extraction focused on health practices, protocols, claims, and safety caveats.
A dedicated analysis of warnings, limitations, trade-offs, weak evidence, and uncertainty.
Repeatable methods, frameworks, mental models, processes, and systems.
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.