Turning reports into responsible intelligence.
CCRNet was created as a research platform for exploring how cybercrime reports can become structured, useful knowledge—without collecting the highly sensitive information that belongs in official or financial systems.
A research foundation for understanding digital crime.
The platform supported our research into how cybercrime reports could be consistently structured, categorized, and analyzed. We also explored how those reports could be converted into useful training data for artificial-intelligence and blockchain-based systems.
The goal was not simply to collect accounts of individual incidents. It was to study how patterns, relationships, and recurring risk signals might be identified across reports—and how that knowledge could support more secure, scalable fraud-prevention tools.
CCRNet remains an independent research initiative. Its work and publications should not be understood as official law-enforcement findings or as determinations that a person or organization committed wrongdoing.
A limited set of voluntarily submitted information.
The only identifying information collected was the reporter’s name, together with the incident information that the reporter chose to submit. Reports were used to support research into cybercrime data structures, classification, analysis, and emerging technical systems.
Sensitive personal and financial credentials were outside the scope.
- Financial or banking information
- Government identification
- Banking credentials or passwords
- Other sensitive personal information
Report intake is currently closed while CCRNet is rebuilt. No incident data is being collected through this website.
Projects and publications shaped by the work.
Research associated with CCRNet contributed to several projects exploring global reporting, secure data infrastructure, and fraud-risk intelligence.
A note on responsible interpretation Research prototypes and publications describe exploratory systems and methods. Analytical signals can support investigation, but they require human review and should never be treated as proof of fraud or guilt.