Assessing Crime Disclosure Patterns in a Large-Scale Cybercrime Forum

Researchers analyzed over 3.5 million posts from a major cybercrime forum, finding that 25% of initial posts contain explicit crime-related content and over one-third of users disclose criminal activity. The study used large language models to classify content and revealed that most users show restraint by gradually escalating disclosure through ambiguous 'grey' content before explicit criminal posts.

• →25% of initial posts on cybercrime forums contain explicit crime-related content, showing crime disclosure is relatively normative.
• →Over one-third of users disclose criminal activity at least once in their initial forum posts.
• →Most participants show restraint with two-thirds posting only benign or grey content before escalating disclosure gradually.
• →Grey posts serve as anchoring mechanisms where users avoid overt criminal statements through ambiguous content.
• →Large language models prove effective for scalable classification of criminal content in cybercrime forums.