Darkode: Recruitment Patterns and Transactional Features of “the Most Dangerous Cybercrime Forum in the World”
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article explores the social and market dynamics of Darkode, an invitation-only cybercrime forum that was dismantled by the FBI in July 2015 and was described by a U.S. Attorney as “the most sophisticated English-speaking forum for criminal computer hackers in the world.” Based on a leaked database of 4,788 discussion threads, we examine the selection process through which 344 potential new members introduced themselves to the community in order to be accepted into this exclusive group. Using a qualitative approach, we attempt to assess whether this rigorous procedure significantly enhanced the trust between traders, and therefore, contributed to the efficiency of this online illicit marketplace. We find that trust remained elusive and interactions were often fraught with suspicion and accusations. Even hackers who were considered successful faced significant challenges in trying to profit from the sale of malicious software and stolen data.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it