Ransomware-as-a-Service and its Evolution: Lessons from the Babuk, GandCrab, and Sodinokibi Families
Bibliographic record
Abstract
Ransomware-as-a-Service (RaaS) has transformed cybercriminal operations by enabling threat actors to launch ransomware attacks using ready-made tools provided by developers. This study analyzes the evolution of several RaaS samples from Babuk, GandCrab, and Sodinokibi collected over several years. We introduce a novel learning model that uses contrastive techniques to understand the underlying patterns in the malware's binary code, enabling better capture of the subtle changes they undergo as ransomware evolve. Our method, which focuses on concept drift, demonstrates strong capability in identifying different variants, achieving an accuracy of almost 80% in distinguishing their forms from other ransomware types. These findings shed light on the difficulties RaaS malware presents for standard defenses and emphasize the need for sophisticated analytical tools in cybersecurity to mitigate their threats.
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How this classification was reachedexpand
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".