Conti Inc.: understanding the internal discussions of a large ransomware-as-a-service operator with machine learning

Author:

Ruellan EstelleORCID,Paquet-Clouston Masarah,Garcia Sebastián

Abstract

AbstractRansomware-as-a-service (RaaS) is increasing the scale and complexity of ransomware attacks. Understanding the internal operations behind RaaS has been a challenge due to the illegality of such activities. The recent chat leak of the Conti RaaS operator, one of the most infamous ransomware operators on the international scene, offers a key opportunity to better understand the inner workings of such organizations. This paper analyzes the main discussion topics in the Conti chat leak using machine learning techniques such as Natural Language Processing (NLP) and Latent Dirichlet Allocation (LDA), as well as visualization strategies. Five discussion topics are found: (1) Business, (2) Technical, (3) Internal tasking/Management, (4) Malware, and (5) Customer Service/Problem Solving. Moreover, the distribution of topics among Conti members shows that only 4% of individuals have specialized discussions while almost all individuals (96%) are all-rounders, meaning that their discussions revolve around the five topics. The results also indicate that a significant proportion of Conti discussions are non-tech related. This study thus highlights that running such large RaaS operations requires a workforce skilled beyond technical abilities, with individuals involved in various tasks, from management to customer service or problem solving. The discussion topics also show that the organization behind the Conti RaaS operator shares similarities with a large firm. We conclude that, although RaaS represents an example of specialization in the cybercrime industry, only a few members are specialized in one topic, while the rest runs and coordinates the RaaS operation.

Funder

Human-centric cybersecurity partnership

Publisher

Springer Science and Business Media LLC

Reference61 articles.

1. Alwashali, A. A. M. A., Abd Rahman, N. A., & Ismail, N. (2021). A survey of ransomware as a service (RaaS) and methods to mitigate the attack. In 2021 14th International Conference on Developments in eSystems Engineering (DeSE), 92–96. ISSN: 2161-1351.

2. Alzahrani, S., Xiao, Y., & Sun, W. (2022). An Analysis of Conti Ransomware Leaked Source Codes. IEEE Access, 10, 100178–100193. Conference Name: IEEE Access.

3. Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent dirichlet allocation. Journal of machine Learning research, 3, 993–1022.

4. Brewer, R. (2016). Ransomware attacks: detection, prevention and cure. Network Security, 2016(9), 5–9.

5. Cimpanu, C. (2020). Conti (Ryuk) joins the ranks of ransomware gangs operating data leak sites. ZDNET. https://www.zdnet.com/article/conti-ryuk-joins-the-ranks-of-ransomware-gangs-operating-data-leak-sites/.

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