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Cybercrime as a Service: A Scoping Review

Mauko, Ema et al. · arxiv_oai_expanded
arXiv (OAI Expanded) · Papers
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cryptography-and-securityemerging-technologies
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[2604.00063] Cybercrime as a Service: A Scoping Review Skip to main content Search Submit Donate Log in Computer Science > Cryptography and Security arXiv:2604.00063 (cs) [Submitted on 31 Mar 2026] Title: Cybercrime as a Service: A Scoping Review Authors: Ema Mauko , Shane D Johnson , Enrico Mariconti View PDF Abstract: Cloud computing has drastically altered the ways in which it is possible to deliver information technologies in a service-led structure, however, this has also been reflected in the cybercrime domain. Cybercrime as a Service is an economic model where a technically skilled actor offers a given cyberattack as an end-to-end service to non-technical actors who pay a subscription fee for said service. The services, which can vary in scope, targets, and delivery modes, include everything from the vulnerability discoveries, delivery of the attack, and the attack itself to financial rewards to the subscriber. In this scoping literature review, we analysed 195 articles from both academic and grey literature with a view of investigating the services articles studied, the methodological approach the how the CaaS model is predicted to develop in the future. Our review indicates that with further commercialisation of the model will further lower the barrier of entry to the cybercrime realm, increase sophistication of the attacks and increase resilience of the service providers and their ecosystem which will result in harder shutdowns of services by the authorities. Furthermore, as the model becomes more accessible, groups such as organised crime groups, extremist actors may use them as well, which may have implications for criminal activity in both cyber and physical domains. Subjects: Cryptography and Security (cs.CR) ; Emerging Technologies (cs.ET) Cite as: arXiv:2604.00063 [cs.CR] (or arXiv:2604.00063v1 [cs.CR] for this version) https://doi.org/10.48550/arXiv.2604.00063 Focus to learn more arXiv-issued DOI via DataCite Journal reference: 2026. ACM Comput. Surv. 58, 15, Article 380 (November 2026), 37 pages Related DOI : https://doi.org/10.1145/3833078 Focus to learn more DOI(s) linking to related resources Submission history From: Ema Mauko [ view email ] [v1] Tue, 31 Mar 2026 08:26:11 UTC (1,639 KB) Full-text links: Access Paper: View PDF view license Additional Features Audio Summary Current browse context: cs.CR < prev | next > new | recent | 2026-04 Change to browse by: cs cs.ET References & Citations SciX Google Scholar Semantic Scholar export BibTeX citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs . Which authors of this paper are endorsers? | Disable MathJax ( What is MathJax? ) We gratefully acknowledge support from our major funders , member institutions , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab)

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