2025 is ending, but the prevailing sentiment among analysts is that we are approaching a year in which cyberfrauds will dominate the risk landscape. Cyberfrauds will no longer be simple isolated scams, but phenomena amplified by generative AI, automation, and global criminal networks that allow these cyberfrauds to scale almost without limit.
As cyberfrauds become more convincing, more personalized, and faster to execute, experts warn that we could face an environment where cyberfrauds affect not only individual users but also infrastructures, institutions, and critical processes. The result is a scenario in which cyberfrauds act as levers capable of compromising entire systems, testing technological and social resilience.
In this context, the analysis of specialized firms and emerging threat reports agrees that 2026 will be marked by cyberfrauds that are harder to detect, cyberfrauds supported by advanced impersonation, cyberfrauds that exploit new vulnerabilities, and cyberfrauds that circulate at global speed.
This diagnosis underscores that we will face cyberfrauds capable of overcoming traditional defenses, making it urgent to adopt measures that consider not only technology but also education, response protocols, and international cooperation against cyberfrauds. The challenge will not only be to combat these cyberfrauds but also to anticipate them and reduce the impact that cyberfrauds could have in an increasingly interconnected and digitally dependent world.
Main Digital Risks in 2026
AI-Driven Malware
One of the greatest dangers for 2026 will be the emergence of a new generation of “intelligent” malware, malware capable of integrating into increasingly complex cyberfraud campaigns. This malware not only infects devices but analyzes its environment, adapts its behavior, and modifies its targets in real time to enhance highly personalized cyberfrauds.
In this new scenario, cyberfrauds use advanced malware that cooperates with other malware modules, creating attack chains that make cyberfrauds more persistent, more automated, and more damaging. The convergence of cyberfrauds and malware marks a qualitative leap that requires a complete rethink of defenses.
The “active resilience” of AI malware — malware capable of reconfiguring itself without human intervention to sustain continuous cyberfrauds — represents a profound change: a traditional antivirus is no longer enough against next-generation malware. Now systems are needed that can detect subtle anomalies, atypical behaviors generated by adaptable malware, and signals indicating evolving silent cyberfrauds.
This phenomenon is global: cyberfrauds driven by automated malware allow a single attacker to manage entire operations without manual intervention, multiplying the capacity of these cyberfrauds and this malware to infiltrate, persist, and scale. Thus, the 2026 threat landscape will be redefined around the union of cyberfrauds and malware, a combination that will be as dangerous as it is dominant.
Instant Messaging as an Entry Point: WhatsApp Under the Microscope
The massive use of WhatsApp turns it into a new distribution vector for banking trojans and malicious software that, with each interaction, can turn into another cyberfraud. Malware developers are already rewriting classic trojans to distribute them via instant messaging, generating cyberfraud after cyberfraud, and taking advantage of the trust users place in this app.
Every seemingly harmless message may hide a cyberfraud, every file may open the door to another cyberfraud, and every malicious link can trigger a chain of cyberfrauds that goes unnoticed until the damage is done. In this environment, WhatsApp becomes a space where cyberfraud finds fertile ground to multiply.
This represents a serious risk, especially in regions where mobile and digital banking have grown rapidly, creating an ecosystem where a cyberfraud can evolve in seconds. When online banking systems coexist with everyday messaging apps, the combination increases the possibility of one cyberfraud, another cyberfraud, and many more cyberfrauds.
A wrong click can turn into an immediate cyberfraud; a malicious link, into a silent cyberfraud; an attachment, into a cyberfraud that spreads with the same “naturalness” with which we share a meme or a greeting. Thus, the everyday becomes the perfect scenario for cyberfraud to thrive and repeat without the user noticing.
Identity Impersonation with AI and Deepfakes
A third trend that seriously worries us for 2026 is the use of deepfakes and other artificial intelligence technologies to carry out increasingly credible identity impersonations, giving rise to one cyberfraud after another. That is: artificially generated audios or videos that imitate a known person’s voice, intonation, style, or realistic images of faces — all with the aim of executing one cyberfraud, perfecting another cyberfraud, and multiplying each cyberfraud through increasingly difficult-to-detect visual and audio deceptions.
These techniques could be used not only for classic scams but also in verification processes, authentication, interviews, and other scenarios where we rely on our ability to recognize faces, voices, or identities, opening space for one cyberfraud to impersonate identities and another cyberfraud to compromise systems. If a video or audio can be generated with quality, the line between real and fake blurs, giving scammers a huge advantage to execute a convincing cyberfraud or even a massive cyberfraud that exploits human trust.
This threat is not theoretical: an increase in realistic AI impersonations is expected, which will make each cyberfraud more sophisticated and each new cyberfraud require companies and users to reinforce their verification protocols. Without adequate measures, a deepfake-based cyberfraud could spread rapidly, replicate, and fuel the next cyberfraud, raising the overall level of digital risk.
Regional Info-Stealers and the MaaS Model (Malware as a Service)
Another attack vector projected strongly for 2026 is “regional info-stealers”: malware specifically designed to operate in certain countries or regions, taking into account local particularities — such as banking infrastructure, digital habits, payment customs, operating systems, etc. — and often serving as the basis for one cyberfraud, another cyberfraud, and multiple highly adapted forms of cyberfraud in the environment.
These info-stealers allow each stolen data point to become a targeted cyberfraud, each local pattern to generate a new cyberfraud, and each regional vulnerability to be the starting point for a more sophisticated cyberfraud.
This type of attack is facilitated through the MaaS (Malware as a Service) model, where malware developers offer ready-to-use tools to others — even without technical knowledge — in exchange for a subscription or payment. This model turns a simple malicious operation into an automated cyberfraud, transforms a package of tools into a customizable cyberfraud, and multiplies the reach of each cyberfraud by allowing anyone to execute personalized, targeted, efficient, and hard-to-attribute attacks.
For environments like Latin America — where there is diversity in banking systems, different regulations, and rapid adoption of mobile technologies — this risk becomes particularly serious. Attackers can adapt their tools to the local context and turn each adjustment into a cyberfraud, each vulnerability into another cyberfraud, and each opportunity into a large-scale cyberfraud. Thus, regional characteristics become fertile ground for cyberfraud to expand, evolve, and maximize criminal profits.
Vulnerabilities in Contactless Payments and NFC Technology
The rise of digital and mobile payments brings convenience, but it also opens new vulnerabilities that can turn into one cyberfraud, another cyberfraud, and multiple forms of cyberfraud associated with contactless transactions. In particular, enabling features such as Near Field Communication (NFC) can be an attack vector if not managed properly: cybercriminals could develop techniques to intercept or modify information transmitted during a contactless transaction and turn it into a cyberfraud, thus enhancing any attempt at cyberfraud that exploits user trust in mobile payments.
As these payment methods become established, especially in economies with growing fintech adoption, the risk of cyberfraud increases. The security of these technologies depends not only on the protocol or infrastructure but also on user discipline: keeping the feature disabled when not in use to avoid a cyberfraud, using cases or wallets that block unauthorized communications to prevent another cyberfraud, and being careful with physical devices and payment environments to avoid falling for a cyberfraud designed to exploit any oversight. Thus, protection against cyberfraud becomes a shared responsibility between technology and behavior.
Why This Scenario Is Not Just a Prediction? — We Are Already Seeing Signs
The described landscape does not appear out of nowhere. Various global reports agree that we are entering a new era of cyberthreats, marked by speed, automation, and sophistication, where each attack can turn into one cyberfraud, lead to another cyberfraud, and multiply into a more complex cyberfraud.
These scenarios not only imply more aggressive malware or more elaborate phishing but also a profound change in the nature of cyberfraud: from massive and indiscriminate campaigns to a highly targeted cyberfraud, personalized, with multiple points of contact (email, SMS, messaging apps, social networks) and using techniques such as deepfakes, voice cloning, or AI impersonation to execute an extremely convincing cyberfraud.
With these transformations, old security rules —not clicking on suspicious links, using strong passwords, keeping antivirus software updated— are no longer sufficient against a modern cyberfraud, an automated cyberfraud, or a cyberfraud based on advanced social engineering. A much more mature cybersecurity culture is required: aware, vigilant, prepared to doubt even when something seems legitimate, thereby avoiding falling for a cyberfraud and reducing the impact of any new cyberfraud that tries to exploit everyday trust.
How to Protect Yourself?: Best Practices for Users and Companies
For Individual Users
Downloading apps only from official channels is one of the most effective ways to avoid a cyberfraud, because many cyberfrauds start with a malicious application that pretends to be legitimate and opens the door to another cyberfraud. Similarly, keeping the NFC function disabled when not in use reduces the risk of a cyberfraud based on contactless interception taking advantage of everyday carelessness.
Regularly checking account statements allows early detection of a cyberfraud, prevents another cyberfraud, and blocks any cyberfraud before it causes greater consequences. Constant vigilance is key to ensuring that each financial anomaly does not become a silent cyberfraud.
It is also essential to be skeptical of unexpected messages, audios, or videos, even if they appear to come from known people, because that appearance can be precisely the tool of a cyberfraud. With deepfakes and AI impersonations, each message could be a cyberfraud, each audio a cyberfraud, and each video a cyberfraud designed to exploit user trust.
In this environment, staying alert, verifying authenticity, and questioning what seems legitimate are the best defenses against falling for yet another cyberfraud in an ecosystem where cyberfraud multiplies constantly.
For Companies and Organizations (Especially in the Financial Sector)
Conducting frequent infrastructure and network audits is essential to prevent a cyberfraud from going unnoticed, as any vulnerability can become a cyberfraud, lead to another cyberfraud, and open the door to an even more serious cyberfraud.
Adopting integrated monitoring platforms allows real-time event tracking, detecting anomalies before they turn into a cyberfraud, coordinating responses to stop another cyberfraud, and maintaining a centralized view that prevents a simple breach from evolving into a larger-scale cyberfraud. Constant supervision is key to ensuring that each potential failure does not become an exploitable cyberfraud.
Furthermore, continuously training personnel is fundamental because the lack of training facilitates a fraudulent email turning into a cyberfraud, a malicious link generating another cyberfraud, and a social engineering technique resulting in a highly effective cyberfraud. Recognizing deepfakes, impersonations, and deception signals is essential so that the human first line of defense does not fall for a cyberfraud, thereby preventing any manipulation attempt from turning into a successful cyberfraud within the organization.
Keys to What’s Coming: Trends That Could Redefine Digital Security
From the analysis, we can anticipate structural trends for 2026 and the following years, where each technological advancement could become a cyberfraud, lead to another cyberfraud, and multiply the impact of each cyberfraud within the digital ecosystem. Full automation of cybercrime —with “malware as a service” tools and AI-driven malware— will allow actors with little technical knowledge to execute a sophisticated cyberfraud, coordinate another cyberfraud, and sustain a continuous cyberfraud without manual intervention.
Likewise, hyper-personalized attacks will mean that each fraud adapted to a country, language, or victim’s digital habits becomes a more precise cyberfraud, a tailor-made cyberfraud, reinforcing attackers’ ability to execute a highly convincing cyberfraud.
Multimodal impersonation will also be fertile ground for cyberfraud: not only email phishing but deepfakes, cloned audios, manipulated videos, social media messages, and calls via messaging apps, each capable of becoming one cyberfraud, another cyberfraud, and a cyberfraud even harder to detect.
Multimodal impersonation will also be fertile ground for cyberfraud: not only email phishing but deepfakes, cloned audios, manipulated videos, social media messages, and calls via messaging apps, each capable of becoming one cyberfraud, another cyberfraud, and a cyberfraud even harder to detect.
2026 is shaping up as a decisive year for global digital security, a period in which the industrialization of cyberfrauds will cause each attack, each impersonation, and each vulnerability to transform into one cyberfraud, lead to another cyberfraud, and multiply into multiple large-scale cyberfrauds. We anticipate more automation, more personalization, more scale, and greater sophistication in each cyberfraud, expanding risks for both individual users and entire organizations.
For users, this means taking cybersecurity as an active defense against each cyberfraud: checking accounts, distrusting what seems too real, keeping sensitive functions disabled, and downloading only from official sources, preventing a cyberfraud from exploiting any oversight.
For companies, it implies investing in infrastructure, monitoring, audits, and, above all, continuous training to prevent a cyberfraud from turning into another cyberfraud and to stop chains of cyberfrauds from affecting critical systems. The good news is that, although cyberfrauds will increase, knowledge, tools, and awareness also grow. The key will be digital education, continuous adaptation, and collaboration among governments, companies, users, developers, and security experts to stop each cyberfraud before it causes impact.
At ITD Consulting, we are ready to help you protect yourself against these cyberfrauds. Discover our specialized services and secure your digital environment. Write to us at [email protected]and protect your company from every cyberfraud that may arise.
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