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    Home»Business»3 defining trends for cybersecurity in 2026
    Business 5 Mins Read

    3 defining trends for cybersecurity in 2026

    Business 5 Mins Read
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    The past year was a landmark for AI proliferation, with sweeping implications for virtually every area of business and life. But with progress came peril. We saw cyberattacks explode in number and sophistication, outmaneuvering legacy security defenses to create record damage.

    These trends will only accelerate from here, and it’s not enough for teams to simply brace for impact. Instead, organizations must anticipate what’s ahead and reimagine their security stacks, thinking about how to preempt attacks and optimizing their workflows.

    Thinking about cybersecurity in the new year, it’s critical to have a clear vision and get to work fast to meet the moment. Here are three trends to watch.

    1. Eyes on the evolving threat landscape

    In 2026, the mass personalization of cyberattacks will disrupt the classical kill chain model, which relies on observing and then reacting to stop threats. Attackers will leverage AI to understand business’s unique vulnerabilities and craft personalized, novel software for each enterprise. This means every organization will see a massive rise in sophisticated, tailored attacks that are not known to the majority of their current security tools, pitting them in a race against time to spot the attack and respond before sustaining widespread damage. Adding AI to reactive tools will help, but will be woefully insufficient to counter this new onslaught. Instead, this shift will require security teams to develop wholly new approaches to preemptively mitigate and avoid these highly personalized threats. 

    AI will also lead to the development of malware that can adapt and evade defensive measures, posing a significant threat to cybersecurity teams. These make it less likely that the novel attacks mentioned above will be detected before they can do large scale damage. AI-powered, autonomous malware will be capable of changing code and behavior to avoid detection, making it harder for security systems to identify and neutralize it. The emergence of autonomous malware will mark a new era in cyberthreats, where AI-driven attacks become increasingly sophisticated and resilient and put further stress on existing security solutions that rely on a detect and respond model to be effective. 

    Compounding these threats, the problem of deepfakes will significantly worsen. The proliferation of deepfakes will increase misinformation and social engineering, leading to major breaches and higher success rates for scams and theft. As AI technology advances, the creation of realistic deepfakes will become easier and more widespread. This will result in a proliferation of fake videos and audio recordings that can be used to deceive individuals and organizations, undermining trust and security. This will coincide and often be combined with a new generation of AI-driven email, text and social media-based attacks. These attacks are tailored to individuals and nearly indistinguishable from legitimate communication, enabling highly personalized, real-time social-engineering campaigns. Relying on humans as a last line of defense has long been a tenuous approach. Against threats this advanced, that approach collapses. Modern security demands automated, adaptive defenses that remove the burden from individuals.

    2. Protect an expanding attack surface

    IoT and IT devices (networking and security infrastructure) will become a bigger target for attacks due to the ease of creating and deploying attacks against them. The proliferation of smart devices in businesses and homes presents an opportunity for attackers to get persistent footholds from which they can pivot and launch attacks or wreak havoc and create disruption of operations. Bespoke and out of date networking and security infrastructure likewise will be exploited as AI can readily adapt attackers for different operating systems and software levels. With AI, it will be much more attractive for cybercriminals to develop and execute attacks on these devices, leading to an increase in security incidents. 

    AI itself is becoming one of the most attractive parts of the attack surface to exploit. Attacks on AI will increase dramatically, leading to significant data leaks and business process disruption. As AI gains ever wider adoption and is interwoven into all aspects of enterprise software, AI’s autonomous nature will be co-opted to enable the AI to function much like a human insider threat, where the internal AI models’ elevated access rights will be leveraged in large scale breaches. Robust security measures are needed to protect the rapidly expanding AI attack surface. 

    3. Cybercrime-as-a-service hits its stride

    The era when a cybercriminal’s reach was constrained by their technical skill is long gone. Today, an AI-driven underground economy is reshaping the threat landscape, empowering financially motivated actors with unprecedented capabilities. These adversaries no longer need deep expertise; they can tap into a growing ecosystem of ready-made services, ranging from exploit kits and ransomware-as-a-service platforms to stolen credential marketplaces and initial access brokers.

    Looking ahead to 2026, this “cybercrime-as-a-service” model is expected to reach new heights of sophistication. AI tools will enable even inexperienced attackers to execute complex, multi-stage campaigns with alarming precision. As a result, the traditional line between opportunistic hackers and highly organized cybercrime syndicates will continue to blur, driving both the scale and complexity of financially motivated attacks to levels we’ve never seen before.

    It’s time to reimagine cybersecurity considering the changes we’ll continue to see in 2026. The world’s pre-AI reactive model of security will not work in an AI-first attacker world. Simply adding AI to these legacy tools will give a false since of comfort in the face of the onslaught that is coming. This is an illusion of improved security that will be painfully exposed in 2026. Enterprises need to think differently in a post-AI world about cybersecurity, transforming from a reactive posture into a preemptive strategy that anticipates rather than reacts to attackers.

    Scott Harrell is CEO of Infoblox.   



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