MALWARE & THREATS Cyber Insights 2026: Malware and Cyberattacks in the Age of AI Security leaders share how artificial intelligence is changing malware, ransomware, and identity-led intrusions, and how defenses must evolve. By Kevin Townsend February 2, 2026 (7:00 AM ET) Flipboard Reddit Whatsapp Email SecurityWeek’s Cyber Insights 2026 examines expert opinions on the expected evolution of more than a dozen areas of cybersecurity interest over the next 12 months. We spoke to hundreds of individual experts to gain their expert opinions. Here we explore malware and malicious attacks in the age of artificial intelligence (AI). The big takeaway from 2026 onward is the arrival and increasingly effective use of AI, and especially agentic AI, that will revolutionize the attack scenario. The only question is how quickly. Michael Freeman, head of threat intelligence at Armis, predicts, “By mid-2026, at least one major global enterprise will fall to a breach caused or significantly advanced by a fully autonomous agentic AI system.” These systems, he continues, “use reinforcement learning and multi-agent coordination to autonomously plan, adapt, and execute an entire attack lifecycle: from reconnaissance and payload generation to lateral movement and exfiltration. They continuously adjust their approach based on real-time feedback. A single operator will now be able to simply point a swarm of agents at a target.” The UK’s NCSC is slightly more reserved: “The development of fully automated, end-to-end advanced cyberattacks is unlikely [before] 2027. Skilled cyber actors will need to remain in the loop. But skilled cyber actors will almost certainly continue to experiment with automation of elements of the attack chain…” Both opinions could be accurate. We don’t yet know how the adversarial use of AI will pan out over the next few years. What we do know is that attacks will increase in volume, speed and targeting, assisted by artificial intelligence. Malware, malicious attacks and AI Effects Almost every segment of an attack chain can be automated by AI. One example is the speed with which attackers will reverse engineer a newly released patch, develop an exploit for the vulnerability and discover which companies are vulnerable almost certainly before the average company can initiate the patch. ADVERTISEMENT. SCROLL TO CONTINUE READING. A second example could be the delivery of finely targeted attacks at the scale of traditional spray and pray attacks. “Malware is becoming far more targeted and personal. Attackers are moving away from mass ‘spray and pray’ tactics and are focusing on specific individuals, organizations, or systems,” says Mehran Farimani, CEO at RapidFort. “By using data gathered from social media, breaches, and online behavior,” he continues, “they can craft attacks that look legitimate and exploit very specific vulnerabilities. Future malware will feel smarter and stealthier, adapting to defenses, learning from user habits, and blending into normal activity.” “Forget ‘spray and pray’,” adds Shaun Cooney, CPTO at Promon, “this is more akin to mass targeting with a sniper rifle.” James Wickett, CEO at DryRun Security, adds the low cost of using AI to the advance of precision targeting. “The economics have flipped,” he says. “The cost to go from vulnerability discovery to exploit used to be weeks and thousands of dollars. Now it’s near zero. So instead of mass ‘spray and pray’ campaigns, we’ll get micro-targeted attacks built for a single system, a single company, maybe even a single developer.” A third example is the media’s headline threat from AI – the automation of the complete attack lifecycle from vulnerability detection, exploit production, to malware payload delivery and data exfiltration. Cory Michal, CSO of AppOmni, calls it the rise of ‘vibe-hacking’. “We’ve observed attackers using AI to automatically generate data extraction code, reconnaissance scripts, and even adversary-in-the-middle toolkits that adapt to defense. They’re essentially ‘vibe-hacking’ using generative AI to better mimic authentic behavior, refine social engineering lures, and accelerate the technical aspects of intrusion and exploitation.” When these components can be chained together under the orchestration of agentic AI, we will be closer to the one-click fully automated attack. “LLM-enabled malware has already moved from proof-of-concept to practice,” says Steve Stone, SVP of threat discovery & response at SentinelOne. “Our discovery of MalTerminal (the earliest known GPT4-powered malware capable of generating ransomware or reverse-shell code at runtime), along with ESET’s PromptLock sample and emerging campaigns like LameHug and PromptSteal, show how attackers are experimenting with AI to create polymorphic, self-evolving payloads.” These tools blur the line between code and conversation, he continued, “allowing malicious logic to be generated dynamically and evade traditional signatures.” AI agents can already prepare the stages while agentic AI will be the glue that chains them behind a single click. We’re not there yet, but the potential exists and that future will undoubtedly come. Ransomware Extortion will remain a primary purpose of malicious attacks simply because of its success. According to FinCEN, $2.1 billion was paid in ransoms during the three years 2022 to 2024. In 2023 the figure amounted to $1.1 billion (the all-time high) but subsided to $734 million in 2024. Two years can hardly be considered a trend, but many commenters believe that ransomware is slowly becoming less successful due to increased pressure against ransom payments and improved cyber defenses. Counter intuitively, if true, this ‘trend’ may be strengthened rather than reversed by the rise of AI. Jason Baker, Managing Security Consultant of Threat Intelligence at GuidePoint Security. Jason Baker, managing security consultant of threat intelligence at GuidePoint Security, explains. “AI-generated ransomware, or other malware used for extortion, presents a problem for the users – namely, they are unlikely to fully understand how it works, or how to troubleshoot or debug issues.” Now imagine you’re an extortionist, he continues. “Your victim has paid, and your AI-generated decryption tool doesn’t work. How do you fix this? Do you have any incentive to fix it? And how long do people keep paying you ransoms once the word gets out that you can’t undo the damage you’ve done?” The return of DDoS? DDoS declined because of the success of ransomware – but it may return due to any decline in ransomware. “Attackers are reverting to one of their oldest and most disruptive tools: the denial-of-service attack. In 2026, we’ll see a record-setting resurgence of DDoS activity: the largest volumetric attack ever recorded, and the highest requests-per-second rate in history,” warns David Holmes, application security CTO at Thales. He notes that Imperva’s network is already seeing early signs: attacks that are 50% larger than anything we’ve seen before. “For threat actors, the playbook is simple. If they can’t extort you with encryption, they’ll take you offline instead. Organizations that spent the past few years fortifying against ransomware will now have to look outward again, reinforcing cloud-based DDoS protection and adaptive mitigation to withstand the next wave. The attackers haven’t disappeared; they’ve just changed tactics, and in 2026, they’ll come roaring back.” AI will play a major part in enabling and improving the efficiency of these DDoS attacks. The no-malware alternative The no-malware alternative isn’t completely no-malware, but the malware is limited to third party infostealers. “The defining shift in malware heading into 2026 is the consolidation of the entire attack chain around infostealers. They’ve become the entry point, the data broker, the reconnaissance layer, and the fuel for everything that comes after,” suggests the Flashpoint Analyst Team, noting that 1.8 billion credentials were stolen by infostealers in the first half of 2025. The Team continues, “AI-generated malware will get headlines, but threat actors don’t need fully autonomous malware when infostealers already automate the hardest part: initial compromise at scale.” Those same stealers no longer just collect passwords – they also collect session cookies, access tokens, host metadata, browser profiles and more. The attacker can assume the victim’s identity outright. Once inside the target network, a seasoned attacker can live off the land (LotL) effectively invisibly until data exfiltration without the use of any malware. This scenario is supported by Adrian Culley, senior sales engineer at SafeBreach. “The preferred method of intrusion is shifting universally toward Identity-led, malware-free Intrusions,” he says. “The focus on LotL TTPs allows intrusions to blend into normal network activity.” Infostealers can provide easy access, while LotL provides stealthy collection and exfiltration of data without requiring malware. Extortion may remain the priority motive, but “Think less ‘pay to decrypt’, and more ‘pay to stop leaks’,” suggests Yaz Bekkar, principal consulting architect XDR, at Barracuda Networks. The new criminal ecosystem Hacker levels Only sophisticated organized crime groups and nation state actors will have the immediate technical skill to realize the full potential of artificial intelligence. But AI is removing the entry barrier for new and unskilled hackers. As a result, there will be three distinct classes of bad actor in the future: elite nation state, organized crime, and a rapidly expanding script kiddie level. “The criminal ecosystem will change,” explains Bekkar. “With AI, you don’t need deep skills, you need ideas. As barriers to entry drop even further, more low-skilled actors will become more dangerous, faster. At the same time, the dominant gangs won’t disappear; instead, they’ll run ‘platforms’ and affiliate programs, renting out AI-driven kits.” “The