Malware Attacks: More Than Just Ransomware

This post was originally published in August 2021 and has been substantially updated to reflect the current malware landscape as of 2026.

Ransomware still dominates security headlines, and for good reason. The ZeroFox Q4 2025 Ransomware Wrap-Up documented 2,091 ransomware and digital extortion incidents in a single quarter, a 46% increase from Q3 of the same year. But ransomware is one branch of a much larger tree. Security teams that focus their detection strategy exclusively on ransomware are missing the infostealers harvesting credentials at scale, the AI-generated payloads evading signature-based tools, and the supply chain compromises that turn trusted software into an attack vector.

This post covers the malware types that matter most in 2026, how delivery methods have evolved, and what effective malware detection looks like when the threat landscape moves this fast.

How the Malware Landscape Has Changed

Five years ago, the malware conversation centered on ransomware groups, commodity trojans, and exploit kits delivered through malicious domains. The fundamentals haven't disappeared, but the economics have shifted in ways that make every category more dangerous.

AI has compressed the development cycle. Threat actors are using large language models to generate functional malware faster than ever. IBM X-Force documented Slopoly, a backdoor likely built using an LLM, deployed by the Hive0163 group in an Interlock ransomware attack in early 2026. The malware maintained persistent server access for over a week. As IBM noted, AI-generated malware reduces the time an operator needs to develop and execute an attack, lowering the barrier for less-skilled actors.

Infostealers have become the dominant entry point. These tools do more than collect passwords; they harvest session cookies, access tokens, browser profiles, and host metadata, giving attackers enough to assume a victim's identity outright. And the supply chain has become an attack surface. In March 2026, the threat group TeamPCP compromised LiteLLM, a popular AI library downloaded millions of times daily, by first backdooring the Trivy security scanner used in its CI/CD pipeline. The malicious packages harvested API keys, cloud tokens, and SSH keys from every developer environment that installed them.

Malware Types Security Teams Should Prioritize in 2026

Ransomware and Ransomware-as-a-Service (RaaS)

While we’re focused on more than ransomware, it still remains the most visible and financially destructive malware category. What's changed is the business model. Ransomware-as-a-Service platforms mean the person building the ransomware and the person deploying it are often different entities. Double and triple extortion (encrypting data, stealing it, and threatening DDoS or contacting customers) is now standard operating procedure. The 2026 Key Forecasts Report from the ZeroFox Intelligence team projects continued diversification of ransomware operations, with new groups spinning up and rebranding faster than law enforcement can disrupt them.

Infostealers

Infostealers are the malware category that has grown the most since 2021 and arguably the one with the broadest impact. These tools run silently on compromised endpoints, harvesting credentials, cookies, tokens, and browser data, then exfiltrating everything to attacker-controlled infrastructure. Stolen credentials fuel ransomware attacks, account takeovers, and fraud operations downstream. They're the supply chain of cybercrime: one successful infostealer deployment feeds dozens of follow-on attacks.

Trojans and Remote Access Trojans (RATs)

Trojans disguise themselves as legitimate software to gain system access. RATs extend that access by giving attackers persistent, remote control over compromised machines. The Interlock ransomware group's NodeSnake RAT, deployed against UK universities in 2025, is a current example: it establishes persistent network access through phishing emails, then supports lateral movement, data exfiltration, and eventual ransomware deployment. Modern RATs often include backdoor functionality and rootkit techniques to evade detection and maintain long-term access.

Spyware

Spyware monitors user activity, captures keystrokes, records browsing history, and exfiltrates personal or corporate data. Kaspersky telemetry shows spyware detections up roughly 51% year-over-year, driven by renewed interest in surveillance and fraud. Mobile spyware has expanded rapidly, with Android-targeted variants increasingly capable of intercepting one-time passwords, NFC transactions, and banking sessions.

Worms and Supply Chain Malware

Worms spread autonomously by exploiting vulnerabilities, without requiring user interaction. What's new is the supply chain dimension. The TeamPCP campaign in March 2026 included a self-propagating npm worm that spread across dozens of packages, turning trusted developer tooling into a distribution mechanism. This category now overlaps heavily with supply chain attacks, where the malware doesn't need to find a vulnerability in your network if it can ride in through a dependency you trust.

AI-Generated and Polymorphic Malware

This is the category that didn't exist in any meaningful way in 2021. Threat actors are now using generative AI to write malware, generate phishing lures, and create polymorphic variants that change their code structure on every execution. Nearly 90% of new malware strains identified in 2026 are polymorphic, meaning signature-based detection alone will miss them. The Slopoly case demonstrated that LLM-generated malware is already appearing in live ransomware operations, and analysts expect this trend to accelerate as models become more capable and more accessible.

How Malware Gets Delivered in 2026

The delivery methods have evolved alongside the malware itself.

• AI-generated phishing is now the primary delivery vector for most malware campaigns. AI-crafted emails achieve higher click-through rates than human-written ones, at a fraction of the cost. 
• Supply chain compromise targets the software and services organizations already trust. Rather than attacking you directly, threat actors poison a library, scanner, or plugin that your team downloads as part of normal operations.
• QR code phishing (quishing) has emerged as a vector because QR codes are difficult to inspect before scanning. Submitting a suspicious QR code to a malware sandbox lets teams safely determine where it leads without exposing anyone to the payload.
• ClickFix social engineering tricks users into running malicious PowerShell commands to "fix" a fake browser error. This technique accounted for 12% of initial infections in 2025 and is a favored tactic of groups like Interlock.
• Malvertising and SEO poisoning inject malicious content into legitimate advertising networks or manipulate search results to direct victims to attacker-controlled pages. These blur the line between normal browsing and malware delivery.

What Effective Malware Detection Looks Like Now

Signature-based detection still catches known threats, but it can't keep pace with polymorphic and AI-generated variants. When malware changes its code structure on every execution, signature databases are always behind.

Effective detection in 2026 requires layering. Behavioral analysis observes what software actually does at runtime, catching malicious behavior even when the code signature is unknown. Malware sandboxing lets analysts safely detonate suspicious files and URLs in isolated environments, producing a verdict backed by evidence rather than heuristic guesswork. Threat intelligence feeds push updated indicators of compromise into blocking tools as new campaigns emerge, closing the gap between discovery and defense.

The common thread across all of these layers: detection alone produces "maybes." Turning those maybes into confident action requires validation, and validation at speed requires the right tooling. For a detailed breakdown of how this workflow operates in practice, see our guide on malware protection in 2026.

How ZeroFox Approaches Malware Detection

ZeroFox operates on a continuous cycle of Discover, Validate, Disrupt. For malware detection specifically, that means discovering malware campaigns, phishing kits, and attacker infrastructure across the external attack surface before they reach your environment. Analysts can pivot across 12 billion+ correlated signals to trace threats from initial indicator to full campaign picture.

The ZeroFox Malware Sandbox, built in partnership with PolySwarm, validates threats through on-platform detonation of files, URLs, hashes, and QR codes. Dual-engine analysis combines behavioral execution with static deconstruction, and results include extracted IOCs, MITRE ATT&CK mapping, and AI-powered summaries. Sandbox evidence then feeds directly into takedown and disruption workflows, connecting validation to action in a single platform.

Request a demo to see how ZeroFox detects and disrupts malware threats across the external attack surface.