By Marco Balduzzi (Technical Research Lead, Forward-Looking Threat Research Team), Roel Reyes (Senior Threat Researcher, Forward-Looking Threat Research Team), Jessica Balaquit (Threat Researcher, ML/AI Research), Ryan Flores (Director of Technology Research, Threat Research), Benjamin Zigh (Director, Threat Research Insights)
Key takeaways
- A study by TrendAI™ Research confirms that endpoint risk is not random; user behavior strongly influences it. Behaviors such as installing large numbers of applications, visiting gambling sites, or using devices primarily at night significantly increase exposure to specific malware types.
- The analysis of high-risk endpoints identified in this multi-engine study revealed that certain behaviors directly influence exposure to different malware classes, supporting the assumption that cybercriminals tailor campaigns to target specific victims and business models.
- By combining behavioral analytics with advanced statistical modeling, the research establishes a clearer, explainable way to anticipate malware exposure — enabling organizations to proactively pinpoint higher‑risk users and machines and strengthen…
