Trellix ATLAS vs. Blue Hexagon

Customers obtain a unique insight into the various malicious files, domains, and IP addresses detected globally. The Advanced Threat Landscape Analysis System (ATLAS) aggregates information from numerous Trellix sources to provide the latest worldwide threats, enriched with data regarding industry sectors and geographic locations. By linking these threats with campaign information and integrating findings from Trellix’s Advanced Research Center (ARC) and Threat Intelligence Group (TIG), alongside publicly available resources, ATLAS delivers a concentrated view of campaigns that includes elements such as events, timelines, threat actors, and indicators of compromise (IOCs). This innovative system equips users with an exceptional global perspective on malicious threats identified by Trellix, offering geospatial situational awareness. It effectively leverages telemetry data collected from various regions to underline both present and future threats, emphasizing those that stand out based on diverse criteria like type, industry sector, and geographic area. Additionally, this thorough methodology guarantees that clients stay updated on the dynamic threat landscape, thereby enhancing their ability to safeguard against potential cyber threats. As a result, users can make more informed decisions regarding their cybersecurity strategies.

Our state-of-the-art real-time deep learning system is designed to achieve unmatched levels of detection speed, efficiency, and extensive coverage in the realm of cyber defense. We carefully train our neural networks utilizing a diverse spectrum of global threat intelligence sourced from various channels, including threat databases, the dark web, our own systems, and collaborative partnerships. Much like how layers in neural networks can identify images, our innovative neural network architecture adeptly identifies threats in both payloads and headers. Blue Hexagon Labs conducts thorough evaluations of our models' accuracy in the face of emerging threats in real-time, guaranteeing their reliability and precision. Our technology excels at detecting a wide array of cyber threats, encompassing file-based and fileless malware, exploits, command and control communications, and malicious domains across different operating systems such as Windows, Android, and Linux. Deep learning, a specialized field within machine learning, utilizes complex, multi-layered artificial neural networks to proficiently learn and represent data. As the cyber threat landscape continuously evolves, our platform is regularly updated to tackle new challenges and uphold its leading-edge capabilities. This ongoing commitment to innovation enables us to stay ahead of potential threats and safeguard digital environments effectively.