Ransomware Detection With Real-Time Data

This report outlines the rapid evolution of ransomware—driven by RaaS models, identity-based intrusions, and malware-free techniques—and argues that traditional detection is insufficient. It advocates for timely, relevant data integrated into threat intelligence, AI/ML, behavioral analytics, automation, and attack surface management to enable earlier detection, faster response, and reduced dwell time. The paper highlights key challenges (e.g., polymorphic/fileless attacks, encrypted traffic, credential misuse, and alert fatigue) and presents Recorded Future’s intelligence-led capabilities for proactive ransomware detection, mitigation, and incident response.