Bending the Curve: Operational Cyber Epidemiology for Ransomware

Ransomware is often treated as a detection problem, but the most disruptive incidents behave more like outbreaks. A single foothold can spread through identities, administrative tools, and shared services while responders make time-critical decisions with incomplete visibility. This paper presents an operational cyber epidemiology framework that adapts the Susceptible-Exposed-Infectious-Removed (SEIR) model to ransomware incident management. In this ontology, Exposed denotes latent compromise and staging, including the dwell period before confirmed secondary compromise, while Infectious denotes active lateral propagation. Drawing on ISO 5477:2023 guidance for public health emergency preparedness and response information management and the 2025 UNDRR-ISC Hazard Information Profiles, the framework defines interoperable ransomware case definitions and Essential Elements of Information for cross-incident comparison. Basic and effective reproduction numbers, R0 and Re, are used as directional, near-real-time decision aids for security operations centers. Propagation state is separated from observation status to avoid confusing spread dynamics with detection capability. Publicly reported incidents, including WannaCry, NotPetya, SolarWinds, and MGM and Caesars, illustrate how outbreak-style measures can support earlier isolation, credential containment, and restoration sequencing. The paper also derives practical protection-threshold heuristics aimed at reducing Re below 1 and provides a tool-agnostic playbook card linking operational information to explicit action triggers. The primary contribution is a shared language that connects technical telemetry to containment decisions under resource constraints.