Abstract: Systems, methods, and storage media for determining the probability of cyber risk-related loss within one or more computing systems composed of computing elements are disclosed. Exemplary implementations may: assess vulnerability by determining an exposure window for a computing element based on the number of discrete times within a given time frame where the computing element is in a vulnerable state; determine a frequency of contact of the computing element with threat actors; normalize the exposure window and the frequency of contact; calculate a threat event frequency by dividing the normalized exposure window by the normalized frequency of contact; and repeat the steps for multiple elements. When combined with liability data that describes the loss magnitude implications of these events ,organizations can prioritize the elements based on loss exposure and take action to prevent loss exposure.

Abstract: Systems, methods, and storage media for determining the probability of cyber risk-related loss within one or more computing systems composed of computing elements are disclosed. Exemplary implementations may: assess vulnerability by determining an exposure window for a computing element based on the number of discrete times within a given time frame where the computing element is in a vulnerable state; determine a frequency of contact of the computing element with threat actors; normalize the exposure window and the frequency of contact; calculate a threat event frequency by dividing the normalized exposure window by the normalized frequency of contact; and repeat the steps for multiple elements. When combined with liability data that describes the loss magnitude implications of these events, organizations can prioritize the elements based on loss exposure and take action to prevent loss exposure.

Abstract: Systems, methods, and storage media for determining the probability of cyber risk-related loss within one or more computing systems composed of computing elements are disclosed. Exemplary implementations may: assess vulnerability by determining an exposure window for a computing element based on the number of discrete times within a given time frame where the computing element is in a vulnerable state; determine a frequency of contact of the computing element with threat actors; normalize the exposure window and the frequency of contact; calculate a threat event frequency by dividing the normalized exposure window by the normalized frequency of contact; and repeat the steps for multiple elements. When combined with liability data that describes the loss magnitude implications of these events, organizations can prioritize the elements based on loss exposure and take action to prevent loss exposure.