1. A computer-implemented method for assessing cybersecurity training needs, comprising: by a sensor, sensing data corresponding to at least one action performed by a user with respect to a user computing device; and by a computer system comprising a processor, executing computer-readable programming instructions that cause the computer system to: access a data storage device that stores a training needs model, map the sensed data to the training needs model to determine whether the sensed data corresponds to a pattern associated with a threat scenario in the training needs model, in response to determining that the sensed data corresponds to a pattern associated with a threat scenario in the training needs model, identify a cybersecurity threat scenario for which the user is at risk, and use the training needs model to estimate susceptibility of the user to the cybersecurity threat scenario for which the user is at risk.
1. A computer-implemented method for assessing cybersecurity training needs, comprising: by a sensor, sensing data corresponding to at least one action performed by a user with respect to a user computing device; and by a computer system comprising a processor, executing computer-readable programming instructions that cause the computer system to: access a data storage device that stores a training needs model, map the sensed data to the training needs model to determine whether the sensed data corresponds to a pattern associated with a threat scenario in the training needs model, in response to determining that the sensed data corresponds to a pattern associated with a threat scenario in the training needs model, identify a cybersecurity threat scenario for which the user is at risk, and use the training needs model to estimate susceptibility of the user to the cybersecurity threat scenario for which the user is at risk. 15. The method of claim 1 , wherein: the sensed data comprises or more of the following additional sensed data types: files in a directory of downloaded files, location data, data from a password vulnerability sensor indicating how often the user changes a password or the strength of the password, data from a social networking sensor that crawls social networking sites and estimates a level of social networking activities in which the user engages, data from a dangerous program sensor that inspects the code of software on one or more electronic devices operated by the user, incoming and outgoing data flows from the user computing device, or behavioral characteristics associated with software running on the user computing device; and the method also comprises mapping the one or more additional sensed data types to the training needs model when determining whether the sensed data corresponds to a pattern associated with a threat scenario in the training needs model.