Abstract: The present disclosure describes systems and methods for using a model for a predetermined role for simulated phishing campaigns. A campaign controller communicates simulated phishing communications to one or more devices of a user using a model that the campaign controller selects from a plurality of models in a database that have been established for predetermined roles of a company. The model is selected based on one or more attributes of the user that are identified by the campaign controller. The campaign controller identifies one or more attributes of each user of a plurality of users for the simulated phishing campaign, and the campaign controller selects a respective model for each user based on the attributes of each user, wherein the models are not all the same for all of the users.

Abstract: Systems and methods, disclosed herein, of a campaign controller that stores information to a database about execution of multiple simulated phishing campaigns for multiple users, where each of the simulated phishing campaigns use one or more models for communicating simulated phishing communications. Based on this information, the campaign controller may determine a rate of success of the model, in causing a user to interact with a link in one of the simulated phishing campaigns, and may display the model's rate of success via a user interface.

Abstract: Methods and systems are described in which a system provides a user interface to confirm whether to review or take an action associated with an untrusted email. A driver on a device monitors the startup of any processes. Responsive to monitoring, the driver detects an application process that was created that indicates than an application was launched, and notifies a user console about the creation of the application process. The user console determines if the application process is of significance, if so, it injects a monitor library into the process. Once injected into the process, the monitor library detects if the application process receives an action of a user to access a domain that is not identified as trusted. The monitor library notifies the user console of the user's URL-access request.

Abstract: Embodiments disclosed describe a security awareness system may adaptively learn the best design of a simulated phishing campaign to get a user to perform the requested actions, such as clicking a hyperlink or opening a file. In some implementations, the system may adapt an ongoing campaign based on user's responses to messages in the campaign, along with the system's learned awareness. The learning process implemented by the security awareness system can be trained by observing the behavior of other users in the same company, other users in the same industry, other users that share similar attributes, all other users of the system, or users that have user attributes that match criteria set by the system, or that match attributes of a subset of other users in the system.

Abstract: The present disclose describes systems and methods for creating a simulated phishing campaign for a user based on at least a history of the user with respect to simulated phishing campaigns. A database may be configured to store simulated phishing campaign history of a user, the simulated phishing campaign history comprising information on events associated with the user during one or more previous simulated phishing campaigns, A campaign controller may identify the simulated phishing campaign history of the user from the database, determine based at least on the simulated phishing campaign history of the user, a model from a plurality of models for creating a simulated phishing campaign directed to the user; and create, responsive to the determination, the simulated phishing campaign using the model.

Abstract: Embodiments disclosed describe a security awareness system may adaptively learn the best design of a simulated phishing campaign to get a user to perform the requested actions, such as clicking a hyperlink or opening a file. In some implementations, the system may adapt an ongoing campaign based on user's responses to messages in the campaign, along with the system's learned awareness. The learning process implemented by the security awareness system can be trained by observing the behavior of other users in the same company, other users in the same industry, other users that share similar attributes, all other users of the system, or users that have user attributes that match criteria set by the system, or that match attributes of a subset of other users in the system.

Abstract: The present disclosure describes systems and methods for using a template for a simulated phishing campaign, A database includes a plurality of templates for simulated phishing campaigns, each template of the plurality of templates identifying a list of a plurality of types of simulated phishing communications and at least a portion of content for the simulated phishing communications. A campaign controller selects a template from the plurality of templates for a simulated phishing campaign directed to a user of a plurality of users; and communicates, to one or more devices of the user a first type of simulated phishing communication of the plurality of types of simulated phishing communications with at least the portion of content identified by the template.

Abstract: A system and method is described that sends multiple simulated phishing emails, text messages, and/or phone calls (e.g., via VoIP) varying the quantity, frequency, type, sophistication, and combination using machine learning algorithms or other forms of artificial intelligence. In some implementations, some or all messages (email, text messages, VoIP calls) in a campaign after the first simulated phishing email, text message, or call may be used to direct the user to open the first simulated phishing email or text message, or to open the latest simulated phishing email or text message. In some implementations, simulated phishing emails, text messages, or phone calls of a campaign may be intended to lure the user to perform a different requested action, such as selecting a hyperlink in an email or text message, or returning a voice call.

Abstract: A method, electronic device and computer program product for real-time detection of malicious software (“malware”) are provided. In particular, execution of a suspicious software application attempting to execute on a user's device may be emulated in a virtual operating system environment in order to observe the behavior characteristics of the suspicious application. If after observing the behavior of the suspicious application in the virtual environment, it is determined that the application is malicious, the application may not be permitted to execute on the user's actual device. The suspicious application may be identified as malicious if an isolated data string of the application matches a “blacklisted” data string, a certain behavior of the application matches a behavior that is known to be malicious, and/or the overall behavior of the application is substantially the same or similar to a known family of malware.