Abstract: The present disclosure generally relates to web page analysis, and more particularly to a classification system for web pages. The classification system may classify a web page as malicious based upon one or more signatures generated for the web page. For example, the classification system may compare one or more signatures generated for a first web page to one or more signatures generated for a second web page, where the first web page and the second web page are the same web page at different times or different web pages. Based upon a similarity of the signatures, the classification system may output whether the first web page is malicious. For another example, the classification system may include a classification model that is trained based upon one or more signatures for one or more classified web pages. The classification model may output whether the web page is malicious.

Abstract: An inventory of Internet-facing assets related to a username within a social media site is generated using network data gathered from network data sources. Using data sources of known threats, such as malware, phishing attempts, scam pages, blacklisted sites, and so on, a network analytic system generates analytical information about components that are owned, managed, and/or controlled by a target entity. A measure of identity threat is generated based on a classification model using the analytical information.

Abstract: An inventory of Internet-facing assets related to a username within a social media site is generated using network data gathered from network data sources. Using data sources of known threats, such as malware, phishing attempts, scam pages, blacklisted sites, and so on, a network analytic system generates analytical information about components that are owned, managed, and/or controlled by a target entity. A measure of identity threat is generated based on a classification model using the analytical information.

Abstract: An inventory of Internet-facing assets related to a target domain is generated using network data gathered from network data sources. Using data sources of known threats, such as malware, phishing attempts, scam pages, blacklisted sites, and so on, a network analytic system generates analytical information about domains, sub-domains, and components that are owned, managed, and/or controlled by a target entity. A measure of domain identity threat is generated based on a classification model using the analytical information.

Abstract: The present disclosure generally relates to web page analysis, and more particularly to a classification system for web pages. The classification system may classify a web page as malicious based upon one or more signatures generated for the web page. For example, the classification system may compare one or more signatures generated for a first web page to one or more signatures generated for a second web page, where the first web page and the second web page are the same web page at different times or different web pages. Based upon a similarity of the signatures, the classification system may output whether the first web page is malicious. For another example, the classification system may include a classification model that is trained based upon one or more signatures for one or more classified web pages. The classification model may output whether the web page is malicious.