Abstract: A method includes accessing a plurality of network sources by a crawler bank. The crawler bank includes a plurality of crawlers. Each crawler may be designated to specifically crawl at least one of the network sources. In some implementations, the method includes crawling each of the network sources to identify one or more featured content. In some implementations, the crawlers look to identify vulnerability reports on the network sources. In some implementations, crawlers look to identify vulnerability reports based on a predetermined set of rules. The predetermined set of rules may include a name of a product, a name of a vendor or manufacturer, a name and a version of a product, a product part number, etc. In some implementations, the method includes transmitting each of the identified featured content to the server. In such implementations, the crawlers transmit the identified vulnerability reports to the crawler bank on the server.

Abstract: Various implementations disclosed herein provide a method for detecting impact of the vulnerability by using a normalizer and correlator. In various implementations, the method includes: accessing a first set of data from a first data sources, calculating a risk level value for each of the first set of data based on a first set of rules, sorting the first set of data based on their risk level, accessing the sorted first set of data by a correlator, accessing, by the correlator, a second set of data from second data sources, correlating each of the sorted first set of data to at least a data of the second set of data based a second set of rules, and calculating a confidence score for each data of the sorted first set of data based on a third set of rules.

Abstract: Various implementations disclosed herein provide a method for detecting impact of the vulnerability by using a normalizer and correlator. In various implementations, the method includes: accessing a first set of data from a first data sources, calculating a risk level value for each of the first set of data based on a first set of rules, sorting the first set of data based on their risk level, accessing the sorted first set of data by a correlator, accessing, by the correlator, a second set of data from second data sources, correlating each of the sorted first set of data to at least a data of the second set of data based a second set of rules, and calculating a confidence score for each data of the sorted first set of data based on a third set of rules.

Abstract: Various implementations disclosed herein provide a method for vulnerability detection using a crawler bank. In various implementations, the method includes accessing a plurality of network sources by a crawler bank. In some embodiments, the crawler bank includes a plurality of crawlers. Each crawler may be designated to specifically crawl at least one of the network sources. In some implementations, the method includes crawling each of the network sources to identify one or more featured content. In some implementations, the crawlers look to identify vulnerability reports on the network sources. In some implementations, crawlers look to identify vulnerability reports based on a predetermined set of rules. The predetermined set of rules may include a name of a product, a name of a vendor or manufacturer, a name and a version of a product, a product part number, etc. In some implementations, the method includes transmitting each of the identified featured content to the server.

Abstract: A method and apparatus for configuring a user interface is disclosed. The method and apparatus allow for the determination of a function provided by the user interface using a skin. Such a skin includes information regarding an object, where the object represents an entity managed using the user interface.