Abstract: Methods and apparatuses are described in which unstructured computer text is analyzed for generation of customized digital documents. A server tokenizes and encodes historical user interactions and historical digital documents into multidimensional vectors. The server trains an interaction classification model using the multidimensional vectors as input to generate a classification for an input user interaction, and trains a language generation model using the multidimensional vectors as input to generate a customized digital document based upon an input user interaction. The server receives a new user interaction and encodes the new user interaction into a new multidimensional vector. The server executes the trained interaction classification model using the new vector as input to generate a digital document classification. The server executes the trained language generation model using the new vector and the classification as input to generate a customized digital document.

Abstract: An example embodiment may involve a remote network management platform including a computational instance hosting a particular application. The particular application may be based on a unit of program code, use one or more database tables, and define one or more user roles with respect to accessing the program code and the database tables. A scanner application may be configured to: receive, from a client device, a request to scan the particular application; retrieve the particular application; conduct a static security scan by applying a set of rules that define security vulnerabilities, where the rules take into account (i) relationships between the user roles and the unit of program code, and (ii) relationships between the user roles and the database table; and transmit, to the client device, a representation of a web page that contains observed security vulnerabilities of the particular application.

Abstract: Methods and apparatuses are described in which unstructured computer text is analyzed for generation of customized digital documents. A server tokenizes and encodes historical user interactions and historical digital documents into multidimensional vectors. The server trains an interaction classification model using the multidimensional vectors as input to generate a classification for an input user interaction, and trains a language generation model using the multidimensional vectors as input to generate a customized digital document based upon an input user interaction. The server receives a new user interaction and encodes the new user interaction into a new multidimensional vector. The server executes the trained interaction classification model using the new vector as input to generate a digital document classification. The server executes the trained language generation model using the new vector and the classification as input to generate a customized digital document.

Abstract: An example embodiment may involve a remote network management platform including a computational instance hosting a particular application. The particular application may be based on a unit of program code, use one or more database tables, and define one or more user roles with respect to accessing the program code and the database tables. A scanner application may be configured to: receive, from a client device, a request to scan the particular application; retrieve the particular application; conduct a static security scan by applying a set of rules that define security vulnerabilities, where the rules take into account (i) relationships between the user roles and the unit of program code, and (ii) relationships between the user roles and the database table; and transmit, to the client device, a representation of a web page that contains observed security vulnerabilities of the particular application.

Abstract: An example embodiment may involve a remote network management platform including a computational instance hosting a particular application. The particular application may be based on a unit of program code, use one or more database tables, and define one or more user roles with respect to accessing the program code and the database tables. A scanner application may be configured to: receive, from a client device, a request to scan the particular application; retrieve the particular application; conduct a static security scan by applying a set of rules that define security vulnerabilities, where the rules take into account (i) relationships between the user roles and the unit of program code, and (ii) relationships between the user roles and the database table; and transmit, to the client device, a representation of a web page that contains observed security vulnerabilities of the particular application.

Abstract: An example embodiment may involve a remote network management platform including a computational instance hosting a particular application. The particular application may be based on a unit of program code, use one or more database tables, and define one or more user roles with respect to accessing the program code and the database tables. A scanner application may be configured to: receive, from a client device, a request to scan the particular application; retrieve the particular application; conduct a static security scan by applying a set of rules that define security vulnerabilities, where the rules take into account (i) relationships between the user roles and the unit of program code, and (ii) relationships between the user roles and the database table; and transmit, to the client device, a representation of a web page that contains observed security vulnerabilities of the particular application.