Abstract: The disclosure is directed towards the detection of supply chain-related security threats to software applications. One method includes identifying differences between updated source code and previous source. The updated source code corresponds to an updated version of an application. The previous source code corresponds to a previous version of the application. A risk score is determined for the updated version. The risk score is based on a machine learning (ML) risk model. The ML risk model analyzes the differences between the updated source code and the previous source code. A value of the risk score corresponds to potential security threats that are associated with the updated version. The potential security threats are not associated with the previous version of the application. The risk score is provided to interested parties.

Abstract: One method embodiment includes receiving input creating a data distribution restriction implemented to restrict distribution of data by publisher nodes located in at least one geographic or political area to subscriber nodes outside of the at least one geographic or political area. The method then queries a subscription repository storing data defining subscriptions to publisher node data events on publisher nodes located in the at least one geographic or political area to identify existing subscriptions to data events about the particular data by subscriber nodes located outside of the at least one geographic or political area. The method may then output the query results identifying existing subscriber node subscriptions contrary to the new or newly modified data distribution restriction. The received input may then be stored in a database such that subsequent changes are conditionally limited by the new or newly modified data distribution restriction.

Abstract: Methods, systems, and computer storage media provide a privacy compliance notification indicating a database's level of compliance with a privacy policy after restoring the database to the database's backup copy. The database is associated with a database management engine. The database supports privacy-based first-class data entities. The privacy-based first-class data entities are database entities having privacy system-level metadata properties associated with data operations in a database language syntax. The privacy compliance notification may be generated based on determining whether a privacy database operation associated with a database journal and a privacy journal has been executed on a database since the database was restored to a backup copy of the database.

Abstract: The disclosure is directed towards the detection of supply chain-related security threats to software applications. One method includes identifying differences between updated source code and previous source. The updated source code corresponds to an updated version of an application. The previous source code corresponds to a previous version of the application. A risk score is determined for the updated version. The risk score is based on a machine learning (ML) risk model. The ML risk model analyzes the differences between the updated source code and the previous source code. A value of the risk score corresponds to potential security threats that are associated with the updated version. The potential security threats are not associated with the previous version of the application. The risk score is provided to interested parties.