Abstract: An improved computing tool performs an improved computing tool function to identify sensitive data risks in cloud-based deployments. A knowledge graph is built based on data schema information for a cloud-based computing environment, a set of parsed infrastructure logs, and a set of captured application queries. A set of sensitive flows in the knowledge graph are identified representing paths from a sensitive data element to an endpoint in the knowledge graph. The set of sensitive flows are scored based on a scoring algorithm and an alert is issued to an administrator in response to a score of a sensitive flow within the set of sensitive flows exceeding a threshold.

Abstract: Mechanisms are provided in a cloud-based computing environment for identifying sensitive data risks in cloud-based deployments. The mechanisms build a knowledge graph based on data schema information for a cloud-based computing environment, a set of parsed infrastructure logs, and a set of captured application queries. The mechanisms identify a set of sensitive flows in the knowledge graph representing paths from a sensitive data element to an endpoint in the knowledge graph. The mechanisms score the set of sensitive flows based on a scoring algorithm and issue an alert to an administrator in response to a score of a sensitive flow within the set of sensitive flows exceeding a threshold.

Abstract: Mechanisms are provided in a cloud-based computing environment for identifying sensitive data risks in cloud-based deployments. The mechanisms build a knowledge graph based on data schema information for a cloud-based computing environment, a set of parsed infrastructure logs, and a set of captured application queries. The mechanisms identify a set of sensitive flows in the knowledge graph representing paths from a sensitive data element to an endpoint in the knowledge graph. The mechanisms score the set of sensitive flows based on a scoring algorithm and issue an alert to an administrator in response to a score of a sensitive flow within the set of sensitive flows exceeding a threshold.

Abstract: Log(s) of IT events are accessed in a distributed system that includes a distributed application. The distributed system includes multiple data objects. The distributed application uses, processes, or otherwise accesses one or more of data objects. The IT events concern the distributed application and concern accesses by the distributed application to the data object(s). The IT events are correlated with a selected set of the data objects. Risks are estimated to the selected set of data objects based on the information technology events. Estimating risks uses at least ranks of compliance rules as these rules apply to the data objects in the system, and vulnerability scores of systems corresponding to the set of data objects and information technology events. Information is output that allows a user to determine the estimated risks for the selected set of data objects. Techniques for determining ranks of compliance rules are also disclosed.