Data discovery and classification using sampling-based scanning techniques

A computing system comprising:

• at least one processor;
• and
• memory storing instructions executable by the at least one processor, wherein the instructions, when executed, cause the computing system to:
• select a first sampling criterion representing a first distribution of data objects in a data store;
• select a second sampling criterion representing a second distribution of data objects in the data store;
• deploy one or more scanners configured to select a set of the data objects, in the data store that satisfy both the first sampling criterion and the second sampling criterion;
• obtain a scanner result, generated by the one or more scanners, that represents detected instances, in the set of the data objects, of one or more data patterns representing a target data type;
• generate a classification result based on detected instances of the one or more data patterns;
• and
• perform a computing action based on the classification result.

A computer-readable media having computer-readable instructions stored thereon, wherein the computer-readable instructions, when executed by a computer, cause the computer to:

• identify a subject vulnerability signature representing an access path to target data in a computing environment;
• identify one or more characteristics associated with the target data;
• generate a sampling criterion based on the one or more characteristics of the target data;
• deploy one or more scanners configured to select a set of data objects in a data store based on the sampling criterion;
• generate a classification result based on an analysis of data objects, in the set of data objects, relative to the target data, the classification result representing a classification of the data store as having correspondence to the subject vulnerability signature;
• and
• perform a computing action based on the classification result.