Detecting sensitive information in records using context and decoys

A system for detecting sensitive information, comprising:

• one or more processors;
• and
• a memory comprising instructions that, when executed by the one or more processors, cause the system to:
• determine a first likelihood that a record contains at least a given type of sensitive information using a first detection technique comprising:
• providing one or more inputs to a machine learning model based on the record;
• and
• receiving the first likelihood as an output from the machine learning model based on the one or more inputs;
• determine a second likelihood that the record contains at least the given type of sensitive information using a second detection technique comprising a search of the record;
• apply a policy to determine whether the record contains sensitive information based on the first likelihood and the second likelihood, wherein the policy states that the second detection technique is used when the first likelihood determined using the first detection technique is above a threshold likelihood;
• perform one or more actions based on whether the record contains sensitive information;
• receive a ground truth label indicating whether the record contains sensitive information;
• and
• revise the policy based on the ground truth label.