Abstract: A method implements input validation using mathematical expressions. The method includes receiving an input string, scanning the input string to locate a hit string matching a hit expression from a validation package, and converting the hit string to a list of values corresponding to characters from the hit string. The method further includes validating the hit string by evaluating a validation expression from the validation package using the list of values to generate a validation result and returning the validation result.

Abstract: A method includes receiving event strings from source code repositories, creating, for the source code repositories, digests of keywords, receiving log strings, and aggregating the log strings into a log group. The method further includes comparing the digests to the log group to generate scores, whereby the scores correlate the digests to the log group. The method further includes selecting a source code repository from the source code repositories according to the scores, and associating the log group to a service corresponding to the source code repository, where the source code repository corresponds to the digest with a highest score.

Abstract: A method includes receiving event strings from source code repositories, creating, for the source code repositories, digests of keywords, receiving log strings, and aggregating the log strings into a log group. The method further includes comparing the digests to the log group to generate scores, whereby the scores correlate the digests to the log group. The method further includes selecting a source code repository from the source code repositories according to the scores, and associating the log group to a service corresponding to the source code repository, where the source code repository corresponds to the digest with a highest score.

Abstract: Described herein are example implementations for the automatic detection and handling of personal identifiable information (PII) in electronic records. In some aspects, a system receives one or more computer readable logs of information for one or more computer services, with each log including a string of characters. The system performs one or more string search algorithm based operations on the entirety of the one or more strings of the one or more computer readable logs to identify a range of the one or more strings to be searched for PII that is less than the entirety of the one or more strings. The system also performs one or more regular expression algorithm based operations on the range of the one or more strings to identify one or more instances of PII. The system generates and outputs an indication of the one or more instances of the PII that are identified.

Abstract: Aspects of the present disclosure provide techniques for detecting sensitive information. Embodiments include determining a first likelihood that a record contains at least a given type of sensitive information using a first detection technique that involves 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. Embodiments include determining 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. Embodiments include applying a policy to determine whether the record contains sensitive information based on the first likelihood and the second likelihood. Embodiments include performing one or more actions based on whether the record contains sensitive information.