Password semantic analysis pipeline

A computer-implemented method, comprising:

• performing, by one or more hardware processors with associated memory that implements a password semantic analysis pipeline system:
• implementing a password semantic analysis pipeline model trained according to a machine learning technique, wherein
• the password semantic analysis pipeline model is trained to determine, based on given characteristics data of a given network environment, whether each of a plurality of tokens that are chunked portions of a data structure input as a password in an application is a known syntax type or a recognized entity;
• generating, using the password semantic analysis pipeline model, a password strength score, wherein
• the password strength score is a combination of a confidence score determined for each of the plurality of tokens and a weight factor assigned to the known syntax type or the recognized entity;
• applying the password strength score to the data structure input as the password is entered in the application;
• and
• providing an output to the application indicating whether the data structure input as the password is acceptable or unacceptable for continued access to the application, wherein
• the password semantic analysis pipeline system is configured to:
• process the data structure using a Natural Language Processing (NLP) methodology to determine whether the token is a verb or a noun,
• adjust the weight factor assigned to the known syntax type or the recognized entity,
• implement a mapping of special characters to regular characters, or
• perform one or more remediation actions if the output indicates that the data structure input as the password exceeds a risk threshold.

One or more non-transitory computer-accessible storage media storing program instructions that when executed on or across one or more processors implement at least a portion of a password semantic analysis pipeline system and cause the password semantic analysis pipeline system to:

• implement a password semantic analysis pipeline model trained according to a machine learning technique, wherein
• the password semantic analysis pipeline model is trained to determine, based on given characteristics data of a given network environment, whether each of a plurality of tokens that are chunked portions of a data structure input as a password in an application is a known syntax type or a recognized entity;
• generate, using the password semantic analysis pipeline model, a password strength score, wherein
• the password strength score is a combination of a confidence score determined for each of the plurality of tokens and a weight factor assigned to the known syntax type or the recognized entity;
• apply the password strength score to the data structure input as the password is entered in the application;
• and
• provide an output to the application indicating whether the data structure input as the password is acceptable or unacceptable for continued access to the application, wherein
• the password semantic analysis pipeline system is configured to:
• process the data structure using a Natural Language Processing (NLP) methodology to determine whether the token is a verb or a noun,
• adjust the weight factor assigned to the known syntax type or the recognized entity,
• implement a mapping of special characters to regular characters, or
• perform one or more remediation actions if the output indicates that the data structure input as the password exceeds a risk threshold.