Automatic identification of change requests to address information technology vulnerabilities

A system, comprising:

• one or more processors;
• and
• a memory coupled to the one or more processors, wherein the memory is configured to provide the one or more processors with instructions which when executed cause the one or more processors to:
• train a machine learning model based at least on previous change requests, wherein each of the previous change requests are associated with a controlled management of a lifecycle of a change to an information technology environment;
• identify a security vulnerability of the information technology environment;
• determine using the trained machine learning model for the security vulnerability a corresponding match score for each of a plurality of pending change requests;
• and
• receive an indication of whether a resolution specification for the security vulnerability is to be linked with one of the plurality of pending change requests selected based on a factor associated with its corresponding match score.

A computer program product, the computer program product being embodied in a non-transitory computer readable storage medium and comprising computer instructions for:

• training a machine learning model based at least on previous change requests, wherein each of the previous change requests are associated with a controlled management of a lifecycle of a change to an information technology environment;
• identifying a security vulnerability of the information technology environment;
• using the trained machine learning models, determining for the security vulnerability a corresponding match score for each of a plurality of pending change requests;
• and
• receiving an indication of whether a resolution specification for the security vulnerability is to be linked with one of the plurality of pending change requests selected based on a factor associated with its corresponding match score.