Multi-computer system for performing vulnerability analysis and alert generation

A method, comprising:

• receiving, by a computing platform, the computing platform having at least one processor, and memory, and for a first software product, software bill of materials data, the software bill of materials data including data of the first software product;
• extracting, by the at least one processor and from the software bill of materials data, software attributes for the first software product, the software attributes for the first software product including at least an author of the first software product;
• receiving, by the at least one processor and from one or more sources, author data associated with an author of the first software product;
• executing, by the at least one processor, a natural language processing function on the author data to determine one or more author attributes;
• executing, by the at least one processor, a machine learning model to determine a confidence score associated with the first software product, wherein the machine learning model uses as inputs the software attributes of the first software product and the determined one or more author attributes;
• generating, by the at least one processor and based on the confidence score associated with the software product, an alert including at least the confidence score;
• and
• transmitting, by the at least one processor and to an enterprise organization computing device, the generated alert, wherein transmitting the alert causes the alert to be displayed on a display of the enterprise organization computing device.

One or more non-transitory computer-readable media storing instructions that, when executed by a computing platform comprising at least one processor, memory, and a communication interface, cause the computing platform to:

• receive, for a first software product, software bill of materials data, the software bill of materials data including data of the first software product;
• extract, from the software bill of materials data, software attributes for the first software product, the software attributes for the first software product including at least an author of the first software product;
• receive, from one or more sources, author data associated with an author of the first software product;
• execute a natural language processing function on the author data to determine one or more author attributes;
• execute a machine learning model to determine a confidence score associated with the first software product, wherein the machine learning model uses as inputs the software attributes of the first software product and the determined one or more author attributes;
• generate, based on the confidence score associated with the software product, an alert including at least the confidence score;
• and
• transmit, to an enterprise organization computing device, the generated alert, wherein transmitting the alert causes the alert to be displayed on a display of the enterprise organization computing device.