System and method for electronic message data analysis and neutralization via machine learning

A computer program product for electronic message data analysis and neutralization via machine learning, the computer program product comprising a non-transitory computer-readable medium comprising code causing an apparatus to:

• receive message data at a gateway server;
• receive the message data in a categorization engine, the categorization engine comprising a machine learning model;
• score, using the categorization engine, the message data based on contents of the message data;
• categorize, using the machine learning model, the message data in a category of malicious or non-malicious,
• wherein upon a condition where the message data is categorized as malicious, the categorization engine alters one or more hyperlinks in the message data such that a hyperlink of the one or more hyperlinks, upon interaction therewith, presents an indicator as to a reasoning that the message data was categorized as malicious, wherein the reasoning is an output from the machine learning model;
• apply metadata, at the gateway server, to the message data based on the category;
• transmit, upon receiving a transmission request, the message data to an endpoint device;
• and
• present the message data at the endpoint device based on the category.

A method for electronic message data analysis and neutralization via machine learning, the method comprising:

• receiving message data at a gateway server;
• receiving the message data in a categorization engine, the categorization engine comprising a machine learning model;
• scoring, using the categorization engine, the message data based on contents of the message data;
• categorizing, using the machine learning model, the message data in a category of malicious or non-malicious,
• wherein upon a condition where the message data is categorized as malicious, the categorization engine alters one or more hyperlinks in the message data such that a hyperlink of the one or more hyperlinks, upon interaction therewith, presents an indicator as to a reasoning that the message data was categorized as malicious, wherein the reasoning is an output from the machine learning model;
• applying metadata, at the gateway server, to the message data based on the category;
• transmitting, upon receiving a transmission request, the message data to an endpoint device;
• and
• presenting the message data at the endpoint device based on the category.