Determining a risk probability of a url using machine learning of url segments

One or more non-transitory computer-readable storage media storing instructions which, when executed by one or more hardware processors, cause performance of a method comprising:

• normalizing a URL to yield a normalized URL;
• segmenting the normalized URL into two or more segments;
• receiving at least one probability value from a machine learning model, wherein the wherein the machine learning model is trained to provide an indication of risk associated with the received URL based at least in part on the two or more segments;
• and
• performing a security action based at least in part on the at least one probability value.

A system, the system comprising:

• a processing resource;
• a non-transitory computer-readable medium communicably coupled to the processing resource and having instructions stored therein which, when executed by the one or more hardware processors, causes the system to:
• normalize a URL to yield a normalized URL;
• segment the normalized URL into two or more segments;
• receive at least one probability value from a machine learning model, wherein the wherein the machine learning model is trained to provide an indication of risk associated with the received URL based at least in part on the two or more segments;
• and
• perform a security action based at least in part on the at least one probability value.