Machine learning-based systems and methods of using urls and html encodings for detecting phishing websites

Abstract

Disclosed is classifying a URL and a content page accessed via the URL as phishing or not. URL embedder extracts characters in a predetermined set from the URL to produce a character string trained using ground truth classification of the URL, producing a URL embedding. HTML parser accesses content at the URL and extracts HTML tokens from the content page. Further, HTML encoder, trained on HTML tokens extracted from content pages at example URLs, each example URL accompanied by a ground truth image captured from the content page accessed via the example URL, produces an HTML encoding of the tokens extracted from the page. Also, phishing classifier layers, trained on the URL embedding and the HTML encoding of example URLs, processes a concatenated input of the URL embedding and the HTML encoding to produce a likelihood score that the URL and content accessed via the URL presents a phishing risk.