Netskope, Inc.

Najmeh Miramirkhani

Zhi Xu

Yihua Liao

Ari Azarafrooz

Disclosed is phishing classifier that classifies a URL and content page accessed via the URL as phishing or not is disclosed, with URL feature hasher that parses and hashes the URL to produce feature hashes, and headless browser to access and internally render a content page at the URL, extract HTML tokens, and capture an image of the rendering. Also disclosed are an HTML encoder, trained on HTML tokens extracted from pages at URLs, encoded, then decoded to reproduce images captured from rendering, that produces an HTML encoding of the tokens extracted, and an image embedder, pretrained on images, that produces an image embedding of the image captured. Further, phishing classifier layers, trained on the feature hashes, the HTML encoding, and the image embedding, process the URL feature hashes, HTML encoding and image embeddings to produce a likelihood score that the URL and the page accessed presents a phishing risk.

Detecting phishing websites via a machine learning-based system using URL feature hashes, HTML encodings and embedded images of content pages

Disclosed is classifying a URL and a 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 page. Further, HTML encoder, trained on HTML tokens extracted from pages at example URLs, each example URL accompanied by a ground truth image captured from the page accessed via the example URL, produces an HTML encoding of the extracted tokens. 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 score of a phishing risk.

Machine learning-based system for detecting phishing websites using the URLS, word encodings and images of content pages

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.

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Santa Clara, CA, United States of America

Najmeh Miramirkhani