Phishing Intelligence Using the Simple Set Comparison Tool

Phishing websites, phish, attempt to deceive users into exposing their passwords, user IDs, and other sensitive information by imitating legitimate websites, such as banks, product vendors, and service providers. Phishing investigators need fast automated tools to analyze the volume of phishing attacks seen today. In this paper, we present the Simple Set Comparison tool. The Simple Set Comparison tool is a fast automated tool that groups phish by imitated brand allowing phishing investigators to quickly identify and focus on phish targeting a particular brand. The Simple Set Comparison tool is evaluated against a traditional clustering algorithm over a month\u27s worth of phishing data, 19,825 confirmed phish. The results show clusters of comparable quality, but created more than 37 times faster than the traditional clustering algorithm. Keywords: phishing, phish kits, phishing investigation, data mining, parallel processin

DeltaPhish: Detecting Phishing Webpages in Compromised Websites

The large-scale deployment of modern phishing attacks relies on the automatic exploitation of vulnerable websites in the wild, to maximize profit while hindering attack traceability, detection and blacklisting. To the best of our knowledge, this is the first work that specifically leverages this adversarial behavior for detection purposes. We show that phishing webpages can be accurately detected by highlighting HTML code and visual differences with respect to other (legitimate) pages hosted within a compromised website. Our system, named DeltaPhish, can be installed as part of a web application firewall, to detect the presence of anomalous content on a website after compromise, and eventually prevent access to it. DeltaPhish is also robust against adversarial attempts in which the HTML code of the phishing page is carefully manipulated to evade detection. We empirically evaluate it on more than 5,500 webpages collected in the wild from compromised websites, showing that it is capable of detecting more than 99% of phishing webpages, while only misclassifying less than 1% of legitimate pages. We further show that the detection rate remains higher than 70% even under very sophisticated attacks carefully designed to evade our system.Comment: Preprint version of the work accepted at ESORICS 201