Active Credential Leakage for Observing Web-Based Attack Cycle

Abstract

A user who accesses a compromised website is usually redirected to an adversary’s website and forced to download malware. Additionally, the adversary steals the user’s credentials by using information-stealing malware. Furthermore, the adversary may try to compromise public websites owned by individual users by impersonating the website administrator using the stolen credential. These compromised websites then become landing sites for drive-by download malware infection. Identifying malicious websites using crawling techniques requires large resources and takes a lot of time. To observe web-based attack cycles to achieve effective detection and prevention, we propose a novel observation system based on a honeytoken that actively leaks credentials and lures adversaries to a decoy that behaves like a compromised web content management system. The proposed procedure involves collecting malware, leaking credentials, observing access by an adversary, and inspecting the compromised web content. It can instantly discover malicious entities without conducting large-scale web crawling because of the direct observation on the compromised web content management system. Our system enables continuous and stable observation for about one year. In addition, almost all the malicious websites we discovered had not been previously registered in public blacklists.