Biblio

As the web keeps increasing in size, the number of vulnerable and poorly-managed websites increases commensurately. Attackers rely on armies of malicious bots to discover these vulnerable websites, compromising their servers, and exfiltrating sensitive user data. It is, therefore, crucial for the security of the web to understand the population and behavior of malicious bots.In this paper, we report on the design, implementation, and results of Aristaeus, a system for deploying large numbers of "honeysites", i.e., websites that exist for the sole purpose of attracting and recording bot traffic. Through a seven-month-long experiment with 100 dedicated honeysites, Aristaeus recorded 26.4 million requests sent by more than 287K unique IP addresses, with 76,396 of them belonging to clearly malicious bots. By analyzing the type of requests and payloads that these bots send, we discover that the average honeysite received more than 37K requests each month, with more than 50% of these requests attempting to brute-force credentials, fingerprint the deployed web applications, and exploit large numbers of different vulnerabilities. By comparing the declared identity of these bots with their TLS handshakes and HTTP headers, we uncover that more than 86.2% of bots are claiming to be Mozilla Firefox and Google Chrome, yet are built on simple HTTP libraries and command-line tools.

Honeypots constitute an invaluable piece of technology that allows researchers and security practitioners to track the evolution of break-in techniques by attackers and discover new malicious IP addresses, hosts, and victims. Even though there has been a wealth of research where researchers deploy honeypots for a period of time and report on their findings, there is little work that attempts to understand how the underlying properties of a compromised system affect the actions of attackers. In this paper, we report on a four-month long study involving 102 medium-interaction honeypots where we vary a honeypot's location, difficulty of break-in, and population of files, observing how these differences elicit different behaviors from attackers. Moreover, we purposefully leak the credentials of dedicated, hard-to-brute-force, honeypots to hacking forums and paste-sites and monitor the actions of the incoming attackers. Among others, we find that, even though bots perform specific environment-agnostic actions, human attackers are affected by the underlying environment, e.g., executing more commands on honeypots with realistic files and folder structures. Based on our findings, we provide guidance for future honeypot deployments and motivate the need for having multiple intrusion-detection systems.

Domain squatting is a common adversarial practice where attackers register domain names that are purposefully similar to popular domains. In this work, we study a specific type of domain squatting called "combosquatting," in which attackers register domains that combine a popular trademark with one or more phrases (e.g., betterfacebook[.]com, youtube-live[.]com). We perform the first large-scale, empirical study of combosquatting by analyzing more than 468 billion DNS records - collected from passive and active DNS data sources over almost six years. We find that almost 60% of abusive combosquatting domains live for more than 1,000 days, and even worse, we observe increased activity associated with combosquatting year over year. Moreover, we show that combosquatting is used to perform a spectrum of different types of abuse including phishing, social engineering, affiliate abuse, trademark abuse, and even advanced persistent threats. Our results suggest that combosquatting is a real problem that requires increased scrutiny by the security community.