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Traditional honeypot technology is server based and not able to detect client-side attacks. A low interaction honeypot like Honeyd, or a high interaction honeynet system with the Roo Honeywall, acts as a server, exposeing some vulnerable services and passively waiting to be attacked (Figure 1). However, to detect a client-side attack, a system needs to actively interact with the server or process malicious data. A new type of honeypot is therefore needed: the client honeypot. Client honeypots crawl the network, interact with servers, and classify servers with respect to their malicious nature (Figure 2).
The main differences between a client-side honeypot and traditional honeypot are:
* client-side: it simulates/drives client-side software and does not expose server based services to be attacked.
* active: it cannot lure attacks to itself, but rather it must actively interact with remote servers to be attacked.
* identify: whereas all accesses to the traditional honeypot are malicious, the client-side honeypot must discern which server is malicious and which is benign.
Similarly to traditional server honeypots, there are two types of client honeypots: low and high interaction client honeypots. The low interaction client honeypot uses a simulated client (for example HoneyC or wget in the case of a browser-based client honeypot), interacts with servers, and classifies the servers based on some established definition of “malicious” activity. Usually this is performed via static analysis and signature matching. Low interaction client honeypots have the benefit of being quite fast, but can produce false alerts or miss a malicious server, especially since they do not act like a “real” client and have programmatic limitations. They may also fail to fully emulate all vulnerabilities in a client application. The other type of client honeypot, the high interaction client honeypot, takes a different approach to make a classification of malicious activity. Using a dedicated operating system, it drives an actual vulnerable client to interact with potentially malicious servers. After each interaction, it checks the operating system for unauthorized state changes. If any of these state changes are detected, the server is classified as malicious. Since no signatures are used, high interaction client honeypots are able to detect unknown attacks.
In this paper, we are looking at malicious web servers that attack web browsers. Attacks on web browsers by malicious web servers seem to be the most prominent client-side attack type today, but they are still not well understood. The goal of our work is to assess the threat to web browser client applications from malicious web servers with a high interaction client honeypot. We chose to use a high interaction client honeypot, because it allows us to obtain information about attacks that are unknown or obfuscated in a way that low interaction client honeypots could not detect. We obtain and present information on malicious web servers, evaluate several defense mechanisms, and make recommendations on how to protect systems against these malicious web servers.