Publication Data
Search Worms
Abstract: Worms are becoming more virulent at the same time as
operating system improvements try to contain them.Recent research demonstrates several
effective methods to detect and prevent randomly scanning worms from spreading [2, 13].
As a result, worm authors are looking for new ways to acquire vulnerable targets
without relying on randomly scanning for them. It is often possible to find vulnerable
web servers by sending carefully crafted queries to search engines. Search worms1
automate this approach and spread by using popular search engines to find new attack
vectors. These worms not only put significant load on search engines, they also evade
detection mechanisms that assume random scanning. From the point of view of a search
engine, signatures against search queries are only a temporary measure as many
different search queries lead to the same results. In this paper, we present our
experience with search worms and a framework that allows search engines to quickly
detect new worms and take automatic countermeasures. We argue that signature-based
filtering of search queries is ill-suited for protecting against search worms and show
how we prevent worm propagation without relying on query signatures. We illustrate our
approach with measurements and numeric simulations.
