While software is now being developed with more sophisticated tools, its complexity has increased considerably, and, as a consequence new vulnerabilities are discovered every day. To address the constant flow of vulnerabilities being identified, patches are frequently being pushed to consumers. Patches, however, often involve having to shutdown services in order to be applied, which can result in expensive downtime. To solve this problem, various hot-patching systems have been devised to patch systems without the need for restarting. These systems often require either the cooperation of the system or the process they are patching. This still leaves out a considerable amount of systems, most notably embedded devices, which remain unable to be hot-patched.

Finding and exploiting vulnerabilities in binary code is a challenging task. The lack of high-level, semantically rich information about data structures and control constructs makes the analysis of program properties harder to scale. However, the importance of binary analysis is on the rise. In many situations binary analysis is the only possible way to prove (or disprove) properties about the code that is actually executed. In this paper, we present a binary analysis framework that implements a number of analysis techniques that have been proposed in the past. We present a systematized implementation of these techniques, which allows other researchers to compose them and develop new approaches. In addition, the implementation of these techniques in a unifying framework allows for the direct comparison of these apporaches and the identification of their advantages and disadvantages. The evaluation included in this paper is performed using a recent dataset created by DARPA for evaluating the effectiveness of binary vulnerability analysis techniques. Our framework has been open-sourced and is available to the security community.