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Embedded devices are becoming more widespread, interconnected, and-enabled than ever. However, recent studies showed that these devices are from being secure. Moreover, many embedded systems rely on web interfaces user interaction or administration. Unfortunately, web security is known to difficult, and therefore the web interfaces of embedded systems represent a attack surface. In this paper, we present the first fully automated framework that applies firmware analysis techniques to achieve, in a scalable manner, vulnerability discovery within embedded firmware images. We apply our to study the security of embedded web interfaces running in Off-The-Shelf (COTS) embedded devices, such as routers, DSL/cable, VoIP phones, IP/CCTV cameras. We introduce a methodology and implement scalable framework for discovery of vulnerabilities in embedded web regardless of the vendor, device, or architecture. To achieve this, our framework performs full system emulation to achieve the execution of images in a software-only environment, i. e. , without involving any embedded devices. Then, we analyze the web interfaces within the using both static and dynamic tools. We also present some interesting-studies, and discuss the main challenges associated with the dynamic of firmware images and their web interfaces and network services. The we make in this paper shed light on an important aspect of devices which was not previously studied at a large scale. We validate our framework by testing it on 1925 firmware images from 54 vendors. We discover important vulnerabilities in 185 firmware, affecting nearly a quarter of vendors in our dataset. These results demonstrate the effectiveness of our approach.
Costin et al. (Wed,) studied this question.