Hyp3rArmor: reducing web application exposure to automated attacks

Web applications (webapps) are subjected constantly to automated, opportunistic attacks from autonomous robots (bots) engaged in reconnaissance to discover victims that may be vulnerable to specific exploits. This is a typical behavior found in botnet recruitment, worm propagation, largescale fingerprinting and vulnerability scanners. Most anti-bot techniques are deployed at the application layer, thus leaving the network stack of the webapp’s server exposed. In this paper we present a mechanism called Hyp3rArmor, that addresses this vulnerability by minimizing the webapp’s attack surface exposed to automated opportunistic attackers, for JavaScriptenabled web browser clients. Our solution uses port knocking to eliminate the webapp’s visible network footprint. Clients of the webapp are directed to a visible static web server to obtain JavaScript that authenticates the client to the webapp server (using port knocking) before making any requests to the webapp. Our implementation of Hyp3rArmor, which is compatible with all webapp architectures, has been deployed and used to defend single and multi-page websites on the Internet for 114 days. During this time period the static web server observed 964 attempted attacks that were deflected from the webapp, which was only accessed by authenticated clients. Our evaluation shows that in most cases client-side overheads were negligible and that server-side overheads were minimal. Hyp3rArmor is ideal for critical systems and legacy applications that must be accessible on the Internet. Additionally Hyp3rArmor is composable with other security tools, adding an additional layer to a defense in depth approach.This work has been supported by the National Science Foundation (NSF) awards #1430145, #1414119, and #1012798

Automated Dynamic Firmware Analysis at Scale: A Case Study on Embedded Web Interfaces

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

DDoS-Capable IoT Malwares: comparative analysis and Mirai Investigation

The Internet of Things (IoT) revolution has not only carried the astonishing promise to interconnect a whole generation of traditionally “dumb” devices, but also brought to the Internet the menace of billions of badly protected and easily hackable objects. Not surprisingly, this sudden flooding of fresh and insecure devices fueled older threats, such as Distributed Denial of Service (DDoS) attacks. In this paper, we first propose an updated and comprehensive taxonomy of DDoS attacks, together with a number of examples on how this classification maps to real-world attacks. Then, we outline the current situation of DDoS-enabled malwares in IoT networks, highlighting how recent data support our concerns about the growing in popularity of these malwares. Finally, we give a detailed analysis of the general framework and the operating principles of Mirai, the most disruptive DDoS-capable IoT malware seen so far

Building an Emulation Environment for Cyber Security Analyses of Complex Networked Systems

Computer networks are undergoing a phenomenal growth, driven by the rapidly increasing number of nodes constituting the networks. At the same time, the number of security threats on Internet and intranet networks is constantly growing, and the testing and experimentation of cyber defense solutions requires the availability of separate, test environments that best emulate the complexity of a real system. Such environments support the deployment and monitoring of complex mission-driven network scenarios, thus enabling the study of cyber defense strategies under real and controllable traffic and attack scenarios. In this paper, we propose a methodology that makes use of a combination of techniques of network and security assessment, and the use of cloud technologies to build an emulation environment with adjustable degree of affinity with respect to actual reference networks or planned systems. As a byproduct, starting from a specific study case, we collected a dataset consisting of complete network traces comprising benign and malicious traffic, which is feature-rich and publicly available

An Iterative and Toolchain-Based Approach to Automate Scanning and Mapping Computer Networks

As today's organizational computer networks are ever evolving and becoming more and more complex, finding potential vulnerabilities and conducting security audits has become a crucial element in securing these networks. The first step in auditing a network is reconnaissance by mapping it to get a comprehensive overview over its structure. The growing complexity, however, makes this task increasingly effortful, even more as mapping (instead of plain scanning), presently, still involves a lot of manual work. Therefore, the concept proposed in this paper automates the scanning and mapping of unknown and non-cooperative computer networks in order to find security weaknesses or verify access controls. It further helps to conduct audits by allowing comparing documented with actual networks and finding unauthorized network devices, as well as evaluating access control methods by conducting delta scans. It uses a novel approach of augmenting data from iteratively chained existing scanning tools with context, using genuine analytics modules to allow assessing a network's topology instead of just generating a list of scanned devices. It further contains a visualization model that provides a clear, lucid topology map and a special graph for comparative analysis. The goal is to provide maximum insight with a minimum of a priori knowledge.Comment: 7 pages, 6 figure

UK security breach investigations report: an analysis of data compromise cases

This report, rather than relying on questionnaires and self-reporting, concerns cases that were investigated by the forensic investigation team at 7Safe. Whilst removing any inaccuracies arising from self-reporting, the authors acknowledge that the limitation of the sample size remains. It is hoped that the unbiased reporting by independent investigators has yielded interesting facts about modern security breaches. All data in this study is based on genuine completed breach investigations conducted by the compromise investigation team over the last 18 months