Defending Against Firmware Cyber Attacks on Safety-Critical Systems

In the past, it was not possible to update the underlying software in many industrial control devices. Engineering teams had to ‘rip and replace’ obsolete components. However, the ability to make firmware updates has provided significant benefits to the companies who use Programmable Logic Controllers (PLCs), switches, gateways and bridges as well as an array of smart sensor/actuators. These updates include security patches when vulnerabilities are identified in existing devices; they can be distributed by physical media but are increasingly downloaded over Internet connections. These mechanisms pose a growing threat to the cyber security of safety-critical applications, which are illustrated by recent attacks on safety-related infrastructures across the Ukraine. Subsequent sections explain how malware can be distributed within firmware updates. Even when attackers cannot reverse engineer the code necessary to disguise their attack, they can undermine a device by forcing it into a constant upload cycle where the firmware installation never terminates. In this paper, we present means of mitigating the risks of firmware attack on safety-critical systems as part of wider initiatives to secure national critical infrastructures. Technical solutions, including firmware hashing, must be augmented by organizational measures to secure the supply chain within individual plants, across companies and throughout safety-related industries

File Carving and Malware Identification Algorithms Applied to Firmware Reverse Engineering

Modern society depends on critical infrastructure (CI) managed by Programmable Logic Controllers (PLCs). PLCs depend on firmware, though firmware security vulnerabilities and contents remain largely unexplored. Attackers are acquiring the knowledge required to construct and install malicious firmware on CI. To the defender, firmware reverse engineering is a critical, but tedious, process. This thesis applies machine learning algorithms, from the le carving and malware identification fields, to firmware reverse engineering. It characterizes the algorithms\u27 performance. This research describes and characterizes a process to speed and simplify PLC firmware analysis. The system partitions binary firmwares into segments, labels each segment with a le type, determines the target architecture of code segments, then disassembles and performs rudimentary analysis on the code segments. The research discusses the system\u27s accuracy on a set of pseudo-firmwares. Of the algorithms this research considers, a combination of a byte-value frequency file carving algorithm and a support vector machine (SVM) algorithm using information gain (IG) for feature selection achieve the best performance. That combination correctly identifies the file types of 57.4% of non-code bytes, and the architectures of 85.3% of code bytes. This research applies the Firmware Disassembly System to a real-world firmware and discusses the contents

Cutting Through the Complexity of Reverse Engineering Embedded Devices

Performing security analysis of embedded devices is a challenging task. They present many difficulties not usually found when analyzing commodity systems: undocumented peripherals, esoteric instruction sets, and limited tool support. Thus, a significant amount of reverse engineering is almost always required to analyze such devices. In this paper, we present Incision, an architecture and operating-system agnostic reverse engineering framework. Incision tackles the problem of reducing the upfront effort to analyze complex end-user devices. It combines static and dynamic analyses in a feedback loop, enabling information from each to be used in tandem to improve our overall understanding of the firmware analyzed. We use Incision to analyze a variety of devices and firmware. Our evaluation spans firmware based on three RTOSes, an automotive ECU, and a 4G/LTE baseband. We demonstrate that Incision does not introduce significant complexity to the standard reverse engineering process and requires little manual effort to use. Moreover, its analyses produce correct results with high confidence and are robust across different OSes and ISAs

InternalBlue - Bluetooth Binary Patching and Experimentation Framework

Bluetooth is one of the most established technologies for short range digital wireless data transmission. With the advent of wearables and the Internet of Things (IoT), Bluetooth has again gained importance, which makes security research and protocol optimizations imperative. Surprisingly, there is a lack of openly available tools and experimental platforms to scrutinize Bluetooth. In particular, system aspects and close to hardware protocol layers are mostly uncovered. We reverse engineer multiple Broadcom Bluetooth chipsets that are widespread in off-the-shelf devices. Thus, we offer deep insights into the internal architecture of a popular commercial family of Bluetooth controllers used in smartphones, wearables, and IoT platforms. Reverse engineered functions can then be altered with our InternalBlue Python framework---outperforming evaluation kits, which are limited to documented and vendor-defined functions. The modified Bluetooth stack remains fully functional and high-performance. Hence, it provides a portable low-cost research platform. InternalBlue is a versatile framework and we demonstrate its abilities by implementing tests and demos for known Bluetooth vulnerabilities. Moreover, we discover a novel critical security issue affecting a large selection of Broadcom chipsets that allows executing code within the attacked Bluetooth firmware. We further show how to use our framework to fix bugs in chipsets out of vendor support and how to add new security features to Bluetooth firmware

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

Software implementation of a secure firmware update solution in an IoT context

The present paper is concerned with the secure delivery of firmware updates to Internet of Things (IoT) devices. Additionally, it deals with the design of a safe and secure bootloader for a UHF RFID reader. A software implementation of a secure firmware update solution is performed. The results show there is space to integrate even more security features into existing devices

Towards the Model-Driven Engineering of Secure yet Safe Embedded Systems

We introduce SysML-Sec, a SysML-based Model-Driven Engineering environment aimed at fostering the collaboration between system designers and security experts at all methodological stages of the development of an embedded system. A central issue in the design of an embedded system is the definition of the hardware/software partitioning of the architecture of the system, which should take place as early as possible. SysML-Sec aims to extend the relevance of this analysis through the integration of security requirements and threats. In particular, we propose an agile methodology whose aim is to assess early on the impact of the security requirements and of the security mechanisms designed to satisfy them over the safety of the system. Security concerns are captured in a component-centric manner through existing SysML diagrams with only minimal extensions. After the requirements captured are derived into security and cryptographic mechanisms, security properties can be formally verified over this design. To perform the latter, model transformation techniques are implemented in the SysML-Sec toolchain in order to derive a ProVerif specification from the SysML models. An automotive firmware flashing procedure serves as a guiding example throughout our presentation.Comment: In Proceedings GraMSec 2014, arXiv:1404.163

Bootbandit: A macOS Bootloader Attack

Full disk encryption (FDE) is used to protect a computer system against data theft by physical access. If a laptop or hard disk drive protected with FDE is stolen or lost, the data remains unreadable without the encryption key. To foil this defense, an intruder can gain physical access to a computer system in a so-called “evil maid” attack, install malware in the boot (pre-operating system) environment, and use the malware to intercept the victim’s password. Such an attack relies on the fact that the system is in a vulnerable state before booting into the operating system. In this paper, we discuss an evil maid type of attack, in which the victim’s password is stolen in the boot environment, passed to the macOS user environment, and then exfiltrated from the system to the attacker’s remote command and control server. On a macOS system, this attack has additional implications due to “password forwarding” technology, in which users’ account passwords also serve as FDE passwords