Emergent Mind

Abstract

Since hardware oftentimes serves as the root of trust in our modern interconnected world, malicious hardware manipulations constitute a ubiquitous threat in the context of the Internet of Things (IoT). Hardware reverse engineering is a prevalent technique to detect such manipulations. Over the last years, an active research community has significantly advanced the field of hardware reverse engineering. Notably, many open research questions regarding the extraction of functionally correct netlists from Field Programmable Gate Arrays (FPGAs) or Application Specific Integrated Circuits (ASICs) have been tackled. In order to facilitate further analysis of recovered netlists, a software framework is required, serving as the foundation for specialized algorithms. Currently, no such framework is publicly available. Therefore, we provide the first open-source gate-library agnostic framework for gate-level netlist analysis. In this positional paper, we demonstrate the workflow of our modular framework HAL on the basis of two case studies and provide profound insights on its technical foundations.

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