Mens Sana In Corpore Sano: Sound Firmware Corpora for Vulnerability Research

• URL: http://arxiv.org/abs/2404.11977v4
• Date: Thu, 21 Nov 2024 15:58:22 GMT
• Title: Mens Sana In Corpore Sano: Sound Firmware Corpora for Vulnerability Research
• Abstract summary: This paper analyzes the problem space and investigates its impact on research. We derive guidelines that help researchers to nurture corpus replicability and representativeness. We show the feasibility of our guidelines and build a new, replicable corpus for large-scale analyses on Linux firmware: LFwC.
• Score: 1.1101390076342181
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Firmware corpora for vulnerability research should be scientifically sound. Yet, several practical challenges complicate the creation of sound corpora: Sample acquisition, e.g., is hard and one must overcome the barrier of proprietary or encrypted data. As image contents are unknown prior analysis, it is hard to select high-quality samples that can satisfy scientific demands. Ideally, we help each other out by sharing data. But here, sharing is problematic due to copyright laws. Instead, papers must carefully document each step of corpus creation: If a step is unclear, replicability is jeopardized. This has cascading effects on result verifiability, representativeness, and, thus, soundness. Despite all challenges, how can we maintain the soundness of firmware corpora? This paper thoroughly analyzes the problem space and investigates its impact on research: We distill practical binary analysis challenges that significantly influence corpus creation. We use these insights to derive guidelines that help researchers to nurture corpus replicability and representativeness. We apply them to 44 top tier papers and systematically analyze scientific corpus creation practices. Our comprehensive analysis confirms that there is currently no common ground in related work. It shows the added value of our guidelines, as they discover methodical issues in corpus creation and unveil miniscule step stones in documentation. These blur visions on representativeness, hinder replicability, and, thus, negatively impact the soundness of otherwise excellent work. Finally, we show the feasibility of our guidelines and build a new, replicable corpus for large-scale analyses on Linux firmware: LFwC. We share rich meta data for good (and proven) replicability. We verify unpacking, deduplicate, identify contents, provide ground truth, and show LFwC's utility for research.

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