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These blobs can be very large, and therefore any analysis tool must be able to handle such complex firmware. Additionally, embedded devices frequently require their firmware to be cryptographically signed by the manufacturer, making modification of the firmware on the device for analysis purposes infeasible. In this presentation, we will talk about the challenges of performing automated vulnerability analysis and backdoor finding in firmware. Then, we report on a binary static analysis system, called Angr, that automates most of the process of searching firmware binaries for the presence of flaws. To the best of our knowledge, Angr is the first firmware analysis system working at the binary level, in a scalable manner, and with no requirement to instrument code on the original device. To this end, Angr utilizes advanced program analysis techniques to analyze binary code in complex firmware of diverse hardware platforms, and it automates much of the process of identifying occurrences of buffer overflow and authentication bypass vulnerabilities. The tool uses novel techniques to improve the scalability of the analysis, which we will explain during the presentation. This includes a combination of more traditional static program analysis, value set analysis (VSA), and symbolic execution. The presentation will conclude with a few examples of vulnerabilities that our tool has discovered in firmware samples. We also plan to run a live demo that highlights the capabilities of our system Read more↗

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Updated1 year ago
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Keywordsus branco distributing the reconstruction of high level intermediate representation for large scale malware analysis
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