DEBIN uses machine learning to recover debug information (e.g., names and types) of stripped binaries (x86, x64, ARM).
This is helpful for various binary analysis tasks such as decompilation, malware inspection and similarity.
DEBIN is a novel system for predicting debug information in stripped binaries. It is able to distinguish register-allocated and memory-allocated variables with decision-tree-based classification. Moreover, it is capable of predicting meaningful names and types for variables and functions through structured prediction with probabilistic graphical models. These models are learned from thousands of non-stripped binary in open source packages. The system can be further used for malware inspection.
If you have any feedback, suggestions or want to use DEBIN for larger binaries, please email Martin Vechev by email@example.com.
To use our application with all its potential, please use a tablet device display or larger. Our prediction results cannot be properly displayed on a small screen.
Thank you, DEBIN Team
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