Predicting Debug Information in Stripped Binaries

Technology

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.

Research

DEBIN is developed at Secure, Reliable and Intelligent Systems Lab, ETH Zurich. To investigate further on how DEBIN works, please refer to DEBIN CCS'18 paper. DEBIN is part of the Machine Learning for Programming project.

Contact

If you have any feedback, suggestions or want to use DEBIN for larger binaries, please email Martin Vechev by firstname.lastname@inf.ethz.ch.

Disclaimer

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