Deepbits Won NSF SBIR Phase I Award for “Enabling Robust Binary Code AI via Novel Disassembly”

On July 23, 2021, Deepbits won NSF SBIR Phase I Award for "Enabling Robust Binary Code AI via Novel Disassembly". Disassembler is an essential building block to many cybersecurity solutions. It is being used to disassemble code and extract features for high-level cybersecurity applications, such as vulnerability analysis, malware detection, etc. Current disassembly solutions are slow and inaccurate, and the volume of code analyzed by cybersecurity applications is huge. Cybersecurity companies either deploy tremendous computing resources to handle huge volumes of code or only extract superficial features from code for AI models, making those solutions extremely vulnerable to adversarial attacks.

The lack of a fast and accurate disassembler has become an obstacle to the applications of novel AI approaches in the cybersecurity industry. This project provides an innovative disassembly solution for binary code. The proposed solution combines state-of-the-art binary analysis techniques and newly emerging deep learning techniques to build a fast and accurate disassembler. The proposed solution utilizes GPU technology to accelerate the disassembly process. The final disassembly is expected to be over 100 times faster than state-of-the-art disassemblers, while achieving the same or better accuracy.