Ron Marcovich, Orna Grumberg, Gabi Nakibly (Technion, Israel Institute of Technology)

protocol from a binary code that implements it. This process is useful in cases such as extraction of the command and control protocol of a malware, uncovering security vulnerabilities in a network protocol implementation or verifying conformance to the protocol’s standard. Protocol inference usually involves time-consuming work to manually reverse engineer the binary code.

We present a novel method to automatically infer state machine of a network protocol and its message formats directly from the binary code. To the best of our knowledge, this is the first method to achieve this solely based on a binary code of a single peer. We do not assume any of the following: access to a remote peer, access to captures of the protocol’s traffic, and prior knowledge of message formats. The method leverages extensions to symbolic execution and novel modifications to automata learning. We validate the proposed method by inferring real-world protocols including the C&C protocol of Gh0st RAT, a well-known malware

View More Papers

30 Years into Scientific Binary Decompilation: What We Have...

Dr. Ruoyu (Fish) Wang, Assistant Professor at Arizona State University

Read More

On the Anonymity of Peer-To-Peer Network Anonymity Schemes Used...

Piyush Kumar Sharma (imec-COSIC, KU Leuven), Devashish Gosain (Max Planck Institute for Informatics), Claudia Diaz (Nym Technologies, SA and imec-COSIC, KU Leuven)

Read More

Privacy-Preserving Database Fingerprinting

Tianxi Ji (Texas Tech University), Erman Ayday (Case Western Reserve University), Emre Yilmaz (University of Houston-Downtown), Ming Li (CSE Department The University of Texas at Arlington), Pan Li (Case Western Reserve University)

Read More

Post-GDPR Threat Hunting on Android Phones: Dissecting OS-level Safeguards...

Mark Huasong Meng (National University of Singapore), Qing Zhang (ByteDance), Guangshuai Xia (ByteDance), Yuwei Zheng (ByteDance), Yanjun Zhang (The University of Queensland), Guangdong Bai (The University of Queensland), Zhi Liu (ByteDance), Sin G. Teo (Agency for Science, Technology and Research), Jin Song Dong (National University of Singapore)

Read More