Michael Pucher (University of Vienna), Christian Kudera (SBA Research), Georg Merzdovnik (SBA Research)

The complexity and functionality of malware is ever-increasing. Obfuscation is used to hide the malicious intent from virus scanners and increase the time it takes to reverse engineer the binary. One way to minimize this effort is function clone detection. Detecting whether a function is already known, or similar to an existing function, can reduce analysis effort. Outside of malware, the same function clone detection mechanism can be used to find vulnerable versions of functions in binaries, making it a powerful technique.

This work introduces a slim approach for the identification of obfuscated function clones, called OFCI, building on recent advances in machine learning based function clone detection. To tackle the issue of obfuscation, OFCI analyzes the effect of known function calls on function similarity. Furthermore, we investigate function similarity classification on code obfuscated through virtualization by applying function clone detection on execution traces. While not working adequately, it nevertheless provides insight into potential future directions.

Using the ALBERT transformer OFCI can achieve an 83% model size reduction in comparison to state-of-the-art approaches, while only causing an average 7% decrease in the ROC-AUC scores of function pair similarity classification. However, the reduction in model size comes at the cost of precision for function clone search. We discuss the reasons for this as well as other pitfalls of building function similarity detection tooling.

View More Papers

Dinosaur Resurrection: PowerPC Binary Patching for Base Station Analysis

Uwe Muller, Eicke Hauck, Timm Welz, Jiska Classen, Matthias Hollick (Secure Mobile Networking Lab, TU Darmstadt)

Read More

Characterizing the Adoption of Security.txt Files and their Applications...

William Findlay (Carleton University) and AbdelRahman Abdou (Carleton University)

Read More

Semantic-Informed Driver Fuzzing Without Both the Hardware Devices and...

Wenjia Zhao (Xi'an Jiaotong University and University of Minnesota), Kangjie Lu (University of Minnesota), Qiushi Wu (University of Minnesota), Yong Qi (Xi'an Jiaotong University)

Read More

A Heuristic Approach to Detect Opaque Predicates that Disrupt...

Yu-Jye Tung (University of California, Irvine), Ian Harris (University of California Irvine)

Read More