SAFE: Self-Attentive Function Embeddings for Binary Similarity
The binary similarity problem consists in determining if two functions are similar by only considering their compiled form. Techniques for binary similarity have an immediate practical impact on several fields such as copyright disputes, malware analysis, vulnerability detection, etc. Current solutions compare functions by first transforming their binary code in multi-dimensional vector representations (embeddings), and then comparing vectors through simple and efficient geometric operations.