Astroid is a tool for automatically learning semantic malware signatures for Android from very few samples of a malware family. The key idea underlying our technique is to look for a maximally suspicious common subgraph (MSCS) that is shared between all known instances of a malware family. An MSCS describes the shared functionality between multiple Android applications in terms of inter-component call relations and their semantic metadata (e.g., data-flow properties). Our approach identifies such maximally suspicious common subgraphs by reducing the problem to maximum satisfiability. Once a semantic signature is learned, our approach uses a combination of static analysis and a new approximate signature matching algorithm to determine whether an Android application matches the semantic signature characterizing a given malware family.


Automated Synthesis of Semantic Malware Signatures using Maximum Satisfiability. Yu Feng, Osbert Bastani, Ruben Martins, Isil Dillig, Saswat Anand. To appear in NDSS 2017.


Coming soon.