Bridging the Gap: Automated Analysis of Sancus

Techniques for verifying or invalidating the security of computer systems have come a long way in recent years. Extremely sophisticated tools are available to specify and for-mally verify the behavior of a system and, at the same time, attack techniques have evolved to the point of questioning the possibility of obtaining adequate levels of security, especially in critical applications. In a recent paper, Bognar et al. [1] have clearly highlighted this inconsistency between the two worlds: on one side, formal verification allows writing irrefutable proofs of the security of a system, on the other side concrete attacks make these proofs waver, exhibiting a gap between models and implementations which is very complex to bridge. In this paper, we propose a new method to reduce this gap in the Sancus embedded security architecture, by exploiting some peculiarities of both approaches. Our technique first extracts a behavioral model by directly interacting with the real Sancus system and then analyzes it to identify attacks and anomalies. Given a threat model, our method either finds attacks in the given threat model or gives probabilistic guarantees on the security of the system. We implement our method and use it to systematically rediscover known attacks and uncover new ones.