Samba: Detecting SSL/TLS API Misuses in IoT Binary Applications
Kaizheng Liu, Ming Yang, Zhen Ling, Yuan Zhang, Chongqing Lei, Lan Luo, Xinwen Fu · 2024
IoT devices are increasingly adopting Secure Socket Layer (SSL) and Transport Layer Security (TLS) protocols. However, the misuse of SSL/TLS libraries still threatens the communication. Existing tools for detecting SSL/TLS API misuses primarily rely on source code analysis while IoT applications are usually released as binaries with no source code. This paper presents Samba, a novel tool to automatically detect SSL/TLS API misuses in IoT binaries through static analysis. To overcome the path explosion problem and deal with various SSL/TLS implementations, we introduce a three-level reduction method to construct the SSL/TLS API-centric graph (SAG), which has a much smaller size compared with the conventional inter-procedural control flow graph. We propose a formal expression of API misuse signatures, which is capable of capturing different types of misuse, particularly those in the SSL/TLS connection establishment process. We successfully analyze 115 IoT binaries and find that 94 of them have the vulnerability of insecure certificate verification and 112 support deprecated SSL/TLS protocols. Samba is the first IoT binary analysis system for detecting SSL/TLS API misuses.