Practical Type and Memory Safety Violation Detection Mechanisms
thesisposted on 29.08.2020, 14:30 by Yuseok JeonYuseok Jeon
System programming languages such as C and C++ are designed to give the programmer full control over the underlying hardware. However, this freedom comes at the cost of type and memory safety violations which may allow an attacker to compromise applications. In particular, type safety violation, also known as type confusion, is one of the major attack vectors to corrupt modern C++ applications. In the past years, several type confusion detectors have been proposed, but they are severely limited by high performance overhead, low detection coverage, and high false positive rates. To address these issues, we propose HexType and V-Type. First, we propose HexType, a tool that provides low-overhead disjoint metadata structures, compiler optimizations, and handles specific object allocation patterns. Thus, compared to prior work, HexType significantly improves detection coverage and reduces performance overhead. In addition, HexType discovers new type confusion bugs in real world programs such as Qt and Apache Xerces-C++. However, HexType still has considerable overhead from managing the disjoint metadata structure and tracking individual objects, and has false positives from imprecise object tracking, although HexType significantly reduces performance overhead and detection coverage. To address these issues, we propose a further advanced mechanism V-Type, which forcibly changes non-polymorphic types into polymorphic types to make sure all objects maintain type information. By doing this, V-Type removes the burden of tracking object allocation and deallocation and of managing a disjoint metadata structure, which reduces performance overhead and improves detection precision. Another major attack vector is memory safety violations, which attackers can take advantage of by accessing out of bound or deleted memory. For memory safety violation detection, combining a fuzzer with sanitizers is a popular and effective approach. However, we find that heavy metadata structure of current sanitizers hinders fuzzing effectiveness. Thus, we introduce FuZZan to optimize sanitizer metadata structures for fuzzing. Consequently, FuZZan improves fuzzing throughput, and this helps the tester to discover more unique paths given the same amount of time and to find bugs faster. In conclusion, my research aims to eliminate critical and common C/C++ memory and type safety violations through practical programming analysis techniques. For this goal, through these three projects, I contribute to our community to effectively detect type and memory safety violations.