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2019-09-26
Pang, Chengbin, Du, Yunlan, Mao, Bing, Guo, Shanqing.  2018.  Mapping to Bits: Efficiently Detecting Type Confusion Errors. Proceedings of the 34th Annual Computer Security Applications Conference. :518-528.

The features of modularity and inheritance in C++ facilitate the developers' usage, but also give rise to the problem of type confusion. As an ancestor class may have a different data layout from its descendant class, a dangerous downcasting operation from the ancestor to its descendant can lead to a critical attack, such as control flow hijacking, out-of-bounds access to neighbor memory area, etc. As reported in CVE, such vulnerabilities have been found in various common-used software, including Google Chrome, Firefox and Adobe Flash Player, and have a trend of increase in recent years. The urgency of addressing type confusion problems quickens the pace of researchers coming to corresponding solutions. However, the existing works either handle the problem partially, or suffer from the high performance and memory overhead, especially to the large-scale projects. We present Bitype to check the validity explicitly when a type is downcasting to another, maintaining high coverage and reducing overhead and compilation time massively. The core of our design is a Safe Encoding Scheme, which encodes all of the classes by mapping them to bits. With this scheme, Bitype treats the classes and their safe convertible classes as codes and verifies typecastings in an xor operation, both decreasing the performance overhead of check and the memory overhead. Besides, we implement a Clang Tool to avoid the repeated collection of inheritance relationships and deploy a two-level lookup table to trace objects efficiently. Evaluated on SPEC CPU2006 benchmarks and Firefox browser, Bitype shows a slightly higher coverage of typecasting compared to the state-of-the-art HexType[22], but reduces the performance overhead by 2 to 16 times, the memory overhead by 2 to 3 times, the compilation time by 21 to 223 times. As a result, our solution is a practical and efficient typecasting checker for commodity software.

2017-05-30
Haller, Istvan, Jeon, Yuseok, Peng, Hui, Payer, Mathias, Giuffrida, Cristiano, Bos, Herbert, van der Kouwe, Erik.  2016.  TypeSan: Practical Type Confusion Detection. Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security. :517–528.

The low-level C++ programming language is ubiquitously used for its modularity and performance. Typecasting is a fundamental concept in C++ (and object-oriented programming in general) to convert a pointer from one object type into another. However, downcasting (converting a base class pointer to a derived class pointer) has critical security implications due to potentially different object memory layouts. Due to missing type safety in C++, a downcasted pointer can violate a programmer's intended pointer semantics, allowing an attacker to corrupt the underlying memory in a type-unsafe fashion. This vulnerability class is receiving increasing attention and is known as type confusion (or bad-casting). Several existing approaches detect different forms of type confusion, but these solutions are severely limited due to both high run-time performance overhead and low detection coverage. This paper presents TypeSan, a practical type-confusion detector which provides both low run-time overhead and high detection coverage. Despite improving the coverage of state-of-the-art techniques, TypeSan significantly reduces the type-confusion detection overhead compared to other solutions. TypeSan relies on an efficient per-object metadata storage service based on a compact memory shadowing scheme. Our scheme treats all the memory objects (i.e., globals, stack, heap) uniformly to eliminate extra checks on the fast path and relies on a variable compression ratio to minimize run-time performance and memory overhead. Our experimental results confirm that TypeSan is practical, even when explicitly checking almost all the relevant typecasts in a given C++ program. Compared to the state of the art, TypeSan yields orders of magnitude higher coverage at 4–10 times lower performance overhead on SPEC and 2 times on Firefox. As a result, our solution offers superior protection and is suitable for deployment in production software. Moreover, our highly efficient metadata storage back-end is potentially useful for other defenses that require memory object tracking.