Despite protracted efforts by both researchers and practitioners, security vulnerabilities remain in modern software. Artificial diversity is an effective defense against many types of attack, and one form, address-space randomization, has been widely applied. Present artificial diversity implementations are either coarse-grained or require source code. Because of the widespread use of software of unknown provenance, e.g., libraries, where no source code is provided or available, building diversity into the source code is not always possible. I investigate an approach to stack layout transformation that operates on x86 binary programs, which would allow users to obfuscate vulnerabilities and increase their confidence in the software's dependability. The proposed approach is speculative: the stack frame layout for a function is inferred from the binary and assessed by executing the transformed program. Upon assessment failure, the inferred layout is refined in hopes to better reflect the actual function layout.

Fingerprint-protected Universal Serial Bus (USB) drives have seen increasing deployment recently to protect mobile data. Compared to regular USB drives, a fingerprint-protected USB drive has an integrated optical scanner and a private partition/drive (for example, drive G: on MS Windows), which is not accessible before a successful fingerprint authentication.This paper studies the security of a representative fingerprint-protected USB drive called AliceFDrive. Our results are twofold. First, through black-box reverse engineering and manipulation of binary code in a DLL, we bypassed AliceF-Drive's fingerprint authentication and accessed the private drive without actually presenting a valid fingerprint. This authentication bypass is a class attack in that the modified DLL can be distributed to any naive users to bypass AliceF-Drive's fingerprint authentication.Second, in our security analysis of AliceFDrive, we developed a program to automatically recover fingerprint reference templates from AliceFDrive, which may make AliceF-Drive worse than a regular USB drive: when Alice loses her fingerprint-protected USB drive, she does not only lose her data, she also loses her good-quality fingerprints, which are hard to recover as Alice's fingerprints do not change much over a long period of time.