Nathan Burow

Derrick McKee, Nathan Burow, Mathias Payer

When reverse engineering a binary, the analyst must first understand the semantics of the binary's functions through either manual or automatic analysis. Manual semantic analysis is time-consuming, because abstractions provided by high level languages, such as type information, variable scope, or comments are lost, and past analyses cannot apply to the current analysis task. Existing automated binary analysis tools currently suffer from low accuracy in determining semantic function identification in the presence of diverse compilation environments. We introduce Software Ethology, a binary analysis approach for determining the semantic similarity of functions. Software Ethology abstracts semantic behavior as classification vectors of program state changes resulting from a function executing with a specified input state, and uses these vectors as a unique fingerprint for identification. All existing semantic identifiers determine function similarity via code measurements, and suffer from high inaccuracy when classifying functions from compilation environments different from their ground truth source. Since Software Ethology does not rely on code measurements, its accuracy is resilient to changes in compiler, compiler version, optimization level, or even different source implementing equivalent functionality. Tinbergen, our prototype Software Ethology implementation, leverages a virtual execution environment and a fuzzer to generate the classification vectors. In evaluating Tinbergen's feasibility as a semantic function identifier by identifying functions in coreutils-8.30, we achieve a high .805 average accuracy. Compared to the state-of-the-art, Tinbergen is 1.5 orders of magnitude faster when training, 50% faster in answering queries, and, when identifying functions in binaries generated from differing compilation environments, is 30%-61% more accurate.

Nathan Burow, Xinping Zhang, Mathias Payer

Control-Flow Hijacking attacks are the dominant attack vector against C/C++ programs. Control-Flow Integrity (CFI) solutions mitigate these attacks on the forward edge,i.e., indirect calls through function pointers and virtual calls. Protecting the backward edge is left to stack canaries, which are easily bypassed through information leaks. Shadow Stacks are a fully precise mechanism for protecting backwards edges, and should be deployed with CFI mitigations. We present a comprehensive analysis of all possible shadow stack mechanisms along three axes: performance, compatibility, and security. For performance comparisons we use SPEC CPU2006, while security and compatibility are qualitatively analyzed. Based on our study, we renew calls for a shadow stack design that leverages a dedicated register, resulting in low performance overhead, and minimal memory overhead, but sacrifices compatibility. We present case studies of our implementation of such a design, Shadesmar, on Phoronix and Apache to demonstrate the feasibility of dedicating a general purpose register to a security monitor on modern architectures, and the deployability of Shadesmar. Our comprehensive analysis, including detailed case studies for our novel design, allows compiler designers and practitioners to select the correct shadow stack design for different usage scenarios.