Binary obfuscation plays an essential role in evading malware static analysis and detection. The widely used code obfuscation techniques, such as polymorphism and metamorphism, focus on evading syntax based detection. However, statistic test and semantic analysis techniques have been developed to thwart their evasion attempts. More recent binary obfuscation techniques are divided in their purposes of attacking either statistical or semantic approach, but not both. In this paper, we introduce mimimorphism, a novel binary obfuscation technique with the potential of evading both statistical and semantic detections. Mimimorphic malware uses instruction-syntax-aware high-order mimic functions to transform its binary into mimicry executables that exhibit high similarity to benign programs in terms of statistical properties and semantic characteristics. We implement a prototype of the mimimorphic engine on the Intel x86 platform, and evaluate its capability of evading statistical anomaly detection and semantic analysis detection techniques. Our experimental results demonstrate that the mimicry executables are indistinguishable from benign programs in terms of byte frequency distribution and entropy, as well as control flow fingerprint.