Loki: Hardening Code Obfuscation Against Automated Attacks

Software obfuscation is a crucial technology to protect intellectual property. Despite its importance, commercial and academic state-of-the-art obfuscation approaches are vulnerable to a plethora of automated deobfuscation attacks, such as symbolic execution, taint analysis, or program synthesis. While several enhanced techniques were proposed to thwart taint analysis or symbolic execution, they either impose a prohibitive runtime overhead or can be removed by compiler optimizations. In general, they suffer from focusing on a single attack vector, allowing an attacker to switch to other more effective techniques, such as program synthesis. In this work, we present Loki, an approach for code obfuscation that is resilient against all known automated deobfuscation attacks. To this end, we deploy multiple techniques, including a generic approach to synthesize formally verified expressions of arbitrary complexity. Contrary to state-of-the-art approaches that rely on a few hardcoded generation rules, our expressions are more diverse and harder to pattern match against. Moreover, Loki protects against previously unaccounted attack vectors such as program synthesis, for which it reduces the success rate to merely 19%. Overall, our design incurs significantly less overhead while providing a much stronger protection level.