Coursera Flash Sale
40% Off Coursera Plus for 3 Months!
Grab it
Explore a research presentation introducing BIN2WRONG, a comprehensive fuzzing framework designed to systematically detect semantic errors in binary-to-C decompilers. Learn how this innovative approach addresses critical limitations in current decompiler testing by unifying all factors that influence binary code generation, including source constructs, compilers, optimization levels, and executable formats. Discover the novel testcase structure that enables mutation across multiple dimensions simultaneously, revealing complex errors that traditional testing methods miss. Examine the framework's decompiler-agnostic design that supports both free and commercial decompilers, and understand how systematic binary mutation enhances the discovery of decompilation defects. Review comprehensive evaluation results demonstrating BIN2WRONG's superior performance compared to state-of-the-art fuzzers Cornucopia and DecFuzzer, achieving significantly higher binary diversity and decompiler code coverage across seven different decompilers. Understand the practical impact of this research through the discovery of 48 new bugs, including 30 confirmed defects, and learn how the framework's findings led to a major redesign of the commercial decompiler Binary Ninja, highlighting its effectiveness in uncovering critical issues in mainstream decompilation tools essential for debugging, performance tuning, and security hardening of closed-source software.
