Most blockchains cannot hide the binary code of programs (i.e., smart contracts) running on them. To conceal proprietary business logic and to potentially deter attacks, many smart contracts are closed-source and employ layers of obfuscation. However, we demonstrate that such obfuscation can obscure critical vulnerabilities rather than enhance security, a phenomenon we term insecurity through obscurity. To systematically analyze these risks on a large scale, we present SKANF, a novel EVM bytecode analysis tool tailored for closed-source and obfuscated contracts. SKANF combines control-flow deobfuscation, symbolic execution, and concolic execution based on historical transactions to identify and exploit asset management vulnerabilities. Our evaluation on real-world Maximal Extractable Value (MEV) bots reveals that SKANF detects vulnerabilities in 1,030 contracts and successfully generates exploits for 394 of them, with potential losses of \$10.6M. Additionally, we uncover 104 real-world MEV bot attacks that collectively resulted in \$2.76M in losses.
Categories: cs.CR