Insecurity Through Obscurity: Veiled Vulnerabilities in Closed-Source Contracts

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.

Publication Details

Journal
ArXiv.org
Published
2025-04-18
Primary Topic
Security and Verification in Computing
Type
article
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article

Insecurity Through Obscurity: Veiled Vulnerabilities in Closed-Source Contracts

ArXiv.org
Security and Verification in Computing
article

Insecurity Through Obscurity: Veiled Vulnerabilities in Closed-Source Contracts

article en

Abstract

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.

ArXiv.org
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