Malware Analysis: A Perspective from Dynamic Symbolic Execution of Binary Code

Malware analysis typically involves three steps:obfuscation, infection, and malicious action. Many antivirus methods fail because obfuscation hides control structures. This paper provides an overview of dynamic symbolic execution (DSE) applied to binary code, especially x86. DSE is considered the most powerful technique for deobfuscation and can automatically recover control structures such as control‑flow graphs. Several DSE tools target x86 (e.g., angr, Mayhem, S2E, KLEE‑MC, and BE‑PUM); we examine their design choices and trade‑offs. Finally, we evaluate the effectiveness of control‑flow graph similarity for tasks such as packer identification and original entry point (OEP) detection.

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Publication Details

Journal
Journal of Science and Technology on Information security
Published
2025-10-02
DOI
https://doi.org/10.54654/isj.v2i25.1093
Primary Topic
Advanced Malware Detection Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Malware Analysis: A Perspective from Dynamic Symbolic Execution of Binary Code

Mizuhito Ogawa
Journal of Science and Technology on Information security
Advanced Malware Detection Techniques
article

Malware Analysis: A Perspective from Dynamic Symbolic Execution of Binary Code

Mizuhito Ogawa
article en

Abstract

Malware analysis typically involves three steps:obfuscation, infection, and malicious action. Many antivirus methods fail because obfuscation hides control structures. This paper provides an overview of dynamic symbolic execution (DSE) applied to binary code, especially x86. DSE is considered the most powerful technique for deobfuscation and can automatically recover control structures such as control‑flow graphs. Several DSE tools target x86 (e.g., angr, Mayhem, S2E, KLEE‑MC, and BE‑PUM); we examine their design choices and trade‑offs. Finally, we evaluate the effectiveness of control‑flow graph similarity for tasks such as packer identification and original entry point (OEP) detection.

Journal of Science and Technology on Information security
Japan Society for the Promotion of Science
Openalex Percentile: Top 66%
Advanced Malware Detection Techniques
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