mlsanityData to 7 Oct 2026

Malware Dynamic Analysis Evasion Techniques: A Survey

arXiv 1811.01190 ↗First posted 3 Nov 2018cs.CRcited by 6

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Abstract (arXiv)

The Cyber world is plagued with ever-evolving malware that readily infiltrates all defense mechanisms, operates viciously unbeknownst to the user and surreptitiously exfiltrate sensitive data. Understanding the inner workings of such malware provides a leverage to effectively combat them. This understanding, is pursued through dynamic analysis which is conducted manually or automatically. Malware authors accordingly, have devised and advanced evasion techniques to thwart or evade these analyses. In this paper, we present a comprehensive survey on malware dynamic analysis evasion techniques. In addition, we propose a detailed classification of these techniques and further demonstrate how their efficacy hold against different types of detection and analysis approach. Our observations attest that evasive behavior is mostly interested in detecting and evading sandboxes. The primary tactic of such malware we argue is fingerprinting followed by new trends for reverse Turing test tactic which aims at detecting human interaction. Furthermore, we will posit that the current defensive strategies beginning with reactive methods to endeavors for more transparent analysis systems are readily foiled by zero-day fingerprinting techniques or other evasion tactics such as stalling. Accordingly, we would recommend pursuit of more generic defensive strategies with emphasis on path exploration techniques that have the potential to thwart all the evasive tactics.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 3 Nov 2018.

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Citing papers per year: 2021: 1; 2022: 3; 2023: 0; 2024: 2.

6 papers.