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arXiv · 2607.14434

A Measurement Study of AI-Environment Realism Gaps in Malware-Analysis Sandboxes

Zhiyong Sui·Lamine Noureddine·Mst Eshita Khatun·Sideeq Bello·Babangida Bappah·Justin Woodring·Aisha Ali-Gombe
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Abstract

Sandboxing remains a core technique for observing suspicious program behavior, yet environment-aware malware increasingly suppresses execution when analysis is suspected. Prior generations of sandbox evasion focused on virtualization artifacts, timing discrepancies, and wear-and-tear realism. In this paper, we present the first systematic measurement study of AI-environment artifacts as a new sandbox-evasion surface. We operationalize this realism gap through AIprint, a probe framework that captures persistent artifacts left behind by AI-capable software ecosystems, including AI-assistant configuration directories, model caches, environment variables, local inference services, and package dependencies. We systematically extract 450 unique artifacts from 284 open-source AI projects on GitHub, compile them into unprivileged Windows probes, and evaluate them across seven commercial and open-source sandbox backends together with three AI-capable reference hosts. Our results show that traditional VM-detection baselines fail to reliably distinguish real AI-capable systems from modern sandboxes, whereas twelve AI-environment artifacts appear on the reference hosts and on none of the evaluated backends. A controlled 214-step installation experiment establishes a causal relationship between AI tool and package installation and measurable AI-environment artifact accumulation, while adaptive spoofing experiments reveal a fundamental operational asymmetry: reproducing convincing AI software environments is substantially more expensive than detecting shallow spoofing.

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Zhiyong Sui, Lamine Noureddine, Mst Eshita Khatun, Sideeq Bello, Babangida Bappah, Justin Woodring, Aisha Ali-Gombe. 2026-07-16. A Measurement Study of AI-Environment Realism Gaps in Malware-Analysis Sandboxes. https://arxiv.org/abs/2607.14434

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