Beyond Static Labels: A Behavioral Framework for macOS Grayware Classification

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Presented at Objective by the Sea 8.0 by

Rousana Charles

On macOs, adware and potentially unwanted programs (PUPs) have traditionally been viewed as low priority nuisances. However, modern grayware families now demonstrate behaviors commonly associated with malware, such as persistence mechanisms, obfuscation, encrypted payload and covert data collection. Despite this, public dataset still apply static labels (e.g. 'adware.generic or PUP.optional') which fails to capture behavioral nuances and operational risks. This talk explores behavior-first labeling for macOS grayware, looking at five behavioral categories/traits: deception, persistence, monetization, user consent and payload activity. A case study of the Adload family (2016-2025) highlights how these threats evolve over time and how static labels alone fail to capture the dynamic evolution of these threats. While complementing rather than replacing traditional malware classification, this behavioral framework offers a more nuanced and operationally useful approach to identifying and responding to threats in the gray zone. It also provides a foundation for more adaptive detection, risk scoring and intelligence analysis in the modern macOS environment.