Nebulon Enterprise Simulated Threats for Phishing Research (NEST-Phish): A Synthetic Enterprise Phishing Email Dataset for Behavioral and Machine-Learning Research
A synthetic enterprise phishing email dataset built around a fictitious organization, Nebulon, is introduced to support future work on phishing detection, human susceptibility, explainability, and benchmark development in enterprise-like contexts.
Abstract
Phishing remains one of the most persistent cyber threats, yet publicly shareable datasets for studying phishing in realistic enterprise email settings remain limited. To address this gap, we introduce a synthetic enterprise phishing email dataset built around a fictitious organization, Nebulon. The dataset spans a broad set of workplace communication themes and includes matched synthetic legitimate and phishing emails with interpretable phishing-cue annotations. Here, ``legitimate''denotes the non-phishing class, not legitimately occurring organizational emails. Human-subject categorizations and classifier evaluations show that the dataset supports meaningful variation in phishing judgments while also providing learnable signal for supervised detection. This publicly released resource is intended to support future work on phishing detection, human susceptibility, explainability, and benchmark development in enterprise-like contexts.
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