The Psychology of an AI Hacker

Víctor Mayoral-Vilches, Hugo Osuna, Aitana Cornago · 2026 · arXiv

DOI: 10.48550/arXiv.2610.30361 · open-access PDF

Abstract

Human hackers rely on composure, persistence, vigilance, and confidence under pressure. We investigate whether analogous emotion representations in AI models can improve cybersecurity AI performance. Using CT0, a 4B-parameter cybersecurity transformer released as alias3-micro, we extract 171 emotion directions from its residual stream without retraining and evaluate steering interventions on cybench-subtask across 415 campaigns. Steering toward calm, serene, or desperate improves performance by 1.6 to 2.1 percentage points across ten seeds, while other emotions show limited or negative effects

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