How Dangerous Are AI Agents Mimicking You? AntiSkillBench Reveals Privacy Risks
Yongli Xiang · hf · 2026-08-05
As AI agents learn to distill personal interaction histories into reusable "persona skills", the associated privacy and security risks intensify. A new paper introduces AntiSkillBench, an end-to-end benchmark designed to evaluate risks and defenses within the persona-skill pipeline.
The benchmark features:
- Dataset: 7,500 dialogue traces constructed from 50 behaviorally rich user profiles.
- Evaluation Suite: Measures skill-level privacy leakage and agent-level attribute disclosure/behavioral impersonation across three distillation strategies.
- Defense Evaluation: Tests four configurations across online and post-hoc interventions.
Experiments across three frontier agents show that privacy risks persist universally, while existing defenses offer limited, distillation-dependent effectiveness.
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