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arXiv · 2503.07036

Bot Wars Evolved: Orchestrating Competing LLMs in a Counterstrike Against Phone Scams

Nardine Basta·Conor Atkins·Dali Kaafar
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Abstract

We present "Bot Wars," a framework using Large Language Models (LLMs) scam-baiters to counter phone scams through simulated adversarial dialogues. Our key contribution is a formal foundation for strategy emergence through chain-of-thought reasoning without explicit optimization. Through a novel two-layer prompt architecture, our framework enables LLMs to craft demographically authentic victim personas while maintaining strategic coherence. We evaluate our approach using a dataset of 3,200 scam dialogues validated against 179 hours of human scam-baiting interactions, demonstrating its effectiveness in capturing complex adversarial dynamics. Our systematic evaluation through cognitive, quantitative, and content-specific metrics shows that GPT-4 excels in dialogue naturalness and persona authenticity, while Deepseek demonstrates superior engagement sustainability.

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Nardine Basta, Conor Atkins, Dali Kaafar. 2025-03-10. Bot Wars Evolved: Orchestrating Competing LLMs in a Counterstrike Against Phone Scams. https://arxiv.org/abs/2503.07036

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