Profit is the Red Team: Stress-Testing Agents in Strategic Economic Interactions
As agentic systems move into real-world deployments, their decisions increasingly depend on external inputs such as retrieved content, tool outputs, and information provided by other actors. When these inputs can be strategically shaped by adversaries, the relevant security risk extends beyond a fixed library of prompt attacks to adaptive strategies that steer agents toward unfavorable outcomes. We propose profit-driven red teaming, a stress-testing protocol that replaces handcrafted attacks with a learned opponent trained to maximize its profit using only scalar outcome feedback. The protocol requires no LLM-as-judge scoring, attack labels, or attack taxonomy, and is designed for structu...
| Authors | Shouqiao Wang, Marcello Politi, Samuele Marro et al. |
|---|---|
| Primary category | cs.AI |
| Published | 21 March 2026 |
| Last updated at source | 21 March 2026 |
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