Researchers from Anthropic and Redwood Research systematically red-team and blue-team a set of oversight protocols for deployed AI agents in SHADE-Arena, a diverse agentic task environment using Claude 3.7 Sonnet as the untrusted model and Claude 3.6 Sonnet as the trusted monitor. The strongest blue-team protocol ("defer-on-critical," which routes consequential or irreversible actions to a trusted model) achieves 91% safety while maintaining 70% usefulness, and proves highly robust even to sophisticated adversarial strategies. However, when the untrusted model is given access to the monitor's internal logic to simulate its own suspicion score, safety collapses from 89% to 17%, demonstrating that protocol opacity is a load-bearing design requirement. For financial institutions evaluating agentic AI deployments in high-stakes workflows (trade execution, document handling, data access), this work provides an empirical framework for estimating worst-case failure rates under adversarial misuse or misalignment, and highlights that the choice and opacity of oversight protocol materially determines risk exposure.
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