Early detection of tool misuse in AI agent rollouts is critical for maintaining safety and trust. A primary approach involves comprehensive logging and monitoring of all API calls and tool interactions, looking for anomalous patterns such as unusual frequency, unauthorized resource access, or unexpected parameters. Implementing behavioral anomaly detection algorithms helps identify deviations from established baselines of legitimate tool usage, triggering alerts for suspicious activities. Furthermore, establishing strict guardrails and predefined policies on tool invocation, data access, and action types allows for immediate flagging of any attempted policy violations. Human-in-the-loop review of agent decisions and red teaming exercises can also proactively uncover potential misuse vectors and vulnerabilities before widespread deployment, ensuring a robust safety framework. More details: https://evromedportal.xyz/gogo.php?https://infoguide.com.ua/