Bot Detection by NeuralTrust is a runtime security solution designed to identify and block automated traffic targeting large language model (LLM) applications. The product analyzes prompt patterns, frequency, and timing to detect scripted abuse, scrapers, and synthetic users attempting to exploit AI systems. The solution provides protection against DDoS attacks at both L3/L4 and L7 layers, identifies non-browser traffic including headless browsers and automation tools, and detects suspicious behavior patterns such as repeated prompts and rapid inputs. Rate limiting capabilities control request frequency based on IP, session, or token usage. Bot Detection operates within the NeuralTrust runtime stack and integrates with their broader security platform. The product aims to prevent token drainage, unauthorized data extraction, and service disruption while maintaining availability for legitimate users. The solution is implemented through a client library that collects behavioral data for analysis. It supports cost control by limiting misuse and optimizing usage, data protection by blocking unauthorized training and data theft, and uptime assurance through safeguards against service disruption. Bot Detection is part of NeuralTrust's Runtime Security (GAF) product line and works alongside other security features including prompt guard, behavioral threat detection, and sensitive data masking.