Securing AI Agents Against Untrusted Data Sources
AI agents processing external data face severe security risks from malicious inputs. Implementing architectural guardrails helps developers safely integrate untrusted sources into automated workflows, mitigating prompt injection attacks and unauthorized data access while maintaining system reliability and performance in modern applications.
Source: Towards Data Science