The emergence of agentic RAG (Retrieval-Augmented Generation) enhances systems, allowing them to plan, reason, perform complex tasks, and self-correct. While this advancement addresses previous reliability issues, it has also created new security challenges.
Part II of the analysis focuses on the evolving threat landscape heading into 2026. As AI agents advance from mere text generators to active entities with tool access, the security landscape shifts significantly. The updated OWASP Top 10 for LLM (Large Language Model) applications now highlights risks such as unauthorized actions, data exfiltration, and financial exploitation, moving beyond just offensive content.
A critical concern is indirect prompt injection, deemed a high-priority vulnerability in agentic systems. This zero-click exploit allows malicious actors to compromise the system without direct manipulation, leveraging hidden instructions within external content processed by the agent. As a result, vigilance in securing AI systems is urgently needed to mitigate these threats.
