Towards Action Hijacking of Large Language Model-based Agent

Understand

Recently, applications powered by Large Language Models (LLMs) have made significant strides in tackling complex tasks.

• By harnessing the advanced reasoning capabilities and extensive knowledge embedded in LLMs, these applications can generate detailed action plans that are subsequently executed by external tools.
• Furthermore, the integration of retrieval-augmented generation (RAG) enhances performance by incorporating up-to-date, domain-specific knowledge into the planning and execution processes.
• This approach has seen widespread adoption across various sectors, including healthcare, finance, and software development.