The Landscape of Prompt Injection Threats in LLM Agents: From Taxonomy to Analysis
The evolution of Large Language Models (LLMs) has resulted in a paradigm shift towards autonomous agents, necessitating robust security against Prompt Injection (PI) vulnerabilities where untrusted inputs hijack agent behaviors. This SoK presents a comprehensive overview of the PI landscape, covering attacks, defenses, and their evaluation practices. Through a systematic literature review and quantitative analysis, we establish taxonomies that categorize PI attacks by payload generation strategies (heuristic vs. optimization) and defenses by intervention stages (text, model, and execution levels). Our analysis reveals a key limitation shared by many existing defenses and benchmarks: they ...
| Authors | Peiran Wang, Xinfeng Li, Chong Xiang et al. |
|---|---|
| Primary category | cs.CR |
| Published | 11 February 2026 |
| Last updated at source | 11 February 2026 |
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