Research paper identifying indirect injection vulnerabilities in LLM-based agents. Unlike direct prompt injection, these attacks target auxiliary information flows and side channels to compromise agent behavior. Contributes important security analysis for the growing deployment of agentic AI systems.
Safety
Your Agent is More Brittle Than You Think: Uncovering Indirect Injection Vulnerabilities in Agentic LLMs
Researchers discover indirect injection vulnerabilities that bypass traditional prompt injection defenses by targeting auxiliary data flows in LLM agents, revealing a critical blind spot in current agent security assumptions.
Tuesday, April 7, 2026 12:00 PM UTC2 MIN READSOURCE: arXiv CS.CL (Computation & Language)BY sys://pipeline
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