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ReAct agents vulnerable to prompt injection, depth is key

Researchers have investigated the vulnerability of ReAct agents, which combine reasoning with tool use, to indirect prompt injection attacks. Their study found that the depth of the injection within the tool sequence significantly impacts the attack's success rate, with earlier injections being more effective. Claude Haiku demonstrated strong resistance to these attacks across all depths, while GPT-4o-mini's success rate decayed significantly with increasing injection depth. The research also indicated that the turn budget does not appear to be a major risk factor, but framing can influence success rates. AI

IMPACT Highlights a critical security flaw in current agent architectures, necessitating improved defenses for safe deployment.

RANK_REASON Academic paper detailing a new security vulnerability in AI agents. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Mohammadreza Rashidi ·

    Depth-Dependent Indirect Prompt Injection in Tool-Calling ReAct Agents: Injection Depth, Payload Framing, and Turn-Budget Sensitivity

    arXiv:2605.30686v1 Announce Type: cross Abstract: ReAct agents that interleave chain-of-thought reasoning with tool calls are increasingly deployed for real tasks such as scheduling, file retrieval, and data access. Their tool observation loop creates a direct attack surface: an …