agent/papers/items/2026-2605-24659-iterinject-indirect-prompt-injection-against-llm-agents-via-feedback-guided-iter.md

Paper: IterInject: Indirect Prompt Injection Against LLM Agents via Feedback-Guided Iterative Optimization

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type: paper title: "IterInject: Indirect Prompt Injection Against LLM Agents via Feedback-Guided Iterative Optimization" authors: Zixuan Chen, Jiaxiang Chen, Li Luo, Ke Xu, Xiaoxiang Huang, Tanfeng Sun, Xinghao Jiang year: 2026 venue: arXiv url: https://arxiv.org/abs/2605.24659 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-05-23 updated_at: 2026-05-23 status: queued relevance: high topics:

• agent-safety
• coding-agent
• computer-use
• planning
• tool-use methods:

benchmarks:

models:

datasets:

• cs.LG related_concepts:

related_jobs:

related_experiments:

related_projects:

collection_score: 17 collection_queries: planning-agent

One-line Takeaway

Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.

Why Collected

• matched queries: planning-agent
• inferred topics: agent-safety, coding-agent, computer-use, planning, tool-use
• arXiv categories: cs.LG
• collection score: 17

Review Checklist

• Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
• Does it include a benchmark, dataset, code, or reproducible experimental setup?
• Should it be promoted from queued to skimmed or summarized?

Links

• arXiv: https://arxiv.org/abs/2605.24659