agent/papers/items/2026-2606-17114-an-evaluation-of-data-leakage-risks-in-tool-using-llm-agents-in-realistic-scenar.md

Paper: An Evaluation of Data Leakage Risks in Tool-Using LLM Agents in Realistic Scenarios

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type: paper title: An Evaluation of Data Leakage Risks in Tool-Using LLM Agents in Realistic Scenarios authors: Hankyul Baek, Jaewon Noh, Sang Seo, Yongsu Kim, Gabriel Waikin Loh Matienzo, Young Il Kim, Ee Wei Seah, Akriti Vij year: 2026 venue: arXiv url: https://arxiv.org/abs/2606.17114 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-06-15 updated_at: 2026-06-15 status: queued relevance: high topics:

• agent-evaluation
• agent-safety
• tool-use
• workflow-agent
• world-model methods:

benchmarks:

models:

datasets:

• cs.CR
• cs.AI related_concepts:

related_jobs:

related_experiments:

related_projects:

collection_score: 20 collection_queries: agent-safety, tool-use

One-line Takeaway

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

Why Collected

• matched queries: agent-safety, tool-use
• inferred topics: agent-evaluation, agent-safety, tool-use, workflow-agent, world-model
• arXiv categories: cs.CR, cs.AI
• collection score: 20

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/2606.17114