MetaPI: Constructing Prompt Injection Benchmarks from LLM Agent Benchmark

Reported by arXiv cs.CR (Peiran Wang, Chong Xiang, Wenjie Qu, Ying Li, Jiaheng Zhang, G. Edward Suh, Yuan Tian)

Summary by Cyber Security News10 Nov 2026, 06:00 CET

About this summary. This is a short excerpt from the description that arXiv cs.CR published with its article. Cyber Security News did not report or verify the underlying story. Read the original: https://arxiv.org/abs/2611.10026

arXiv:2611.10026v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly perform complex tasks using high-privilege tools, making indirect prompt injection (IPI) a critical security risk. However, IPI benchmarks lag behind their rapidly evolving utility counterparts, only offering limited task and environment coverage and relying on narrow, static attack scenarios.

Read the full article at arXiv cs.CR →

Source attribution: headline and facts are from arXiv cs.CR (arxiv.org). Summary method: excerpt of the source description. See our source attribution policy.

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