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New PIMiner system automates LLM prompt injection red-teaming

By PulseAugur Editorial · [1 sources] ·

Researchers have developed PIMiner, an agentic system designed for automated prompt injection red-teaming of large language models. Unlike existing methods that often struggle with generalization, PIMiner builds a transferable strategy library from scratch during training. This library can be applied to new, unseen target LLMs with minimal queries. Experiments show PIMiner achieving significant attack success rates against models like Gemini 2.5 Pro, GPT-5.1, and Claude Sonnet 4.5 on benchmarks such as IPIArena and AgentDojo. AI

IMPACT This research could lead to more robust LLM defenses against prompt injection attacks, improving the security of AI agents.

RANK_REASON The cluster contains a research paper detailing a new system for LLM security. [lever_c_demoted from research: ic=1 ai=1.0]

Read on Hugging Face Daily Papers →

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

New PIMiner system automates LLM prompt injection red-teaming

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The cluster contains a research paper detailing a new system for LLM security. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    Agent Against Agent: An Agentic System for Automatic Prompt Injection Red Teaming

    Prompt injection poses significant security risks to LLM agents. Efficient and effective red-teaming is therefore critical, both for evaluating these risks and for collecting training data to improve defenses. Existing state-of-the-art prompt injection red-teaming methods primari…

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