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INFUSE tests 19 language models on 56 prompt injection attacks

The mean attack success rate is 19.6% when a language model examines the result.

Claimed, not confirmed

Researchers made INFUSE, a benchmark for indirect prompt injection in long agent tasks. It has 40 tasks and 56 attacks. In tests on 19 models, the mean attack success rate is 19.6%. A prompt-level defense cuts the mean rate from 58.2% to 14.3%.

Mean attack success fell from 58.2% to 14.3% with prompt hardening Two bars on one 0 to 100% scale. Before hardening, mean attack success was 58.2%. With hardening it was 14.3%. 19 LLMs tested. Mean attack success 100% 58.2% 14.3% Before hardening With hardening 19 LLMs tested
In the INFUSE benchmark of 19 LLMs, adding hardening instructions to prompts cut mean attack success from 58.2% to 14.3%.

Sources

  1. INFUSE: A Unified Surface Benchmark for Indirect Prompt Injection in Agentic Systemsarxiv.org
AI MATTER · NEWS · AI MATTER · NEWS ·16 OCT2026

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