New benchmark exposes indirect prompt injection risks in multi-step agent tasks

The INFUSE benchmark evaluates 19 LLMs across 40 realistic workflows and 56 attack scenarios, finding mean attack success rates up to 41.9% and limited protection from existing defenses.

Academic
Thuy Dung Nguyen · Jingyi Guo · Rana Seda Dubauskas · Sreepriya Damuluru · Taylor T. Johnson · Kevin Leach

Vanderbilt University

Research Digest··3 min read
The authors introduce INFUSE, an end-to-end benchmark for evaluating indirect prompt injection (IPI) in long-horizon agent workflows.

The authors constructed INFUSE, a benchmark consisting of 40 realistic, long-horizon tasks spanning debugging, security, file management, system deployment, and application development.

Why this paper

From Vanderbilt University

In one line

Indirect prompt injection frequently compromises long-running LLM agents, while conversational safety guards transfer poorly and instructional hardening offers stronger but uneven protection.

What we could check

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  • ✓Limitations stated by the authors
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Research Digest

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