FATS: A Prompt Injection Attack Utilizing Feign Security Agents with Deceptive Few-shots Learning

arXiv:2410.08776 · cs.CR, cs.AI · Submitted 2024-10-11 · Read on arXiv

cs.CR, cs.AI

Submitted: 2024-10-11

Updated: 2026-09-05

Comments: The final version

DOI: 10.1007/978-981-95-7078-2_47

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Large Language Models (LLMs) — 2× in this paper · explained in 6 episodes
• Reinforcement Learning — 2× in this paper · explained in 4 episodes
• Verification — 2× in this paper · explained in 2 episodes
• Alignment — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Feign Agent Attack with Toxic-shots — 1× in this paper
• Reinforcement Learning with Human Feedback — 1× in this paper
• Semantic Understanding — 1× in this paper · explained in 2 episodes

Sources

• Breaking Down the Defenses: A Comparative Survey of Attacks on Large Language Models
• Defending Against Indirect Prompt Injection Attacks With Spotlighting
• ShieldLM: Empowering LLMs as Aligned, Customizable and Explainable Safety Detectors

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