Indirect Prompt Injection Exploits LLMs’ Lack of Informational Context

A new wave of cyber threats targeting large language models (LLMs) has emerged, exploiting their inherent inability to differentiate between informational content and actionable instructions. Termed “indirect prompt injection attacks,” these exploits embed malicious directives within external data sources-such as documents, websites, or emails-that LLMs process during operation. Unlike direct prompt injections, where attackers manipulate […]

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