Indirect prompt injection lets attackers bypass LLM supervisor agents by hiding malicious instructions in profile fields and contextual data. Learn how this attack works and how to defend against it.

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Authentication Failures (A07) show the largest gap in the dataset: a 48-percentage-point difference between leaders and the field. Leaders fix at nearly 60%, while the field sits at roughly 12%.

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This article is authored by Soham Jagtap, senior research associate, The Dialogue.

We’ve explored how prompt injections exploit the fundamental architecture of LLMs. So, how do we defend against threats that ...