Securing LLM Apps Means Threat-Modelling the Whole System, Not Just the Model

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The article argues that an AI model is only one part of a deployed large-language-model application, which also includes prompts, user input, retrieval systems, APIs, identity controls, logs, and downstream actions. Security failures can arise at the boundaries between these components even when the model behaves as designed. It recommends mapping the application's data and action paths to ask what data can enter, what the system can access, and what actions it can take. The piece cautions that retrieved documents should not be treated as trusted instructions and should be separated from system prompts, with access limited to what the current user is authorised to see. It also advises that the model should not be the sole authority on whether an action is permitted, with authorisation handled by application, identity, and policy layers, and least-privilege controls applied to any tool integrations.

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