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Technical Guide

Prompt injection defense for production GenAI applications

A layered approach to defending copilots, chatbots, RAG apps, and agents from direct and indirect prompt attacks.

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Technical Guide9 min readAI Product Teams, Security Engineering

Prompt Injection Is a Workflow Problem

Prompt injection succeeds when untrusted instructions are allowed to override system intent. Production applications need controls around user input, retrieved context, tool use, and final responses.

Direct vs. Indirect Attacks

Direct attacks arrive from the user. Indirect attacks arrive from content the application retrieves or processes. Both require classification, isolation, policy decisions, and logging.

Defense Layers

Combine input inspection, context trust scoring, tool-call policy, response review, and red team simulation. No single classifier is enough for applications that touch sensitive data or business systems.

Operational Fit

Security controls should run with low latency and produce evidence for engineers. Blocking, redaction, escalation, and allow decisions must be understandable enough to tune safely.

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