---
sidebar_label: Guides
title: Red Teaming Guides
description: Step-by-step tutorials for red teaming LLM applications, testing guardrails, and finding vulnerabilities before deployment
---

# Red Teaming Guides

Practical tutorials for finding vulnerabilities in LLM applications before deployment. Each guide walks through a real-world scenario with working configuration examples you can adapt to your own use case.

## Getting Started

- [How to Red Team LLM Applications](/docs/guides/llm-redteaming) — End-to-end guide to adversarial testing
- [Testing Guardrails](/docs/guides/testing-guardrails) — Evaluate content safety guardrails

## By Application Type

- [RAG Red Teaming](/docs/red-team/rag) — Test retrieval-augmented generation for prompt injection, context manipulation, and data poisoning
- [Agent Red Teaming](/docs/red-team/agents) — Test LLM agents for privilege escalation, context poisoning, and memory manipulation
- [MCP Security Testing](/docs/red-team/mcp-security-testing) — Secure Model Context Protocol servers through red teaming and tool poisoning tests
- [Red Teaming a Chatbase Chatbot](/docs/guides/chatbase-redteam) — Security test a production chatbot

## Specialized Testing

- [Multi-Modal Red Teaming](/docs/guides/multimodal-red-team) — Test image and multi-modal AI systems
- [Foundation Model Red Teaming](/docs/red-team/foundation-models) — Assess foundation model security risks through red teaming and static scanning
- [Evaluating Safety with HarmBench](/docs/guides/evaling-with-harmbench) — Benchmark LLM safety using HarmBench
- [Testing Google Cloud Model Armor](/docs/guides/google-cloud-model-armor) — Assess Google Cloud's AI safety layer

## Ongoing Security

- [LLM Supply Chain Security](/docs/red-team/llm-supply-chain) — Detect trojans, backdoors, and safety regressions in your LLM supply chain
- [Detecting Model Drift](/docs/red-team/model-drift) — Monitor LLM security posture over time by running red team tests repeatedly