> ## Documentation Index
> Fetch the complete documentation index at: https://docs.getnetra.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Overview

> Test your AI agents for safety vulnerabilities with Netra's red teaming framework. Run adversarial attacks, judge responses, and track safety scores over time.

AI agents can be manipulated. Adversarial users craft prompts that bypass safety guardrails, extract system prompts, and force harmful outputs. Netra's Red Teaming framework lets you find these vulnerabilities before your users do — systematically, repeatedly, and at scale.

## Why Red Teaming Matters

Without adversarial testing, you cannot know how your agent behaves under attack. Netra helps you answer critical safety questions with confidence:

| Question                                 | What Netra Tests                                    |
| ---------------------------------------- | --------------------------------------------------- |
| Can my agent be jailbroken?              | Adversarial attacks across multiple risk categories |
| Does my agent leak its system prompt?    | System prompt leakage evaluators                    |
| Is my agent safe across risk categories? | Suites aligned to security frameworks               |
| How has safety changed over time?        | Risk score trending with historical comparison      |

## Core Building Blocks

The Red Teaming suite is built on three interconnected pillars:

### Suites & Evaluators

[Suites & Evaluators](/Redteaming/Suites-and-Evaluators) form the adversarial test catalog. **Evaluators** define individual attack categories — each with a generation template for creating adversarial prompts and a grader rubric for judging agent responses. **Suites** bundle related evaluators into curated groups aligned to security frameworks.

### Setup

A [Setup](/Redteaming/Configs) is a reusable test configuration. It connects a specific agent to selected evaluators, an attacker LLM (for generating adversarial prompts), and a judge LLM (for scoring agent responses). You also choose between single-turn and multi-turn attack modes.

### Runs & Results

A [Run](/Redteaming/Runs) executes all adversarial prompts from a setup against the target agent. Each prompt is sent to the agent, the response is judged by the LLM, and a pass/fail/error result is recorded. Runs execute asynchronously with queue-based concurrency control.

## Execution Modes

Netra supports two attack strategies, each suited to different risk scenarios:

| Mode            | When Used                       | Behavior                                                                                 |
| --------------- | ------------------------------- | ---------------------------------------------------------------------------------------- |
| **Single-turn** | Default for standard evaluators | One adversarial prompt is sent to the agent. The judge scores the single response.       |
| **Multi-turn**  | Turn type set to multi          | The attacker LLM sustains a conversation for N turns. Each turn is judged independently. |

## End-to-End Flow

The red teaming pipeline follows this sequence:

<Steps>
  <Step title="Create a Setup">
    [Create a setup](/Redteaming/Configs) for your agent. Choose the attack type, number of tests, and configure the attacker and judge LLMs.
  </Step>

  <Step title="Select Suites & Evaluators">
    Explore [suites & evaluators](/Redteaming/Suites-and-Evaluators) and select the attack categories that match your risk profile.
  </Step>

  <Step title="Generate Adversarial Prompts">
    Trigger [prompt generation](/Redteaming/Configs#prompt-generation). The attacker LLM generates targeted adversarial prompts for each evaluator.
  </Step>

  <Step title="Run the Test">
    [Start a run](/Redteaming/Runs). Each prompt is sent to the agent, the response is judged, and a pass/fail result is recorded.
  </Step>

  <Step title="Review Results and Risk Scores">
    View per-prompt [results](/Redteaming/Runs#viewing-results) and monitor your [risk scores](/Redteaming/Risk-Scores) over time.
  </Step>
</Steps>

## Getting Started

<Steps>
  <Step title="Create a Setup">
    [Create a setup](/Redteaming/Configs) for your agent. Choose attack type, number of tests, and configure the attacker and judge LLMs.
  </Step>

  <Step title="Select Suites & Evaluators">
    Navigate to **Red Teaming** and explore [suites & evaluators](/Redteaming/Suites-and-Evaluators). Select a suite or pick individual evaluators that match your risk profile.
  </Step>

  <Step title="Generate Adversarial Prompts">
    Trigger [prompt generation](/Redteaming/Configs#prompt-generation). Netra uses the attacker LLM and each evaluator's template to generate targeted adversarial prompts.
  </Step>

  <Step title="Run the Red Team Test">
    [Start a run](/Redteaming/Runs). Each adversarial prompt is sent to your agent. The judge LLM scores every response.
  </Step>

  <Step title="Review Results and Risk Scores">
    View per-prompt [results](/Redteaming/Runs#viewing-results), track [progress](/Redteaming/Runs#progress-tracking), and monitor your [risk scores](/Redteaming/Risk-Scores) over time.
  </Step>
</Steps>

## Related

<CardGroup cols={2}>
  <Card title="Suites & Evaluators" icon="shield-check" href="/Redteaming/Suites-and-Evaluators">
    Browse the adversarial test catalog and select attack categories.
  </Card>

  <Card title="Setup" icon="gear" href="/Redteaming/Configs">
    Create reusable test setups that connect agents to evaluators.
  </Card>

  <Card title="Runs & Results" icon="play" href="/Redteaming/Runs">
    Execute red team tests and view per-prompt pass/fail results.
  </Card>

  <Card title="Risk Scores" icon="chart-line" href="/Redteaming/Risk-Scores">
    Track your agent's safety posture over time with aggregated scores.
  </Card>
</CardGroup>