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

# Custom Vulnerability

> Define and test custom vulnerability categories specific to your AI application's unique risk profile.

## What is a Custom Vulnerability?

A **Custom Vulnerability** is a user-defined attack category that extends beyond the standard vulnerability taxonomy. Every AI application has a unique risk profile shaped by its domain, users, data, and deployment context. Custom vulnerabilities allow you to define, describe, and red-team attack vectors specific to your application that may not fit neatly into predefined categories.

## Why It Matters

Standard vulnerability categories cover common attack patterns, but real-world AI applications face unique risks:

* **Domain-specific threats** — A healthcare AI faces different risks than a financial AI or a customer service chatbot.
* **Business logic abuse** — Custom business rules create unique attack surfaces that generic tests won't cover.
* **Regulatory specificity** — Different industries have specific compliance requirements that need targeted testing.
* **Evolving threats** — New attack techniques emerge faster than taxonomies can be updated.
* **Organizational context** — Internal policies, data sensitivity levels, and user populations create unique risk profiles.

## How to Use Custom Vulnerabilities

### Define the Vulnerability

Clearly describe the attack category:

* **Name** — A descriptive name for the vulnerability
* **Description** — What the vulnerability is and how it manifests
* **Risk level** — The potential impact if the vulnerability is exploited
* **Attack examples** — Concrete examples of how an attacker might exploit this vulnerability

### Create Test Cases

Design evaluation prompts that probe for the vulnerability:

* Direct attack prompts that test the vulnerability head-on
* Indirect approaches that probe for the vulnerability through context or framing
* Edge cases that test boundary conditions specific to your application

### Evaluate and Iterate

Use Know Your AI's evaluation framework to:

* Run custom vulnerability tests against your AI system
* Analyze pass/fail rates and identify weaknesses
* Iterate on both the vulnerability definition and your defenses

## Example Custom Vulnerabilities

| Custom Vulnerability        | Domain        | Description                                                             |
| --------------------------- | ------------- | ----------------------------------------------------------------------- |
| **Treatment Hallucination** | Healthcare    | AI suggests non-existent medical treatments or incorrect dosages        |
| **Portfolio Manipulation**  | Finance       | AI provides investment advice designed to benefit a specific party      |
| **Curriculum Deviation**    | Education     | AI teaching assistant deviates from approved curriculum content         |
| **Spoiler Leakage**         | Entertainment | AI reveals plot spoilers or unreleased content from embargoed materials |
| **Recipe Safety**           | Food/Cooking  | AI suggests dangerous food combinations or ignores allergy warnings     |

## Getting Started

1. **Identify your unique risks** — Review your application's domain, data, and user base for threats not covered by standard categories
2. **Document the vulnerability** — Write a clear description, impact assessment, and example attack scenarios
3. **Create evaluation datasets** — Build a set of test prompts that comprehensively probe the vulnerability
4. **Run evaluations** — Use Know Your AI to test your AI against the custom vulnerability
5. **Refine defenses** — Based on results, strengthen your guardrails and re-test iteratively