# AquilaX Securitron

<img src="/files/OaZQ5RNPfqDfel5XeKCZ" alt="AquilaX Securitron Training Loop" class="gitbook-drawing">

AquilaX powers across two core domains:

1. **All in one scanner**: Utilizing eight security scanners for code base assessment.
2. **AI Engine Securitron**: A highly trained model specialized in application security (AppSec).

Securitron has been trained on over 300 million open-source projects, learning from their source code and identified security vulnerabilities. It has also been meticulously trained on the triaging work performed by leading cybersecurity engineers. As a result, Securitron is the first AI engine on the market extensively trained on billions of data points, enabling it to reason like a human security expert.

This dataset includes:

1. Source Code snippets
2. Identified vulnerabilities
3. Triage results from top security engineers
4. Tags categorizing findings as:
   * False Positive
   * False Negative
   * True Positive
   * True Negative
   * Undefined

This dataset is pivotal in training our **Securitron** model. Securitron plays a crucial role in assessing new vulnerabilities, distinguishing between False and True Positives, offering an unparalleled contextual understanding.

Moreover, Securitron features a Chat component serving as both API and UI. This allows AquilaX users to interact, gain insights into vulnerabilities, understand why certain findings are True Positives, and learn effective mitigation strategies.

Continuous training of Securitron ensures it evolves with each new triage performed by our security engineers, facilitating ongoing improvements in our system.


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.aquilax.ai/blog/aquilax-securitron.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.