> For the complete documentation index, see [llms.txt](https://docs.salusec.io/untitled/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.salusec.io/untitled/lightning-cat/machine-learning.md).

# Machine Learning

Salus Lightning Cat employs machine learning techniques for smart contract vulnerability detection. **We have trained three deep learning models for detecting vulnerabilities in smart contracts: Optimized-CodeBERT, Optimized-LSTM, and Optimized-CNN.** To accurately extract vulnerability features, we obtain code snippets from vulnerable functions, preserving key vulnerability characteristics. By leveraging the CodeBERT pre-trained model for data preprocessing, we can more accurately capture the syntax and semantics of the code, thereby **improving the performance of vulnerability detection.**

<figure><img src="/files/AFv4hyfiu8762IY0rPp2" alt=""><figcaption></figcaption></figure>


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## 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.salusec.io/untitled/lightning-cat/machine-learning.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.