# Sybil

Sybil attacks—where a single actor controls multiple wallets to exploit incentive structures—can undermine incentives. OpenBlock Labs employs advanced algorithms to detect and mitigate Sybil activity, ensuring the fair distribution of rewards in incentive programs like airdrops and liquidity mining campaigns.

#### Detection Methodology

This is a high level overview of the OpenBlock Sybil Methodology:

1. **Graph Construction**: We create an Asset Transfer Graph (ATG) that helps identify clusters of wallets that may be controlled by the same actor.
2. **Behavioral Analysis**: Once potential Sybil clusters are detected, we analyze the wallets in each cluster—looking for high level similarities and anomalies such as non-human type behavior.
3. **Quality Assurance**: Our algorithms produce negligible false positive rate. However, to reduce it further, we apply both automated and manual QA to our results. We always prioritize precision.


---

# 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.openblocklabs.com/intelligence-models/sybil.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.
