Introduction

We are thrilled to present a groundbreaking milestone in the realm of blockchain transparency and security - the official release of eth-pokhar, a tool designed to help identify entities/pools controlling validators participating in the consensus layer of Ethereum.

This report provides a comprehensive overview of eth-pokhar’s features and capabilities and an example of an analysis that we were able to make with its output. Join us as we delve into the intricacies of this tool and its contribution to the observation of the decentralization of the network.

Tagging methods

The task of tagging validators can be tricky, considering that it relies mostly on a mix of on-chain (transparent) data and off-chain data. Some pools like Lido and Rocketpool have contracts which can be queried to tag the validators that they operate. There are other cases of entities that have made their staking contracts public and can also be identified through this information. Other sources can be used, like data obtained from contacts, graffiti (see example) and deposit patterns like the ones found in this repository: eth-deposits.

When creating validators, an address must deposit 32 ETH on the beacon chain contract. In most cases, entities share the same deposit address throughout multiple validators. By knowing a few of these cases, one can extrapolate the information and identify all of the validators that were generated by those addresses and thus identify the entities.

Tool Features

At the moment of this release, the repository provides the tools to identify the following pools/entities:

• Rocketpool
• Lido
• Coinbase (~half of their validators)

It will generate a table with all the validators and their pool names. The tool will also tag validators based on a list of validators and/or depositors that the user knows are linked to a certain entity/pool. The main objective is to have a database with a list of validators that are generated and tagged automatically.

Some statistics

Utilizing a combination of all of the data sources mentioned before, we managed to identify 86% of the validators. You can see the distribution per entity/pool in the following chart (see monitoreth.io for a live view):

From the ~134k validators that we eth-pokhar did not manage to identify, 58.5k were created by depositor addresses that are responsible for less than 64 validators. We tagged these as solo_stakers. Here’s the distribution of validators per depositor address for these cases:

From this chart, we can see that most of the depositors from the solo_stakers category are condensated in 1-10 validators deposited which is expected considering the amount of stake deposited required to create a validator (32 ETH).

Depositors with at least 64 validators deposited are tagged as whale_0x..... and were grouped up as whales in the distribution figure.

It can be useful to track these whales to see if patterns can be found or if there is any information out there that can be used to identify them.

Disclaimer

As mentioned before, for the identification of most entities, we rely on off-chain data that could be incomplete/incorrect. We are constantly trying to verify and expand our data through contacts. If you have information about an entity that we are missing or if you think that we are making a wrong identification on one or more entities, please contact us so we can improve this service.

Conclusion

The release of eth-pokhar represents a significant leap forward in enhancing Ethereum's security. The tool's ability to tag and identify entities and pools controlling validators, coupled with its impressive 86% identification rate, provides valuable insights into the network's decentralization. While eth-pokhar relies on a mix of on-chain and off-chain data, community collaboration is encouraged to refine its accuracy. Overall, eth-pokhar stands as a crucial asset in promoting transparency, community engagement, and the ongoing pursuit of a more decentralized and secure Ethereum network.