Skip to main content

make first and simple checks for wallets trasactional relations to grantees/donnors on public funding rounds onchain

Project description

Sybil Checks Package

pip install SybilChecks

from SybilChecks import checks

Intro

This package was developed during ODC Data Builders Hackathon on Jan-2023, OpenData Community . It intends to make it easier to do first basic checks on donors of public funds rounds. It can integrate systems of risk analysis as a ‘Lego’ for feature engineering or as a start for further data analysis on wallets. It cointans 5 functions, 4 of them tests behaviours and flags booleans outputs for the behaviour tested ,and 1 returns a dataset of historical transactional data till the current date.

The functions were based on previous experience on web2 fraud detection and prevention, for example account_age analogue to first_trx_during_round function on this context, and exclusive on-chain feature peculiarities as in wallet_initiated_by to check close relations between different donors and grantees.

One principle that I kept in mind during the construction of this package was the ‘easy to use’ principle in an attempt that round owners, data analysts or people with little experience could run it and culminate in Sybil identification.

Why use it

In the context for this package was developed, Sybil attack is a kind of fraud in which the attacker seeks an ROI over each donation in a public funds round. To maximise that, the attackers create fake wallets to make donations, as the quadratic voting system used to distribute the funds, prioritise the distribution of funds due to majority preferences. For more information, please check ODC FAQs where you can find resources explaining this fraud.

Giving attackers must split their funds through various accounts, the benefits in using this package is to enhance the cost of forgery for fraudsters as, for example, they will be forced to:

  • Initiate wallets and wait till rounds being announced as initiating wallets during the round could flag them and indicate their presence. This could enhance their risk as money would be stuck in these wallets while markets fluctuates.
  • Enhance their ‘fake wallets layers’ as they will need to perform at least one transaction between the wallets that distribute the funds, and the wallets that make donations. Forcing the wallets that distribute the funds to not make donations on the round otherwise it could be flagged too.
  • Fraudsters' wallets that made donations would be forced to not transact between them otherwise they would be flagged too.

As fraudsters would try to avoid being flagged and good users would not, the cost of forgery would enhance, but not the current cost of making donations as a good user.

When use it

Round owners can elaborate on the moment to use the package giving their other algorithms and preventing systems. For example, they could run the first_trx_during_round and the wallet_initiated functions on every new wallet that makes donations to the round even in real time, and the wallets_trx_during_round every x hours to verify suspicious interactions.

They could test too differents relations like confront transactions:

  • grantees x grantees
  • donors x grantees
  • grantees X donors

This could be done in different moments for different relations

How it works

The package was created using Covalent API, a decentrilized network of nodes, therefore it is imperative that the users get an <api_key> , as it is a necessary variable on every function.

Functions variables :

wallet_id = type: ‘str’, wallet address that will be evaluated
api_key = type: ‘str’, your covalent api_key
chain_id = type: ‘str’, covalent id for the network you want the historical transactions
round_start = type: ‘str’, format : ‘%Y-%m-%d’, date of the round start or date when the round was announced. Example : ‘2022-12-05’
round_finish = type: ‘str’, format : ‘%Y-%m-%d’, date of the round end or date when donors were not able to make donations anymore. Example : ‘2022-12-31’
list_for_testing = type : ‘list’, present on the wallet_initiated module, it should contain a list of unique wallet addresses of donors and grantees but not the wallet tested .
wallets_lists = type : ‘list’, present on the wallet_historical_trx module, it should contains all wallets address that is intended to get the lifetime transactional data on the specified chain_id

Functions:

first_trx_during_round(wallet_id, api_key, chain_id, round_start, round_finish):
Function tests if the wallet was ‘initiated’ (tried its first transaction), on the specific chain tested, during the period specified. This module does not distinguish between failed or successful transactions. Output: list['wallet_id', True/False]

wallet_initiated_by(wallet_id, api_key, chain_id, list_for_testing) :
Function tests if the first funds were received by one of the wallets in the <list_for_testing> variable . It returns ‘True’ only if the first successful and not ‘0’ value transaction was made by some of the wallets in the list. Output: list['wallet_id', True/False]

Example:
Trx_1 : from x_wallet / successful : False / value: 1 (function will discart)
Trx_2 : from x_wallet / successful : True / value: 0 (function will discart)
Trx_3 : from n_wallet / successful : True / value: 10 (function will accept)
If list_for_testing contains 'n_wallet' then module returns True

trx_between_wallets(wallet_id, api_key, chain_id, list_of_donors) :
Function tests if round donors have transitioned between themselves, there is not distinction between successful and failed transactions nor about when these transactions occurred. In this module wallet_id must be in list_of_donors. Output: list['wallet_id', True/False]

wallets_trx_during_round(wallet_id, api_key, chain_id, round_start, round_finish, list_of_donors) :
Function tests if round donors have transitioned between themselves during the period of grant round or announcement of the round, there is no distinction between successful and failed transactions. wallet_id must be in list_of_donors. Output: list['wallet_id', True/False]

wallet_historical_trx(wallets_list , api_key, chain_id):
This function was developed to make it easier to get historical transactional data from a list of wallets. It bridges the gap between the API usage and a final treated dataset.

Further development:

The package has little study around time optimization due to hackathon time constraints. It can be slow when used to check a lot of wallets owing to making one API call for each function ‘check’. Further development would include:

  • modules to import and treat a dataset and use it to retrieve the validations for the other modules.
  • One module that builds and processes networks algorithms and returns network metrics as degree of centrality, closeness and so on ..

Acknowledgements to:

  • Covalent Network, due to the service and support on their discord
  • Simon from 0x9simon due to his discussion around Gas Provision Network. It inspired the construction of the module ‘wallet_initiated’

If you want to contribute, please contact Stefi :)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

SybilChecks-0.0.6.tar.gz (7.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

SybilChecks-0.0.6-py3-none-any.whl (6.6 kB view details)

Uploaded Python 3

File details

Details for the file SybilChecks-0.0.6.tar.gz.

File metadata

  • Download URL: SybilChecks-0.0.6.tar.gz
  • Upload date:
  • Size: 7.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.13

File hashes

Hashes for SybilChecks-0.0.6.tar.gz
Algorithm Hash digest
SHA256 a08647f75b57a08a11be8d41eb9abbe9a18408e0d6da778127dc637ea97b538c
MD5 0991d93f8e8e169058375736b48e5b74
BLAKE2b-256 d9af5e113af0a0dbf738adae77ed023a941dca71092244fbe5f47c011e6318d9

See more details on using hashes here.

File details

Details for the file SybilChecks-0.0.6-py3-none-any.whl.

File metadata

  • Download URL: SybilChecks-0.0.6-py3-none-any.whl
  • Upload date:
  • Size: 6.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.13

File hashes

Hashes for SybilChecks-0.0.6-py3-none-any.whl
Algorithm Hash digest
SHA256 6ba449731549638f5866806445485c2291b0e61de43f930ea0043a885f3aa898
MD5 c8b92f2cb8e5b7cb82d9ad8bf868ffb0
BLAKE2b-256 1473de4d1c857a2711fd9335c070488f6a0f04d7c299ff666aa2db98815faad7

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page