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🤖 Quality Scan

Quality Scan leverages Wallet Intelligence to provide a comprehensive analysis of a group of wallet addresses, identifying and flagging suspicious behaviors. By analyzing specific bot behavior metrics such as high transaction velocity, timed or continuous transactions, and suspicious wallet networks, developers can gain insights into the prevalence of bots within a specified group of wallets. This bulk analysis helps developers make informed business decisions, enhance platform security, and ensure a more genuine user base by understanding the bot landscape within their audience.

Web3 developers can use Bot Scan in several key scenarios, including:

  • Evaluating Marketing Campaigns: Ensuring that incentives reach genuine users by analyzing participants for bot involvement.
  • Assessing User Base Quality: Periodically reviewing the user base to identify and address any influx of bots, maintaining a high-quality community.
  • Pre-launch Security Checks: Identifying potential bots before launching new features to prevent exploitation.
  • Post-event Analysis: Measuring the success of events and identifying any bot participation.
  • Investment Decisions: Providing insights into user base quality for investors or partners by showcasing the proportion of genuine users versus bots.

Quality Scan helps Web3 developers allocate resources more effectively, improve user targeting, and foster a secure and engaged community by understanding and managing the bot presence within their platform.

Instructions​

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The bot classification provided by Thirdwave's Wallet Intelligence API functions similarly to a spam filter. While it is a powerful tool designed to identify and flag suspicious activity with high accuracy, it is not infallible. False positives and false negatives may occasionally occur due to the complex and evolving nature of bot behavior.

Guidance:

  • False Positives: Some legitimate users may be incorrectly flagged as bots. To mitigate this, rather than outright rejecting these users, consider implementing additional verification steps such as CAPTCHA, email, and phone number verification. This adds a layer of friction that helps to differentiate genuine users from bots without disrupting the user experience.
  • Continuous Improvement: Our bot detection algorithms are continually refined and improved based on new data and patterns. Staying updated with the latest API versions and best practices will help you maintain optimal detection accuracy.

By understanding these nuances, you can better leverage the bot detection capabilities of our API, enhancing your platform's security while ensuring a smooth experience for your legitimate users.

Step 0: Upload Wallet Batch

  • Prepare a list of blockchain wallet addresses in an array format. These may be wallets that have recently connected to your application, signed up for an airdrop, or completed a quest for example. This batch can contain up to 10,000 addresses. Example -->
[
"0xd8da6bf26964af9d7eed9e03e53415d37aa96045",
"0x988527874C7E3f02115F89A6a97135c70B6a47Fc",
...,
"0x5f3fd252caa351a69f5c98b78fd0db71adfe5bea"
]

Step 1: Obtain API Key

Step 2: Construct the API Request

  • Use the multi-wallet endpoint URL https://api.thirdwavelabs.com/evm/wallets/batch.
  • Set the request method to POST.

Step 3: Set Headers

  • Include the X-Api-Key header in your request with your API key as the value.
  • Set the Content-Type header to application/json.

Step 4: Send the Request

  • Execute the request, submitting the array of wallet addresses in the request body.
curl
--request POST 'https://api.thirdwavelabs.com/evm/wallets/batch' \
--header 'X-Api-Key: YOUR_API_KEY' \
--header 'Content-Type: application/json' \
--data '["0xd8da6bf26964af9d7eed9e03e53415d37aa96045","0x988527874C7E3f02115F89A6a97135c70B6a47Fc",...,"0x5f3fd252caa351a69f5c98b78fd0db71adfe5bea"]'

Step 5: Receive and Interpret the Response

  • Upon receiving the response from the API, parse the data into a CSV file or spreadsheet format to analyze the wallet audience in aggregate.
  • Review the botWarning field in each wallet object to identify wallets flagged for suspicious transaction patterns.
  • Calculate the percentage of wallets flagged for suspicious transaction patterns out of the the batch to assess the prevalence of likely bot activity.
[
    {
        "data": {
        "address": "0xd8da6bf26964af9d7eed9e03e53415d37aa96045",
        "firstSeenAt": "2015-09-28T08:24:43.000Z",
        "balance": 3206079.16,
        "hodlerScore": 55,
        "engagementScore": 84,
        "botWarning": false,
        "outboundTransactionValue": 64270664.33,
        "outboundTransactionCount": "1244",
        "transactionPatterns": [
         { "key": "CONTINUOUS", "value": false },
         { "key": "HIGH_VELOCITY", "value": false },
         { "key": "SUSPICIOUS_WALLET_NETWORK", "value": false },
         { "key": "TIMED", "value": false }
         ]
    }
    },
    {
        "data": {
        "address": "0x988527874C7E3f02115F89A6a97135c70B6a47Fc",
        "firstSeenAt": "2021-09-14T12:15:40.000Z",
        "balance": 1476.61,
        "hodlerScore": 98,
        "engagementScore": 99,
        "botWarning": true,
        "outboundTransactionValue": 64270664.33,
        "outboundTransactionCount": "1244",
        "transactionPatterns": [
         { "key": "CONTINUOUS", "value": true },
         { "key": "HIGH_VELOCITY", "value": false },
         { "key": "SUSPICIOUS_WALLET_NETWORK", "value": true },
         { "key": "TIMED", "value": false }
         ]
    }
    },
    {
        ...
    },
    {
        "data": {
        "address": "0x5f3fd252caa351a69f5c98b78fd0db71adfe5bea",
        "firstSeenAt": "2024-04-11T07:18:39.000Z",
        "balance": 1.95,
        "hodlerScore": 63,
        "engagementScore": 22,
        "botWarning": false,
        "outboundTransactionValue": 1.56,
        "outboundTransactionCount": "5",
        "transactionPatterns": [
         { "key": "CONTINUOUS", "value": false },
         { "key": "HIGH_VELOCITY", "value": false },
         { "key": "SUSPICIOUS_WALLET_NETWORK", "value": false },
         { "key": "TIMED", "value": false }
         ]
    }
    }
]
info

If the wallet address provided doesn't exist, wasn't in the correct format, or is not on a supported chain, the response for that entry will be null.

Step 6: Additional Information You can also review the transactionPatterns object in the response for more detailed insights into specific transaction patterns detected.

  • High Transaction Velocity - Spot bots through analysis of unnaturally high transaction rates.
  • Timed Transactions - Detect bots by observing consistent, timed activities.
  • Continuous Transactions - Classifies uninterrupted and perpetual engagement, distinguishing genuine user interactions from automated engagements, bolstering platform security against disruptive bot activities.
  • Suspicious Funding Network - Identify bots through their initial funding patterns, even with minimal or no transaction history.

Outcome​

By conducting a Quality Scan using Thirdwave's Wallet Intelligence API, developers can gain insights into the presence of potential bots or specific suspicous transaction pattenrns within a specified group of wallets. This information can inform business strategies and security measures to maintain a healthy and trustworthy ecosystem.