API Reference

What is Bundling

General information about bundling and our advanced analysis - supported on the Solana network

Introduction

In the evolving landscape of blockchain technology, ensuring transaction transparency and security is paramount. A prevalent tactic known as "bundling" involves developers or malicious actors executing multiple transactions in rapid succession, often within the same block or time slot, to manipulate token distribution or obscure fraudulent activities. Recognizing the need to identify and mitigate such practices, Webacy has introduced a robust Bundling Detection feature for Solana.

What is Bundling?

Bundling refers to the practice of grouping multiple transaction instructions into a single transaction or executing several transactions almost simultaneously. This method can be employed for legitimate purposes, such as preventing snipers from acquiring large token amounts during a launch. However, it can also be misused to manipulate token distribution or conceal malicious activities. For instance, orchestrated mass sniping involves queuing multiple buys to execute within the same 0.4 seconds, making it challenging to distinguish between genuine and fraudulent transactions.

How Webacy's Bundling Detection Works

Webacy's Bundling Detection feature analyzes transaction patterns in real-time to identify potential bundling activities. By examining factors such as the number of unique wallets transacting within a specific time slot, the total amount of cryptocurrency spent, the current holdings of these wallets, who funded them, along with many other factors, the system can flag suspicious bundling behavior. This comprehensive analysis enables users to assess the legitimacy of transactions and take appropriate action when necessary.

Key Features

  • Real-Time Monitoring: Continuously scans newly created tokens to detect bundling activities as they occur.
  • Detailed Analysis: Provides insights into each detected bundle, including the number of unique wallets involved, the total amount spent, and the current holdings of these wallets.
  • Developer-Friendly Interface: Presents data in an accessible response format, allowing devs to quickly understand and respond, or traders to make better-informed decisions.

Considerations

While Webacy's Bundling Detection feature is designed to identify suspicious bundling activities, it's important to note that not all detected bundles are indicative of malicious intent. For example, high-demand token launches may result in multiple unrelated wallets transacting within the same time slot. Therefore, it's crucial to analyze the context of each detected bundle and consider additional factors before drawing conclusions.

Also note that this feature has been released for Solana only. If you'd like to request this analysis on other chains, please get in touch.

Conclusion

Webacy's Bundling Detection feature enhances blockchain security by providing users with the tools to identify and analyze bundling activities. By leveraging this feature, users and developers can gain deeper insights into transaction patterns, enabling them to make informed decisions and maintain the integrity of their blockchain interactions.

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The bundling analysis is available in our Threat Risks endpoint.

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Try these addresses!

HeVfXofCHHh2mzmHvs1GCJfs11fvrtLY9oCxea1gpump
3n47zcaEjhw2axMxaKKmJXr6KwAcZtv1zMHvKuE9pump

Example Data Return

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Important Field

Many customers start by implementing the bundled_percentage_supply_bought field. This displays the percentage of the initially acquired supply was purchased in a bundled scheme.

{
"token_address": "313H2Zn8DtdKRKgHuQq8obv52xTNQFkmPR3DySVvpump",
"token_mint_tx": "2MXBvAVWNxHCNF6RUFvzgWLxErNJYJ8HwwKgQ7posE1vVEz6tFnA24xonRTmYhf3MtCTWUbSG5KCtib9fAV8rvSQ",
"token_mint_time": "2025-01-15T21:21:14.000Z",
"minter": "3BGxK4wDHwM5ebniXGqmEHo9nsXHD9xifgxjfc9AV5r4",
"first_buyers_analysis": {
	"timestamp": "2025-01-15T23:24:43.033Z",
	"buyers_analyzed_count": 100, # sample size
	"buys_in_same_block_count": 6, # how many of the buyers_analyzed_count bought in the same block (in any of the first N buys)
	"biggest_funder_sol_amount": 78.2, # the address that funded most of these first buyers, how much SOL did it transfer to them in total
	"biggest_funder_sol_address": "3BGxK4wDHwM5ebniXGqmEHo9nsXHD9xifgxjfc9AV5r4", # the address related to biggest_funder_sol_amount
	"buyers_still_holding_count": 32, # how many of first buyers_analyzed_count are still holding
	"current_holding_percentage": 19.2, # percentage still held of the supply held by the first analyzed buyers
	"distinct_funders_sol_count": 225, # how mnay different addresses sent any sol to the first buys
	"biggest_funder_token_address": "3BGxK4wDHwM5ebniXGqmEHo9nsXHD9xifgxjfc9AV5r4", # addres that sent the most tokens to the buyers
	"buyers_transferred_out_count": 2, # how many of the first buyers_analyzed_count have transferred out funds to other wallets
	"distinct_funders_token_count": 1, # how many different addresses sent any of the analyzed token to the first buyers
	"initially_acquired_percentage": 75.99, # how much of the total supply did these buyers acquire (sum of total buy amounts divided by total supply)
	"biggest_funder_sol_funded_count": 20, # the address that funded most of these first buyers, how much SOL did it transfer to them in total? 
	"average_percentage_bundler_buyer": 1.2, # from the bundled buys, what was the average percentage of the supply acquired (this is only calculated from buys that have other buys in the same block - bundled)
	"bundled_percentage_supply_bought": 13.16, # how much from the initially_acquired_percentage was acquired in a bundle scheme. (this only considers buys from blocks that have 2+ buys in that block)
	"biggest_funder_token_funded_count": 20, # the address that funded most of these first buyers, how much analyzed_token did it transfer to them in total?
	"transfers_in_same_block_sol_count": 81, # how many sol transfers happened in the same block, for blocks with 2+ transfers
	"transfers_in_same_block_token_count": 20, # same as above but for analyzed token
	"bundled_percentage_supply_transfered": 6.06,
	"biggest_funder_supply_percentage_token": 6.06, 
	"distributed_to_distinct_addresses_count": 201, # to how many different addresses were tokens distributed after the first buyers bought
	"transferred_out_from_initially_acquired_percentage": 57.78
},
	"holder_group_analysis": {
		"suspicious_groups": [
			{
				"average_percentage_per_holder": 0.34,
				"bundled_percentage_supply_transfered": 57.13,
				"balance_from": 1000000000000,
				"balance_to": 10000000000000,
				"count": 201,
				"total_balance": 687425095454604,
				"supply_percentage": 68.74,
				"distinct_funders_sol_count": 3,
				"biggest_funder_sol_amount": 81.51333332400024,
				"biggest_funder_sol_transfer_count": 257,
				"biggest_funder_sol_funded_count": 198,
				"biggest_funder_sol_address": "3BGxK4wDHwM5ebniXGqmEHo9nsXHD9xifgxjfc9AV5r4",
				"transfers_in_same_block_sol_count": 18,
				"distinct_funders_token_count": 1,
				"biggest_funder_token_address": "3BGxK4wDHwM5ebniXGqmEHo9nsXHD9xifgxjfc9AV5r4",
				"biggest_funder_token_transfer_count": 198,
				"biggest_funder_supply_percentage_token": 0,
				"transfers_in_same_block_token_count": 40,
				"biggest_funder_token_funded_count": 198,
				"timestamp": "2025-01-15T23:51:19.964Z"
			}
		]
	}
}