Why do we need to create an on-chain fake wallet data analysis tool?

Original source: ChainCloud

"Fake wallet apps have led to over ten thousand people being stolen from, with losses reaching as high as 1.3 billion dollars" - This report released by the blockchain security company Slow Mist at the end of 2021 shocked the entire blockchain industry. The report mentioned that at that time, theft incidents due to downloading fake wallet apps accounted for 61% of all cryptocurrency theft incidents.

As of today, fake wallet scams have not only not diminished, but have become increasingly rampant, with more covert methods and larger scales. In the face of this severe challenge, tracking the flow of stolen assets, improving asset recovery rates, and ultimately deterring attackers' behavior has become an urgent need for the industry.

In response to the increasingly prominent issue of fake wallet scams, we have decided to first apply our expertise in blockchain big data and AI analysis capabilities to this field, successfully exploring the complex operation patterns and funding flow rules of fake wallet scam gangs. Therefore, we have decided to release the first tool of ChainCloud - the on-chain fake wallet data analysis tool.

ChainCloud is committed to building the next generation of blockchain intelligent big data analysis platform, aiming to provide in-depth and user-friendly data for the entire industry. Through this tool, we hope to contribute to the security of the blockchain ecosystem while laying the foundation for ChainCloud's more comprehensive data services in the future.

Limitations of Traditional Tracking Methods

After a fake wallet scam occurs, victims often face tremendous difficulties in tracking, and traditional methods are often powerless.

1. The shortcomings of traditional blockchain explorers

The current block explorer, as a basic tool, has obvious limitations when tracking complex flows of funds. Users need to manually click on each transaction to query the flow of funds one by one, and there is a lack of visualization tools to help understand the overall movement of funds. Especially when funds are dispersed across multiple addresses, the complexity of the tracking process will increase geometrically.

2. The inefficiency and difficulty of manual tracking

Attackers often conduct multiple transfers and engage in complex follow-up operations, significantly increasing the difficulty of manual analysis; funds are often dispersed to thousands of addresses, forming a complex network of funds. Ordinary users lack the expertise to effectively identify associated addresses, making it nearly impossible to fully track such complex fund transfer paths manually.

ChainCloud On-Chain Fake Wallet Data Analysis Tool

In light of the limitations of traditional methods, a professional on-chain fake wallet data analysis tool is particularly necessary. By analyzing a large amount of historical data and case studies, we developed the first tool in the ChainCloud toolbox - an intelligent analysis system for on-chain fake wallet data.

Users only need to input the address from which assets were stolen by a fake wallet, and the system can generate a complete fund flow report, intelligent analysis chart, and supporting data tables in a short period of time. It has the following features:

1. Automatic tracking and updating of fund flows

Real-time monitoring of known fake wallet attackers' address activities, automatically identifying and tracking the complete path of fund dispersion and aggregation, supporting deep tracking of nested multi-layer transfers.

The system can continuously track the flow of funds, maintaining accurate tracking even within complex transfer networks.

2. Visual presentation of complex data

Transform abstract addresses and transactions into an intuitive network graph, clearly displaying the entire process of fund dispersion and aggregation.

By highlighting key nodes and suspicious patterns, it helps non-technical personnel to intuitively understand the flow of funds, reduces the usage threshold, and improves tracking efficiency.

3. Powerful address tagging system

Accurately mark key nodes such as exchanges and mixing services, and use innovative colored address grouping technology to visually differentiate address functions and risk levels through different colors.

Based on AI analysis, addresses are intelligently grouped, automatically classifying addresses with similar behavior patterns and marking them with a unified color tone, making complex relationships clear at a glance.

Future Development and Vision

ChainCloud's on-chain fake wallet data analysis tool is just the starting point of our journey. We are committed to building the next generation of blockchain intelligent big data analysis platforms, hoping to lower the technical barriers through an intuitive visual interface and natural language explanations, making complex blockchain data easy to understand and providing users with personalized data insights.

We believe that through these efforts, we can effectively address the increasingly complex security challenges in the blockchain field, allowing users to participate in and enjoy the conveniences and values brought by blockchain technology with peace of mind.

：