Why We Need an On-chain Fake Wallet Data Analysis Tool

Source: ChainCloud

「Fake Wallet Apps Have Led to Over Ten Thousand People Being Hacked, with Losses of Up to $1.3 Billion」 — This report released by the blockchain security company SlowMist Technology at the end of 2021 shocked the entire blockchain industry. The report mentioned that at the time, hacking incidents caused by downloading fake wallet apps accounted for 61% of all cryptocurrency theft events.

Today, fake wallet scams have not only not subsided, but have instead become increasingly rampant, with more covert methods and larger scales. Faced with this serious challenge, tracking the flow of stolen assets, increasing asset recovery rates, and ultimately deterring attacker behavior have become urgent needs in the industry.

In response to the increasingly prominent issue of fake wallet scams, we decided to first apply our expertise in blockchain big data and AI analysis to this area, successfully exploring the complex operation mode and fund flow pattern of fake wallet scam groups. As a result, we decided to release ChainCloud's first tool — the On-Chain Fake Wallet Data Analysis Tool.

ChainCloud is dedicated to building the next-generation blockchain intelligent big data analysis platform, aimed at providing the entire industry with in-depth and user-friendly data. Through this tool, we hope to contribute to the security of the blockchain ecosystem and, at the same time, lay a 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 great tracking difficulties, and traditional methods are often inadequate:

1. Insufficiency of Traditional Blockchain Explorers

Current blockchain explorers, as basic tools, have significant limitations in tracking complex fund flows. Users need to manually click on each transaction, query the fund flow one by one, and lack visualization tools to help understand the overall fund movement. Especially when funds are dispersed to multiple addresses, the complexity of the tracking process will grow exponentially.

2. Inefficiency and Difficulty of Manual Tracking

Attackers often carry out multiple transfers and complex subsequent operations, greatly increasing the difficulty of manual analysis; funds are often dispersed to thousands of addresses, forming a complex fund network. Ordinary users lack professional knowledge to identify related addresses well, making it almost impossible to fully track these complex fund transfer paths manually.

ChainCloud On-Chain Fake Wallet Data Analysis Tool

Faced with the limitations of traditional methods, a dedicated on-chain fake wallet data analysis tool becomes increasingly necessary. Through analyzing extensive historical data and cases, we have developed the first tool in the ChainCloud toolkit—the 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 will swiftly generate a comprehensive fund flow report, an intelligent analysis graph, and accompanying data tables. It features the following:

1. Automatic Fund Flow Tracking Updates

Real-time monitoring of known fake wallet attacker addresses' activities, automatically identifying and tracing the complete paths of fund dispersal and aggregation, and supporting deep tracking of nested multi-level transfers.

The system can continuously track fund movements, maintaining accurate tracking even within complex transfer networks.

2. Visual Presentation of Complex Data

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

By highlighting key nodes and suspicious patterns, it helps non-technical individuals intuitively understand fund flows, reducing the learning curve and improving tracking efficiency.

3. Robust Address Smart Tagging System

Precisely labeling exchanges, coin mixers, and other key nodes, utilizing innovative color-coded address grouping techniques to visually distinguish address functions and risk levels.

Through AI analysis, addresses are smartly grouped, automatically categorizing addresses with similar behavioral patterns and marking them with a unified color scheme, making complex relationships clear at a glance.

Future Development and Vision

The on-chain fake wallet data analysis tool of ChainCloud is just the beginning of our journey. We are dedicated to building the next-generation blockchain intelligent big data analysis platform, aiming to lower the technical barriers through an intuitive visual interface and natural language explanations, making complex blockchain data easy to comprehend, 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 confidently engage with and benefit from the convenience and value brought by blockchain technology.

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