How to Get All-Round Protection for Web3 Transactions? Complete Analysis of GoPlus Security Layer Risk Identification Mechanism

The rapid development of the Web3 ecosystem has been accompanied by a simultaneous escalation of security threats. From phishing attacks and malicious contracts to wallet theft and rug pulls, on-chain risk patterns are becoming increasingly complex and covert. In June 2026, GoPlus Security disclosed a series of AI-driven smart contract vulnerability attacks: on June 9, the Token of Power (TOP) contract deployed 7 years ago was attacked on Ethereum, resulting in a loss of approximately $1.5 million; on May 25, the WUSD.fi contract deployed 3 years ago was attacked, resulting in a loss of approximately $200k; on June 14 and June 18, Aztec Network was attacked twice in a row due to old contracts deployed 2 years ago, with total losses exceeding $4 million. Traditional security audit models struggle to effectively cover legacy contracts, while attackers are using AI technology to quickly discover and exploit these vulnerabilities.

Against this backdrop, GoPlus Security, as the first decentralized security layer in Web3, has evolved since 2022 from a Web3 user security infrastructure provider into a comprehensive security network covering over 30 blockchain networks. Its security APIs process tens of millions of requests daily, protecting over 12 million wallet addresses and identifying over 800k malicious assets. As of July 6, 2026, according to Gate market data, GoPlus Security (GPS) is priced at $0.009350, with a 24-hour trading volume of $2.3175 million and a total supply of 10.00 billion tokens. Focusing on GoPlus's four core modules—real-time risk scanning system, address behavior analysis model, DApp security detection mechanism, and data-driven security network—an analysis of its on-chain risk identification mechanism's operational logic is provided.

Real-Time Risk Scanning System: Security Gate Before Transaction Execution

One of the core capabilities of the GoPlus security network is performing risk scanning and assessment before each on-chain transaction is executed. This mechanism relies on the GoPlus Intelligence risk analysis engine, providing real-time security intelligence for AI agents, Web3 users, wallets, applications, blockchains, and developers.

Multi-dimensional API Risk Coverage. GoPlus provides a comprehensive suite of real-time risk scanning APIs covering multiple dimensions, including token security, malicious address detection, NFT security, authorization risk analysis, DApp security information, signature data decoding, and phishing site detection. Among them, the token security API can detect rug pulls, scams, and tokens with hidden tax risks; the malicious address API maintains a continuously updated library of malicious wallet addresses; the NFT security API can verify NFT authenticity and identify counterfeit collections.

Transaction Simulation: A Key Step for Risk Rehearsal. In May 2026, GoPlus released a secure transaction simulation API that supports pre-simulating transactions in the EVM and Solana ecosystems. This feature can evaluate execution results and detect potential risks before a transaction is on-chain, covering risks such as addresses, contracts, tokens, URLs, and slippage, and returns multi-dimensional security detection results including risk type, risk level, risk details, and suspicious addresses. This mechanism allows users to learn about potential risks before signing a transaction, effectively avoiding asset losses caused by malicious contracts or phishing signatures.

Scalable Real-Time Response Capability. According to CoinDesk research, the daily average call volume of GoPlus Intelligence's token security API in 2025 reached 717 million, with a peak of nearly 1 billion in February; the monthly average additional all-chain requests including transaction simulations reached 350 million. As of 2026, GoPlus's daily API call volume has reached 30 million. This level of data processing capability enables its risk scanning system to complete comprehensive risk assessments of transactions at the millisecond level.

Address Behavior Analysis Model: From Static Labels to Dynamic Profiles

Address behavior analysis is another key module in the GoPlus security system. Unlike traditional security solutions that rely on static blacklists, GoPlus's address behavior analysis model builds dynamic risk profiles by continuously tracking on-chain address transaction patterns, interaction objects, and fund flows.

Eight-Dimension Risk Detection. In August 2025, GoPlus launched the on-chain address scan API (Address Scan API), which can perform eight-dimensional risk detection for a single address in scenarios such as transfers, transactions, and receipts, including address poisoning, recipient risk, risky transaction counterparties, abnormal gas fees, stablecoin risk, NFT poisoning, authorization risk, and asset risk analysis. Among them, asset risk analysis covers both token and NFT dimensions, identifying token contract risks, stablecoin de-pegging risks, and NFT poisoning and theft issues.

Dynamic Update Mechanism for Malicious Address Database. GoPlus's malicious address API provides a free, comprehensive, and real-time updated malicious address database. This database is not a one-time static dataset but is dynamically iterated through continuous monitoring of on-chain behavior, community feedback, and security incident reports. When an address is identified as being associated with known attack incidents, phishing activities, or fraudulent behavior, it is added to the malicious address database and triggers warnings in subsequent transaction scans.

From Individual Address to Network Association Analysis. The address behavior analysis model not only focuses on the risk attributes of a single address but also analyzes the relationships between addresses through on-chain transaction graphs. The risky transaction counterparty detection dimension can identify addresses that have fund flows with known malicious addresses, thereby discovering potential risk transmission paths at an earlier stage. This network association-based analysis method enables GoPlus to detect addresses that have not yet been directly flagged as malicious but exhibit abnormal risk behavior patterns.

DApp Security Detection Mechanism: Application-Layer Risk Filtering

As the main entry point for users to interact on-chain, the security of DApps directly affects the security of user assets. GoPlus's DApp security detection mechanism provides a security barrier for user DApp interactions through multi-source data aggregation and real-time risk assessment.

DApp Security Information API. GoPlus's DApp Security Information API aggregates security information from multiple DApps, providing rapid risk warnings and insights to ensure safe user interactions. This API comprehensively evaluates DApps from multiple dimensions, including contract code security, historical audit records, user feedback, and on-chain behavior data.

Integration Practices with Leading Platforms. GoPlus's security capabilities have been integrated by multiple leading Web3 platforms. DexScreener has built a unique token security detection system with the help of GoPlus Security, enhancing user trust through GoPlus's security capabilities. GoPlus's products have been integrated into mainstream platforms such as Binance, MetaMask, and Trust Wallet, collectively protecting billions of dollars in on-chain assets. This extensive integration network allows GoPlus's DApp detection mechanism to cover a wider range of application scenarios, creating a scaled security protection effect.

AI-Driven Continuous Audit. Faced with the increasing number of smart contract vulnerability attacks, GoPlus has proposed an AI-driven always-on audit solution. Traditional audit methods struggle to effectively cover legacy contracts, while AI-driven continuous audits can perform security checks on old contracts in a short time, balancing reliability and cost. This mechanism, combined with DApp security detection, enables GoPlus to continuously monitor the security status of DApps without relying on manual periodic audits.

Data-Driven Security Network: From Centralized Intelligence to Decentralized Collaboration

The underlying logic of the GoPlus security network is a data-driven decentralized security infrastructure. Its system architecture consists of three interconnected components: the security data layer collects real-time threat intelligence, the security computation layer uses AI algorithms to detect and analyze data, and the SecWare protocol ensures secure transmission and verification of data within the network.

Security Data Layer: Large-Scale Intelligence Collection. The security data layer is the foundation of the GoPlus network, responsible for collecting real-time security data from over 30 blockchain networks. This data includes on-chain public information such as transaction records, contract deployment information, token issuance data, and address interaction history, as well as security intelligence from partners, security communities, and node operators. The breadth and depth of data directly determine the accuracy and coverage of the upper-level analysis models.

Security Computation Layer: AI-Driven Risk Assessment. The security computation layer consists of multiple distributed Security Compute Nodes (SCNs), responsible for executing security-related computation and verification tasks, such as verifying transaction security analysis results, detecting potential security threats, and simulating transactions. This layer uses advanced machine learning algorithms to perform real-time risk detection for each transaction and completes interaction analysis before smart contracts are deployed on-chain. The distributed node design ensures the scalability of computing power and the decentralized nature of the system.

SecWare Protocol and Ecosystem Collaboration. The SecWare protocol is the middle layer connecting security service providers and demanders in the GoPlus network. Developers can build security applications (Security Software) based on the SecWare protocol, providing users with segmented security services such as anti-fraud, anti-phishing, and anti-MEV. This open ecosystem architecture allows GoPlus's security network to continuously expand—more developers joining means richer security data sources and stronger risk identification capabilities, creating a positive flywheel effect.

Data-Driven Self-Evolution Capability. The unique aspect of the GoPlus security network lies in its data-driven self-evolution mechanism. Each risk scan, transaction simulation, and identified malicious address becomes part of the security data layer, used to optimize subsequent risk identification models. This continuous learning mechanism enables GoPlus to maintain a relatively fast response speed when facing new attack methods.

Conclusion

The core challenge of Web3 security lies not in fixing individual vulnerabilities but in establishing a complete security system that can identify risks before transaction execution, provide real-time protection during interaction, and continuously evolve after an attack occurs. Through the coordinated operation of four modules—real-time risk scanning, address behavior analysis, DApp detection, and a data-driven security network—GoPlus Security has built a decentralized security layer covering the entire transaction lifecycle.

From 30 million daily API calls to security protection covering 12 million wallets, from eight-dimensional address risk detection to AI-driven continuous audits, GoPlus is transforming security from an add-on component of Web3 into native infrastructure. With the proliferation of AI agents and the increase in on-chain interaction frequency, security protection at the moment of execution will become increasingly important. The decentralized security network built by GoPlus provides a verifiable, scalable, and sustainable security paradigm for the Web3 ecosystem.

FAQ

Q: What risks can GoPlus's real-time risk scanning detect before a transaction?

GoPlus's real-time risk scanning can identify token contract risks (such as rug pulls, hidden taxes), malicious address risks, authorization risks, phishing site risks, etc., before transaction execution. Through the transaction simulation API, it can also predict transaction execution results, avoiding asset losses due to abnormal slippage or contract vulnerabilities.

Q: How does the address behavior analysis model determine whether an address is risky?

The model evaluates an address from eight dimensions, including address poisoning, recipient risk, risky transaction counterparties, abnormal gas fees, stablecoin risk, NFT poisoning, authorization risk, and asset risk. It also combines a dynamically updated malicious address database with on-chain transaction graph analysis to identify risk addresses associated with known malicious addresses.

Q: How is GoPlus's DApp security detection different from smart contract auditing?

Traditional smart contract auditing is a one-time code review, while GoPlus's DApp security detection provides continuous monitoring through the DApp Security Information API. It aggregates multi-source security data for real-time risk assessment of DApps and can combine AI-driven continuous audit mechanisms for dynamic security checks on legacy contracts.

Q: How does GoPlus's data-driven security network ensure data reliability?

GoPlus uses a decentralized three-layer architecture: the security data layer collects real-time threat intelligence from over 30 blockchains; the security computation layer is executed by distributed nodes for verification and computation; the SecWare protocol ensures secure data transmission and verification. The distributed node and open ecosystem design reduces the risk of single points of failure and data manipulation.

Q: What role does the GoPlus Security (GPS) token play in the security network?

GPS is the utility token of the GoPlus ecosystem, used to pay for security services (such as API calls, transaction risk checks), staking to secure the network and earn rewards, and participating in system governance voting. The total supply of GPS is 10.00 billion tokens.