> For the complete documentation index, see [llms.txt](https://whitepaper.gopluslabs.io/goplus-network/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://whitepaper.gopluslabs.io/goplus-network/the-goplus-security-layer/security-data-layer.md).

# Security Data Layer

The Security Data Layer is the trusted data foundation of the GoPlus security layer for the AI era.

In the last few years, GoPlus Network has experienced exponential growth, with security data usage increasing by over 5000 times from what was recorded in 2022 and daily API calls reaching tens of millions, demonstrating high levels of ecosystem trust. As GoPlus expands from Web3 security into AI agent security, the integrity and reliability of security data becomes even more important. Agent runtime protection, transaction protection, policy enforcement, and decentralized security services all depend on accurate, timely, and verifiable risk data.

To address this need, GoPlus proposes a decentralized Security Data Contribution and Verification Layer that harnesses multi-party participation and automated verification processes. This foundational layer provides trustworthy, rich, and real-time security data for both Web3 and AI agent security. It supports the collection, verification, and utilization of token risk data, malicious address data, phishing data, dApp risk data, signature risk data, transaction risk data, prompt-injection indicators, malicious command patterns, credential leak patterns, URL risk data, package risk data, and other security intelligence inputs.

<figure><img src="/files/3uVmzFGQ5JGvd7X9NvpV" alt=""><figcaption><p>Security Data Layer</p></figcaption></figure>

### Data Contribution

Security data contributors form the foundation of the entire system. They provide valuable information about potential security risks and threats through various channels, including but not limited to:

**End-users:** Users can report security issues they encounter, such as suspicious scam activities, phishing attempts, malicious websites, wallet drainers, rug pulls, and unsafe agent actions.

**Security researchers:** Professional security researchers can contribute findings on Web3 risks, AI agent threats, malicious packages, prompt-injection payloads, credential leakage patterns, and other in-depth security insights.

**Third-party security companies & organizations:** Specialized security firms can offer comprehensive threat intelligence and risk assessment reports.

Through incentivization and recognition mechanisms, GoPlus encourages broad participation to establish a comprehensive and diverse security database.

### Data Verification

To ensure the credibility and accuracy of the contributed data, we implement a multi-tiered decentralized verification mechanism. The Security Data Verification system consists of a Primary verification process and a Secondary verification process, working in tandem to validate the security data.

#### **Primary verification**

The Primary verification employs a multi-faceted approach to data verification, incorporating trusted third-party entities and automated computational methods:

**Third-Party Verification Nodes:** Reputable entities operate verification nodes that leverage their expertise and resources to assess the veracity of user-contributed information.

**Computational Verification Nodes:** Automated computational methods are used to verify specific types of security data through security scanning, advanced algorithms, and AI techniques.

**Auditors:** Independent auditors oversee the verification process, ensuring compliance with established protocols and maintaining the integrity of the system.

#### **Secondary verification**

The Secondary verification is triggered when disputes arise in the Primary verification. It is composed of highly specialized security teams and institutions that focus on resolving controversies in Primary verification:

**Elite Security Teams:** Renowned security teams with expertise in Web3 security, AI security, application security, and threat intelligence are enlisted to investigate and resolve complex disputes.

**Institutional Arbitrators:** Respected institutions, such as respected university labs and Web3 industry leaders, act as impartial arbitrators to settle disagreements and provide final verdicts.

The Secondary verification ensures that any contentious issues are thoroughly examined and resolved by the most qualified experts in the field.

By seamlessly integrating security data contributors and the multi-tiered verification mechanism, GoPlus creates a robust and resilient decentralized security data ecosystem. This approach enhances the diversity, professionalism, and accuracy of risk data while strengthening the risk models that protect users, AI agents, wallets, applications, and chains. By working together, the ecosystem can build a shared data foundation for protecting high-risk digital actions before they execute.


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