Mind Network

Why Zero Trust in Web3?

What Is Zero Trust Security?

Zero trust is a modern security strategy based on the never trust, always verify principle. Instead of assuming everything behind the application, database, or AI model is safe, the Zero Trust framework assumes a breach (has happened already or will happen soon) and verifies each request as though it originates from an open network.

Zero Trust Principles

  • Verify Explicitly

    Always authenticate and authorize based on all available data points, including user identity, location, device health, service or workload, data classification, and anomalies.
  • Use Least-Privilege Access

    Limit user access with just-in-time and just-enough access (JIT/JEA), risk-based adaptive polices, and data protection to help secure data and productivity.
  • Assume Breach

    Minimize blast radius and segment access. Verify end-to-end encryption and use analytics to gain visibility, drive threat detection, and improve defenses.

Security Challenges in Web3

  • Data Privacy and Ownership: Data privacy is a fundamental right. According to Articles 12 and 17 in the UN Universal Declaration of Human Rights, the 4th and 5th Amendments of the United States Constitution, Articles 7 and 8 of the Charter of Fundamental Rights of the European Union, and Article 8 of the European Convention for the Protection of Human Rights and Fundamental Freedoms, privacy is essential to ensure human dignity, freedom of speech, and freedom of association. Web3 aims to shift the power and control of data from centralized entities to individuals. Users should have control over their sensitive information (such as personal data, financial transactions, and user interactions), which should be fully encrypted with strict access control, but it is barely supported in existing SocialFi/UGC dapps and middleware solutions.
  • On-Chain Data Protection: Blockchain transactions are not anonymous, but pseudonymous, meaning exposing wallet addresses and interactions with smart contracts could still cause unnecessary security threats or unwanted front-run trades (MEV), causing millions of dollars in losses and enormous reputation damage to the field.
  • Decentralized Storage Risks: Decentralized storage systems often involve data replication across multiple nodes in the network. Ensuring the confidentiality of sensitive data becomes challenging when untrusted node operators have access to the replicated data during data storage and computation.
  • Trust and Reliability: Web3 aims to create a trustless environment by reducing the reliance on intermediaries and central authorities. In many scenarios, strict protection during computation and status updates is a must (such as trading signal generation, random selection, anonymous voting, private exchange, etc.) Situations that lack such protection may cause serious financial losses (such as the FTX scandal). The protection of the trustless environment requires the fulfillment of a series of data security measures (including encryption, access controls, and data integrity checks) that are trustworthy and have not been tampered with or compromised.
  • Compliance with Regulations: Web3 applications and data intelligence processes often involve handling data subject to various regulations, such as data privacy laws (e.g., GDPR) and industry-specific regulations (e.g., HIPAA for healthcare data). Adhering to data security practices ensures compliance with these regulations, preventing legal and financial liabilities that may arise from data breaches or mishandling of sensitive data.
  • Data Federation: Data silos limit developers’ creativity. Similar to what occurred in Web2, L1/L2 chains and their ecosystems started creating silos for user footprints, products, and money flow. It is an ongoing challenge to bridge data silos without leaking user information.
  • AI Security: As the world shifts to AI solutions, mitigating the risk of unauthorized manipulation of input data, model prompts, and parameters is critical. If the AI of a home-service robot or trading models of hedges is hacked, unpredictable damage could befall financial markets and human users.