How 0G and AmericanFortress protect senders and receivers from AI hacks

2026-02-05 13:01:39

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The collaboration between 0G and AmericanFortress introduces an innovative trading stack specifically designed for the security of AI agents. At the core of the system is a simple yet critical question: How can senders and receivers remain truly anonymous in decentralized transactions? The new solution combines 0G’s computational layer with AmericanFortress’s dynamic stealth address technology, creating a shield against the growing threats in the on-chain world.

New Security Threats for AI Agents in Decentralized Trading

AI agents executing transactions automatically face risks that have received little attention so far. Phishing attacks, targeted address tracking, and context attacks become real problems when agents frequently and predictably operate on blockchains. The biggest issue: once a transaction from sender to receiver becomes public, anyone can trace this connection—posing potential security and compliance risks.

Stealth Addresses and Zero-Knowledge Proofs as a Shield

The new technology relies on two pillars of cryptography. First, generating encrypted one-time addresses prevents the sender and receiver from being linked. Each transaction receives a new, unique address, making direct tracking impossible and ensuring on-chain privacy.

Additionally, zero-knowledge proofs offer an elegant solution: they hide balances and transaction details while maintaining verifiability. This allows for selective disclosure of proofs needed only for compliance purposes—without revealing the entire transaction.

From Theory to Practice: Integration in the 0G Mainnet

The system is already live on the 0G mainnet and is actively integrated by various institutions, wallets, and layer-2 ecosystems. Developers can incorporate the solution directly into their AI agent frameworks via specialized SDKs. This pragmatic integration demonstrates that protecting sender and receiver is not only theoretically sound but also practically feasible.

This technology addresses a fundamental challenge of AI-driven blockchain usage: balancing transparency and privacy, security and compliance.

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