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Secure Autonomous Agent Payments: Verifying Authenticity and Intent in a Trustless Environment

Vivek Acharya

TL;DR

This paper addresses how to verify authenticity and intent of autonomous AI agent payments in a decentralized, trustless environment. It introduces the Trustless Intent Verification for Autonomous Agents (TIVA), combining DIDs with verifiable credentials, on-chain intent verification, ZKPs for privacy, and optional TEEs. Key components include an Agent Wallet Contract that binds payments to user-signed mandates or on-chain policies, and ZKPs that reveal only necessary information while proving compliance. The framework yields a provably auditable, low-fraud pathway for AI-driven transactions and lays groundwork for practical prototypes and regulatory-aligned autonomous commerce.

Abstract

Artificial intelligence (AI) agents are increasingly capable of initiating financial transactions on behalf of users or other agents. This evolution introduces a fundamental challenge: verifying both the authenticity of an autonomous agent and the true intent behind its transactions in a decentralized, trustless environment. Traditional payment systems assume human authorization, but autonomous, agent-led payments remove that safeguard. This paper presents a blockchain-based framework that cryptographically authenticates and verifies the intent of every AI-initiated transaction. The proposed system leverages decentralized identity (DID) standards and verifiable credentials to establish agent identities, on-chain intent proofs to record user authorization, and zero-knowledge proofs (ZKPs) to preserve privacy while ensuring policy compliance. Additionally, secure execution environments (TEE-based attestations) guarantee the integrity of agent reasoning and execution. The hybrid on-chain/off-chain architecture provides an immutable audit trail linking user intent to payment outcome. Through qualitative analysis, the framework demonstrates strong resistance to impersonation, unauthorized transactions, and misalignment of intent. This work lays the foundation for secure, auditable, and intent-aware autonomous economic agents, enabling a future of verifiable trust and accountability in AI-driven financial ecosystems.

Secure Autonomous Agent Payments: Verifying Authenticity and Intent in a Trustless Environment

TL;DR

This paper addresses how to verify authenticity and intent of autonomous AI agent payments in a decentralized, trustless environment. It introduces the Trustless Intent Verification for Autonomous Agents (TIVA), combining DIDs with verifiable credentials, on-chain intent verification, ZKPs for privacy, and optional TEEs. Key components include an Agent Wallet Contract that binds payments to user-signed mandates or on-chain policies, and ZKPs that reveal only necessary information while proving compliance. The framework yields a provably auditable, low-fraud pathway for AI-driven transactions and lays groundwork for practical prototypes and regulatory-aligned autonomous commerce.

Abstract

Artificial intelligence (AI) agents are increasingly capable of initiating financial transactions on behalf of users or other agents. This evolution introduces a fundamental challenge: verifying both the authenticity of an autonomous agent and the true intent behind its transactions in a decentralized, trustless environment. Traditional payment systems assume human authorization, but autonomous, agent-led payments remove that safeguard. This paper presents a blockchain-based framework that cryptographically authenticates and verifies the intent of every AI-initiated transaction. The proposed system leverages decentralized identity (DID) standards and verifiable credentials to establish agent identities, on-chain intent proofs to record user authorization, and zero-knowledge proofs (ZKPs) to preserve privacy while ensuring policy compliance. Additionally, secure execution environments (TEE-based attestations) guarantee the integrity of agent reasoning and execution. The hybrid on-chain/off-chain architecture provides an immutable audit trail linking user intent to payment outcome. Through qualitative analysis, the framework demonstrates strong resistance to impersonation, unauthorized transactions, and misalignment of intent. This work lays the foundation for secure, auditable, and intent-aware autonomous economic agents, enabling a future of verifiable trust and accountability in AI-driven financial ecosystems.

Paper Structure

This paper contains 5 sections, 1 figure.

Table of Contents

  1. Introduction
  2. Methodology
  3. Results and Security Analysis
  4. Discussion
  5. Conclusion

Figures (1)

  • Figure 1: Conceptual architecture of the Trustless Intent Verification for Autonomous Agents (TIVA). The off-chain domain hosts the AI worker agent (optional TEE) for decision logic and key storage; the on-chain domain verifies DID/credentials and enforces payments via the agent wallet smart contract. The user wallet issues verifiable credentials (1), the wallet verifies DID/credential (2), and the agent submits a payment request (3). Optional policy and zero-knowledge proof modules support rule evaluation and privacy.