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

arXiv: https://arxiv.org/abs/2511.15712 · HTML: https://mlsanity.com/paper/2511.15712/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 10 references that are in the map.
- First posted on arXiv 8 Nov 2025.

## Builds on (most cited first, 3 of 3)

- [Authenticated Delegation and Authorized AI Agents](https://mlsanity.com/paper/2501.09674/) (2025)
- [Coral Protocol: Open Infrastructure Connecting The Internet of Agents](https://mlsanity.com/paper/2505.00749/) (2025)
- [SoK: Security and Privacy of AI Agents for Blockchain](https://mlsanity.com/paper/2509.07131/) (2025)

## Built on by (most cited first, 3 of 3)

- [SoK: Security of Autonomous LLM Agents in Agentic Commerce](https://mlsanity.com/paper/2604.15367/) (2026)
- [Trust Without Trusting: A Recomputable Trust Protocol for Autonomous Agents](https://mlsanity.com/paper/2605.06738/) (2026)
- [Beyond the Mandate: A Systematic Security Analysis of the Agent Payments Protocol (AP2)](https://mlsanity.com/paper/2608.23858/) (2026)

## Abstract (arXiv)

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.