Binding Agent ID: Unleashing the Power of AI Agents with accountability and credibility

TL;DR

This paper introduces BAID, a comprehensive identity infrastructure for autonomous AI agents that ensures accountability and credibility through cryptographic guarantees, blockchain integration, and zkVM-based authentication.

Contribution

It presents a novel identity framework combining biometric, blockchain, and zkVM techniques to establish verifiable user-code binding for AI agents.

Findings

Prototype system demonstrates practical feasibility

Blockchain-based identity management is effective

zkVM-based authentication provides strong security guarantees

Abstract

Autonomous AI agents lack traceable accountability mechanisms, creating a fundamental dilemma where systems must either operate as ``downgraded tools'' or risk real-world abuse. This vulnerability stems from the limitations of traditional key-based authentication, which guarantees neither the operator's physical identity nor the agent's code integrity. To bridge this gap, we propose BAID (Binding Agent ID), a comprehensive identity infrastructure establishing verifiable user-code binding. BAID integrates three orthogonal mechanisms: local binding via biometric authentication, decentralized on-chain identity management, and a novel zkVM-based Code-Level Authentication protocol. By leveraging recursive proofs to treat the program binary as the identity, this protocol provides cryptographic guarantees for operator identity, agent configuration integrity, and complete execution provenance, thereby effectively preventing unauthorized operation and code substitution. We implement and evaluate a complete prototype system, demonstrating the practical feasibility of blockchain-based identity management and zkVM-based authentication protocol.