mlsanityData to 14 Oct 2026

BlockA2A: Towards Secure and Verifiable Agent-to-Agent Interoperability

arXiv 2508.01332 ↗First posted 2 Aug 2025cs.CR cs.AIcited by 15

On the map: LLM agents and tool use → Agent threats, guardrails and governance

Abstract (arXiv)

The rapid adoption of agentic AI, powered by large language models (LLMs), is transforming enterprise ecosystems with autonomous agents that execute complex workflows. Yet we observe several key security vulnerabilities in LLM-driven multi-agent systems (MASes): fragmented identity frameworks, insecure communication channels, and inadequate defenses against Byzantine agents or adversarial prompts. In this paper, we present the first systematic analysis of these emerging multi-agent risks and explain why the legacy security strategies cannot effectively address these risks. Afterwards, we propose BlockA2A, the first unified multi-agent trust framework that enables secure and verifiable and agent-to-agent interoperability. At a high level, BlockA2A adopts decentralized identifiers (DIDs) to enable fine-grained cross-domain agent authentication, blockchain-anchored ledgers to enable immutable auditability, and smart contracts to dynamically enforce context-aware access control policies. BlockA2A eliminates centralized trust bottlenecks, ensures message authenticity and execution integrity, and guarantees accountability across agent interactions. Furthermore, we propose a Defense Orchestration Engine (DOE) that actively neutralizes attacks through real-time mechanisms, including Byzantine agent flagging, reactive execution halting, and instant permission revocation. Empirical evaluations demonstrate BlockA2A's effectiveness in neutralizing prompt-based, communication-based, behavioral and systemic MAS attacks. We formalize its integration into existing MAS and showcase a practical implementation for Google's A2A protocol. Experiments confirm that BlockA2A and DOE operate with sub-second overhead, enabling scalable deployment in production LLM-based MAS environments.

Key facts. Cited by 15 papers in the map (data through 14 Oct 2026). Placed in Agent threats, guardrails and governance, one of 16 directions in LLM agents and tool use. Builds on 23 of its 47 references that are in the map. First posted on arXiv 2 Aug 2025.

Builds on

23 of 47 references.

Closest ancestors · 10

Same direction, newest first

  1. 2025textitAgents Under Siege: Breaking Pragmatic Multi-Agent LLM Systems with Optimized Prompt Attacks31 Mar
  2. 2025Multi-Agent Systems Execute Arbitrary Malicious Code15 Mar
  3. 2025CORBA: Contagious Recursive Blocking Attacks on Multi-Agent Systems Based on Large Language Models20 Feb
  4. 2025G-Safeguard: A Topology-Guided Security Lens and Treatment on LLM-based Multi-agent Systems16 Feb
  5. 2025AgentGuard: Repurposing Agentic Orchestrator for Safety Evaluation of Tool Orchestration13 Feb
  6. 2024Prompt Infection: LLM-to-LLM Prompt Injection within Multi-Agent Systems9 Oct
  7. 2024Breaking Agents: Compromising Autonomous LLM Agents Through Malfunction Amplification30 Jul
  8. 2024AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks2 Mar
  9. 2024Agent Smith: A Single Image Can Jailbreak One Million Multimodal LLM Agents Exponentially Fast13 Feb
  10. 2024PsySafe: A Comprehensive Framework for Psychological-based Attack, Defense, and Evaluation of Multi-agent System Safety22 Jan

Other references · 13

  1. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,695
  2. 2023WebArena: A Realistic Web Environment for Building Autonomous Agentscited by 2,006
  3. 2023AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversationcited by 1,988
  4. 2023MetaGPT: Meta Programming for A Multi-Agent Collaborative Frameworkcited by 1,808
  5. 2023Improving Factuality and Reasoning in Language Models through Multiagent Debatecited by 1,784
  6. 2023CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Societycited by 1,395
  7. 2024Cut the Crap: An Economical Communication Pipeline for LLM-based Multi-Agent Systemscited by 141
  8. 2024Internet of Agents: Weaving a Web of Heterogeneous Agents for Collaborative Intelligencecited by 86
  9. 2024MultiAgent Collaboration Attack: Investigating Adversarial Attacks in Large Language Model Collaborations via Debatecited by 56
  10. 2025From Glue-Code to Protocols: A Critical Analysis of A2A and MCP Integration for Scalable Agent Systemscited by 14
  11. 2023martFL: Enabling Utility-Driven Data Marketplace with a Robust and Verifiable Federated Learning Architecturecited by 11
  12. 2019DECO: Liberating Web Data Using Decentralized Oracles for TLScited by 7
1 more
  1. 2019HyperService: Interoperability and Programmability Across Heterogeneous Blockchainscited by 1

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Citing papers per year: 2025: 3; 2026: 12.

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  1. 2025Decentralized Multi-Agent System with Trust-Aware Communication
  2. 2026A2ABreak: Systematic Security Analysis of the A2A Protocol ↗
  3. 2026Autonomous Agents on Blockchains: Standards, Execution Models, and Trust Boundaries
  4. 2025Seven Security Challenges in Cross-domain Multi-agent LLM Systems
  5. 2025Enabling Regulatory Multi-Agent Collaboration: Architecture, Challenges, and Solutions
  6. 2025From Cloud-Native to Trust-Native: A Protocol for Verifiable Multi-Agent Systems
  7. 2026Blockchain-Enabled Artificial Intelligence and AI Agents for Secure Data Sharing and Cybersecurity Applications
  8. 2026From Secure Agentic AI to Secure Agentic Web: Challenges, Threats, and Future Directions