REVIEW 12 cited by
Building A Secure Agentic AI Application Leveraging A2A Protocol
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
read the original abstract
As Agentic AI systems evolve from basic workflows to complex multi agent collaboration, robust protocols such as Google's Agent2Agent (A2A) become essential enablers. To foster secure adoption and ensure the reliability of these complex interactions, understanding the secure implementation of A2A is essential. This paper addresses this goal by providing a comprehensive security analysis centered on the A2A protocol. We examine its fundamental elements and operational dynamics, situating it within the framework of agent communication development. Utilizing the MAESTRO framework, specifically designed for AI risks, we apply proactive threat modeling to assess potential security issues in A2A deployments, focusing on aspects such as Agent Card management, task execution integrity, and authentication methodologies. Based on these insights, we recommend practical secure development methodologies and architectural best practices designed to build resilient and effective A2A systems. Our analysis also explores how the synergy between A2A and the Model Context Protocol (MCP) can further enhance secure interoperability. This paper equips developers and architects with the knowledge and practical guidance needed to confidently leverage the A2A protocol for building robust and secure next generation agentic applications.
Forward citations
Cited by 12 Pith papers
-
Bridging AI and Software Security: A Comparative Vulnerability Assessment of LLM Agent Deployment Paradigms
Function Calling and MCP architectures show distinct vulnerability patterns, with chained attacks succeeding 91-96% of the time in both.
-
Towards Humanoid Robot Autonomy: A Dynamic Architecture Integrating Continuous thought Machines (CTM) and Model Context Protocol (MCP)
A proposed CTM-MCP architecture for humanoid robot autonomy is supported only by self-assessed LLM simulations, not by real robots or independent benchmarks.
-
AI Agent Communications in AI-Native 6G Network: Status, Challenges and Opportunities
A gap analysis showing that today's AI-native 6G specifications do not yet provide the semantic slicing, cross-layer orchestration, decentralized trust, and protocol adaptation that large-scale AI-agent communication ...
-
SDEC: Semantic Deep Embedded Clustering
SDEC is described as a hybrid autoencoder and transformer embedding method that reportedly sets text clustering benchmarks, but the submission's body is a different, unrelated paper.
-
Agent Capability Negotiation and Binding Protocol (ACNBP)
ACNBP is a proposed standard for secure agent capability negotiation with an extension mechanism, but it lacks formal verification, experiments, and independent evaluation.
-
COALESCE: Economic and Security Dynamics of Skill-Based Task Outsourcing Among Team of Autonomous LLM Agents
COALESCE, a framework for skill-based task outsourcing among LLM agents, claims 41.8% simulated and 20.3% real cost reductions, but the validation contains internal contradictions.
-
A Novel Zero-Trust Identity Framework for Agentic AI: Decentralized Authentication and Fine-Grained Access Control
The authors propose a zero-trust identity and access management framework for AI agents that combines decentralized identifiers, verifiable credentials, a capability-aware naming service, and a global session revocati...
-
Get Experience from Practice: LLM Agents with Record & Replay
AgentRR is a proposed paradigm that records agent traces, generalizes them into multi-level experiences, and replays them under safety checks to make LLM agents cheaper, faster, and more reliable.
-
The Trust Fabric: Decentralized Interoperability and Economic Coordination for the Agentic Web
The paper presents a five-layer decentralized framework (Nanda) for agent discovery, trust scoring, and micropayments, but supports its deployment claims only with self-referential descriptions.
-
ADA: Automated Moving Target Defense for AI Workloads via Ephemeral Infrastructure-Native Rotation in Kubernetes
A proposed Kubernetes-native moving target defense that rotates AI workload pods to invalidate attacker persistence, presented without experimental validation.
-
Vibe Coding vs. Agentic Coding: Fundamentals and Practical Implications of Agentic AI
A qualitative taxonomy positions vibe coding and agentic coding as complementary paradigms rather than rivals in AI-assisted software development.
-
From Large AI Models to Agentic AI: A Tutorial on Future Intelligent Communications
This paper is a broad tutorial on applying LAMs and agentic AI to 6G, largely restating existing research rather than introducing new results.
Discussion (0). Continue with ORCID to comment.