most citedBuilding A Secure Agentic AI Application Leveraging A2A Protocol

5 citations · 9 across the 6 of their papers we have counts for

collaborators

6 papers

cs.AI2025

COALESCE: Economic and Security Dynamics of Skill-Based Task Outsourcing Among Team of Autonomous LLM Agents

Manish Bhatt, Ronald F. Del Rosario, Vineeth Sai Narajala +1

The meteoric rise and proliferation of autonomous Large Language Model (LLM) agents promise significant capabilities across various domains. However, their deployment is increasing…

cs.CR20251 cited

ETDI: Mitigating Tool Squatting and Rug Pull Attacks in Model Context Protocol (MCP) by using OAuth-Enhanced Tool Definitions and Policy-Based Access Control

Manish Bhatt, Vineeth Sai Narajala, Idan Habler

The Model Context Protocol (MCP) plays a crucial role in extending the capabilities of Large Language Models (LLMs) by enabling integration with external tools and data sources. Ho…

cs.CR20251 cited

Agent Name Service (ANS): A Universal Directory for Secure AI Agent Discovery and Interoperability

Ken Huang, Vineeth Sai Narajala, Idan Habler +1

The proliferation of AI agents requires robust mechanisms for secure discovery. This paper introduces the Agent Name Service (ANS), a novel architecture based on DNS addressing the…

cs.CR2025

Securing Agentic AI: A Comprehensive Threat Model and Mitigation Framework for Generative AI Agents

Vineeth Sai Narajala, Om Narayan

As generative AI (GenAI) agents become more common in enterprise settings, they introduce security challenges that differ significantly from those posed by traditional systems. The…

cs.CR20255 cited

Building A Secure Agentic AI Application Leveraging A2A Protocol

Idan Habler, Ken Huang, Vineeth Sai Narajala +1

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 sec…

cs.CR20252 cited

Enterprise-Grade Security for the Model Context Protocol (MCP): Frameworks and Mitigation Strategies

Vineeth Sai Narajala, Idan Habler

The Model Context Protocol (MCP), introduced by Anthropic, provides a standardized framework for artificial intelligence (AI) systems to interact with external data sources and too…