Securing Agentic AI: A Crucial Matter for North East India

In the rapidly evolving world of technology, artificial intelligence (AI) has become an integral part of numerous industries, including those in North East India. However, as AI agents are now not only writing code but also executing it, a new security challenge has emerged. This article delves into the core risks that security teams are inheriting from agentic AI adoption, focusing on Machine Control Protocols (MCPs) and the potential threats they pose.

The Rise of Agentic AI

Tools like Copilot, Claude Code, and Codex can now build, test, and deploy software end-to-end in minutes, reshaping engineering. This speed is a significant advantage, but it also creates a security gap that often goes unnoticed until something breaks.

The Role of Machine Control Protocols (MCPs)

Behind every agentic workflow lies a layer that few organizations are actively securing: MCPs. These systems decide what an AI agent can run, which tools it can call, which APIs it can access, and what infrastructure it can touch. Compromised or misconfigured MCPs can turn automation into an attack surface, with the agent executing commands with authority.

CVE-2025-6514: A Case Study

The impact of this security gap was demonstrated by the CVE-2025-6514 incident, where a flaw in a trusted OAuth proxy used by more than 500,000 developers turned into a remote code execution path. This incident underscored the importance of securing MCPs to prevent similar incidents in the future.

Implications for North East India and India at Large

As AI continues to penetrate various sectors in North East India and across India, understanding and addressing the security risks associated with agentic AI is crucial. The potential for automation to execute attacks, as demonstrated by the CVE-2025-6514 incident, highlights the need for proactive security measures to protect against such threats.

Securing Your AI Stack

To secure your AI stack, it is essential to understand MCP servers, detect and eliminate shadow API keys, audit agent actions, enforce policy before deployment, and implement practical controls to secure agentic AI without slowing development. Register for the live webinar to learn more about these practical controls and regain control of your AI stack before the next incident does it for you.

Conclusion

As AI continues to evolve and become more integrated into our daily lives, it is crucial to address the security challenges that come with it. By understanding the role of MCPs and implementing practical controls, we can ensure that AI works for us, not against us.