CSA: Agentic AI, MCP, and the Identity Explosion

Jul 10, 2025

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Source URL: https://cloudsecurityalliance.org/articles/agentic-ai-mcp-and-the-identity-explosion-you-can-t-ignore
Source: CSA
Title: Agentic AI, MCP, and the Identity Explosion

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**Summary:** The text discusses the introduction of the Model Context Protocol (MCP) by Anthropic, a framework that simplifies AI agents’ interaction with various systems. It emphasizes the emerging security challenges posed by these intelligent, autonomous agents, particularly regarding identity management. With agentic AI making autonomous decisions, the traditional security measures may not suffice, prompting professionals to reconsider their approach to identity and access management.

**Detailed Description:**
The article introduces Anthropic’s Model Context Protocol (MCP) as a universal framework that facilitates connections between AI agents and external platforms, making it easier for these agents to perform tasks across various systems (e.g., GitHub, Slack, databases). While the protocol enhances productivity, it simultaneously raises significant security concerns related to identity management and credential handling. Here are the key points discussed in the text:

– **Definition of Agentic AI:**
– Agentic AI is characterized by its ability to autonomously interact with external tools and systems.
– Operated by large language models (LLMs), these agents can perform tasks with minimal human supervision, acting as active participants in the infrastructure.

– **Potential Agent Capabilities:**
– AI agents can perform actions such as filing issues on GitHub, querying databases, sending messages on Slack, and modifying cloud resources without human intervention.

– **Security Implications:**
– Each action performed by an agent relies on credentials (keys, tokens) associated with non-human identities (NHIs).
– The MCP framework does not define rules for credential ownership, credential rotation, or privilege tracking, relying instead on existing authentication methods like OAuth, which are typically designed for human users.

– **Concerns for Security Teams:**
– Security teams face challenging questions, such as the ownership of agents and their credentials, whether those credentials follow least privilege principles, and visibility in audit logs.
– Most environments currently lack adequate visibility and control over these non-human identities.

– **Identity Management Issues:**
– The deployment of agentic AI often results in inadequate tracking and management of agent identities, leading to the potential for unauthorized access and actions.
– Challenges include hardcoded credentials, lack of ownership metadata, and insufficient lifecycle management of agent privileges.

– **Recommendation for Security Practices:**
– Organizations must treat AI agents as privileged identities, necessitating comprehensive management strategies.
– Before deploying LLM-based assistants, professionals should ensure that these identities are visible in Identity and Access Management (IAM) systems, that their credentials are securely managed and regularly rotated, and that there is accountability for their actions.

– **Broader Implications:**
– The adoption of protocols like MCP is growing, potentially leading to the widespread creation of AI-powered NHIs.
– This shift calls for a reevaluation of current security practices to ensure they adequately address the complexities associated with AI agents acting autonomously.

In summary, as AI agents increasingly interact with systems on their own, it is essential for security and compliance professionals to proactively adapt their strategies to manage these unique identities effectively. The future of security must encompass not only the protection of human users but also the management of intelligent systems that mimic human decision-making.

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