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CIS, Astrix, And Cequence Release New AI Security Companion Guides
(MENAFN- Mid-East Info) Partnership delivers practical guidance for securing LLMs, agents, and MCP environments
Dubai, UAE., April, 2026 - The Center for Internet Security, Inc. (CIS®), Astrix Security, and Cequence Security today announced the release of three new CIS Critical Security Controls® (CIS Controls®) Companion Guides designed to help enterprises secure rapidly evolving AI environments. Co‐authored by experts across all three organizations, the guides extend the CIS Critical Security Controls into AI systems where large language models (LLMs), autonomous agents, and Model Context Protocol (MCP) integrations introduce new and unique risks. Each guide focuses on a distinct layer of the AI ecosystem, offering targeted guidance aligned with how modern AI systems operate:
Dubai, UAE., April, 2026 - The Center for Internet Security, Inc. (CIS®), Astrix Security, and Cequence Security today announced the release of three new CIS Critical Security Controls® (CIS Controls®) Companion Guides designed to help enterprises secure rapidly evolving AI environments. Co‐authored by experts across all three organizations, the guides extend the CIS Critical Security Controls into AI systems where large language models (LLMs), autonomous agents, and Model Context Protocol (MCP) integrations introduce new and unique risks. Each guide focuses on a distinct layer of the AI ecosystem, offering targeted guidance aligned with how modern AI systems operate:
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AI LLM Companion Guide: Provides guidance for securing large language models, including risks related to prompts, context handling, and exposure of sensitive information.
AI Agent Companion Guide: Outlines controls for managing autonomous and semi-autonomous agents, focusing on safe tool execution, governed autonomy, and appropriate access to enterprise systems.
MCP Companion Guide: Details protections for Model Context Protocol environments, emphasizing secure tool access, management of Non-Human Identities (NHIs), and auditable interactions across the protocol layer.
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Adapt the CIS Controls to AI-driven architectures, helping teams secure LLMs, agentic systems, and MCP interfaces without adopting a new framework.
Provide clear, prioritized recommendations that support responsible AI adoption across development, deployment, and operational phases.
Blend the strengths of all three organizations by combining standards leadership with deep expertise in agentic AI and API-centric security.
Cover the full AI security stack, from model inputs and context handling to agent reasoning, tool execution, and protocol-level access.
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