Explore practical answers to the most important questions about Shadow AI, enterprise AI security, AI agents, MCP security, governance, and high-risk AI.
MCP security is the practice of discovering, assessing, and controlling Model Context Protocol servers that connect AI systems to enterprise tools and data. Learn the risks, controls, and governance model.
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AI agent security is the practice of discovering, monitoring, and controlling autonomous AI agents, including the identities they use, the systems and data they can access, and the actions they are allowed to take.
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Enterprise AI security is the practice of discovering, assessing, and controlling AI applications, agents, models, and integrations across an organization. It helps enterprises protect sensitive data, identities, systems, and business operations while enabling secure AI adoption.
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Shadow AI is the use of AI applications, agents, models, extensions, or integrations without IT or security approval. Learn how it enters the enterprise, what risks it creates, and how organizations can continuously detect, assess, and govern it.
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