Enterprise AI Security Discussions

Enterprise AI Security,
Explained Clearly.

Practical guidance on Shadow AI, AI agents, MCP security, governance, and high-risk AI.

Explore AI Security Discussions

Answers to the questions security, risk, compliance, and technology leaders are asking now.

What Is MCP Security?

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.

What Is AI Agent Security?

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.

What Is Enterprise AI Security?

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.

What Is Shadow AI?

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.

What Is Generative AI Security?

Generative AI security is the practice of protecting organizations from risks created by chatbots, copilots, code generators, image generators, and the models behind them. This article explains how enterprises can manage data leakage through prompts, prompt injection, hallucinated output, jailbreaking, model and vendor risk, insecure output handling, and unauthorized Shadow AI use.

What Is AI Identity Security?

AI identity security is the practice of discovering, mapping, and governing the identities and credentials that AI systems use to access enterprise applications and data. This article explains why AI tools often operate through delegated human identities, OAuth grants, API keys, service accounts, and tokens, and how enterprises can reduce identity sprawl, over-scoped access, orphaned tokens, audit-log blindness, and OAuth app abuse.

What Is Enterprise AI Governance?

Enterprise AI governance is the system of policies, roles, processes, and controls an organization uses to manage how AI is adopted, used, monitored, and governed across the business. A strong governance program helps organizations capture the value of AI while keeping data exposure, regulatory risk, and autonomous AI behavior within defined limits.

What Is AI Data Leakage?

AI data leakage is the unintended exposure of sensitive company information through AI tools, often when employees paste or upload confidential data, connect AI integrations, or use AI features that can access more information than expected. This discussion explains how AI data leakage happens, why traditional DLP tools often miss it, and how enterprises can reduce the risk.