Agentic AI Security
Agents don't just answer questions — they take actions. Securing that is a different problem than securing a chatbot.
What agentic AI security means
Agentic AI security is the practice of controlling what autonomous AI agents are allowed to do — their identity, permissions, tool access and behavior at runtime — so an agent's mistakes or manipulation have a bounded blast radius. It's a more specific discipline than general AI security, because an agent that can call tools, move data and talk to other agents has a fundamentally larger attack surface than a system that only answers questions.
The trust chain
Every layer below has to be controlled, not just the model at the top:
Threats and controls
Related
Agentic AI security sits inside the broader discipline of AI Security, and the systems it protects are only worth protecting if they're also built on sound AI Architecture. For a deeper look at one specific sub-topic, see MCP Security.
Evidence
FAQ
What is agentic AI security?
The practice of controlling what autonomous AI agents are allowed to do — their identity, permissions, tool access and behavior at runtime — so an agent's mistakes or manipulation have a bounded blast radius.
What's the difference between AI security and agentic AI security?
AI security covers models, RAG and general LLM applications. Agentic AI security is more specific: it's for systems where an agent takes autonomous actions — calling tools, accessing data, talking to other agents — which introduces authorization and privilege risks a plain chatbot doesn't have.
What is MCP and why does it matter for security?
MCP (Model Context Protocol) is a standard that lets AI agents connect to external tools and data sources. Because it wasn't designed with enterprise authentication as a first requirement, MCP connections are a common source of agent security gaps — weak authentication, over-broad tool access, and unclear trust boundaries between agent and tool. See MCP Security for the full breakdown of risks and controls.
Shipping an autonomous agent with real tool access?
Find out what it can actually do before someone else does.