AI agent security and governance insights
Research, guidance, and product insights for securing AI agent actions, controlling tool access, and governing enterprise execution.
Agentic Security and AI Governance: A Practical Guide for Enterprise AI in 2026
Agentic security controls what AI agents can do with tools, APIs, credentials, and data. Learn the seven runtime controls that turn AI governance policy into enforceable action.
How to Convert Enterprise APIs into Secure Agent Tools Without Exposing Credentials
Most teams give AI agents raw API keys. That is the wrong pattern. Here is the right architecture: convert enterprise APIs into governed tools via KeyRunner MCP, with runtime secret injection and response redaction that strips PII, PHI, PCI and secrets before the agent ever sees them.
How Do AI Agents Access APIs Without Exposing Credentials?
AI agents can access APIs without seeing credentials when a secure execution layer checks the requested action, retrieves the required secret from a vault, makes the API call, and returns only the permitted response.
What Is MCP Security and How Do You Govern MCP Tools?
MCP security governs which tools an AI agent can discover and call, under which conditions, with which downstream credentials, and what data the tool may return.
How Do You Enforce Least Privilege for AI Agents?
Least privilege for AI agents means giving each agent only the tools, data, parameters, credentials, and operating limits required for its assigned task, then checking those permissions at every execution.
How Do You Audit API Calls Made by AI Agents?
To audit AI agent API calls, record the agent and user identity, requested tool, parameters, policy decision, approval, credential reference, redaction, downstream outcome, and timestamp for every execution.
Secure Agent Runtime vs Secrets Manager: What Is the Difference?
A secrets manager protects credentials at rest, while a secure agent runtime controls how an AI agent uses a credential during an action without giving the credential to the agent.
API Gateway vs AI Agent Governance: What Is Missing?
An API gateway manages API traffic, while AI agent governance controls which tools and business actions an agent may use, under which policy, before the request reaches the API.
How Do You Stop Unsafe AI Agent Actions Before Execution?
Unsafe AI agent actions can be stopped before execution by intercepting every tool call, evaluating it against an external policy, and blocking or pausing the request before credentials or downstream APIs are used.
How Do Human Approval Gates Work for AI Agents?
A human approval gate pauses an AI agent action before execution when policy identifies elevated risk, then allows an authorized reviewer to approve or deny the exact requested action.
How Do You Prevent Sensitive API Data from Reaching an LLM?
Sensitive API data can be kept out of an LLM by filtering the downstream response inside a trusted execution layer before the result is returned to the AI agent.
How Should Enterprises Identify and Authorize AI Agents?
Enterprises should give every AI agent a unique identity, preserve the identity of the human or workload behind each request, authorize named tools through external policy, and record every decision and action in an audit trail.