Build a working inventory of AI agents, agent identities, APIs, and MCP-connected tools, with ownership and workflow context.
One control path from agent discovery to action evidence.
Agent Guard is designed around the moment an AI agent selects a tool, accesses data, or attempts an action. Four connected modules help security teams understand that path, apply policy, evaluate risk, and preserve a record.
RazorShark Security is a fictional company created by Luasai for product demonstrations. Products, scenarios, and company information are illustrative.
Define least-privilege policy for the tools, data, and actions an agent may use in a particular task and environment.
Evaluate runtime behavior for indirect prompt injection, tool misuse, unsafe execution, and sensitive-data exposure.
Retain reviewable context for the agent, identity, policy, requested action, decision, and observed outcome.
Category fit
Agent Guard is positioned in Runtime Security, with Application Security, API Security, and Identity Governance as supporting categories. It is adjacent to DLP, CNAPP, SIEM, and SOAR programs. This is category adjacency only; no vendor integration or marketplace authorization is claimed.