AI Application Security
Control what every AI agent can see, do, and change.
RazorShark Agent Guard is a synthetic platform concept designed to help security teams inventory AI agents and MCP-connected tools, define least-privilege action policy, evaluate unsafe runtime behavior, and retain reviewable decision evidence.
Four controls for the agent action path
Discover
Build an inventory of agents, agent identities, APIs, and MCP-connected tools.
Enforce
Define least-privilege policy for tools, data, and actions.
Defend
Evaluate indirect prompt injection, tool misuse, unsafe execution, and sensitive-data exposure while workflows run.
Evidence
Retain context for the agent, identity, policy, requested action, decision, and observed outcome.
Initial customer and partner profile
The initial customer profile is a regulated US or UK enterprise with 1,000 or more employees deploying consequential AI-agent workflows. Buyers include CISOs, AI platform leaders, AppSec leaders, IAM leaders, and security architects.
The ideal co-sell partner is a specialist cybersecurity consultancy or focused reseller with depth in runtime, application, API, identity, cloud, or regulated-industry security and services spanning assessment, policy design, implementation planning, and managed monitoring.
RazorShark Security is a fictional company created by Luasai for product demonstrations. Products, scenarios, and company information are illustrative. RazorShark has no real customers, certifications, marketplace listings, or independently measured product results.