Vorlon Guardian
by Vorlon
Real-time runtime enforcement gateway that blocks unauthorized AI agent actions before the transaction completes
Vorlon Guardian is an inline enforcement gateway for agentic AI that sits at the MCP and REST layers between AI agents and the systems they call, blocking policy-violating actions before they execute. It is built for CISOs and security architects who have visibility into what their agents do but no way to stop them.
Vorlon launched Guardian on June 30, 2026 to close what the company calls the enforcement gap in agentic AI security: most organizations can observe agent activity after the fact but cannot prevent a destructive action in the moment. Guardian sits inline at the Model Context Protocol and REST communication layers, between agents and the SaaS applications, cloud data stores, internal APIs and homegrown systems they interact with, and applies policy before any transaction completes. It offers three enforcement modes — real-time blocking of actions that violate policy, masking of sensitive fields in data in transit without breaking the workflow, and protocol-level read-only enforcement that removes an agent's ability to write regardless of what the model decides to do. Policies can be set both at the agent-platform level and per connected system, and Guardian covers the full spectrum of agent-specific threat patterns including indirect prompt injection, credential abuse, OAuth token abuse, supply chain compromise, integration-layer attacks, agent-to-agent manipulation, anomalous data movement, excessive agency and MCP server attacks. It works with any application or data store exposing an API or MCP server — including legacy systems and apps built with AI coding assistants like Claude Code and OpenAI Codex — and the company says it deploys in minutes. Guardian draws on DataMatrix, Vorlon's patented simulation engine introduced in April 2025 that maintains a live behavioral model of every agent, app, identity, integration and data flow in an environment, and it integrates with Netskope, Microsoft Purview, Google DLP and MIND as well as SIEM, SOAR, AI SOC, ITSM and DLP platforms. It has been available since launch.
At a Glance
- Category
- Governance & Security
- Pricing
- Contact for pricing
- Target Market
- CISOs, CIOs, Security Architects, Enterprise Developers, Platform Engineering Teams
- Founded
- 2022
- Headquarters
- San Francisco, California, United States
Key Features
- ✓Inline protocol-layer enforcement
Guardian sits between agents and target systems at the MCP and REST layers and applies policy before a transaction completes rather than alerting afterward.
- ✓Real-time action blocking
Agent actions that violate policy are stopped before execution, at both the agent-platform level and per connected system.
- ✓Read-only enforcement
Protocol-level restriction removes an agent's write capability entirely, so destructive operations cannot occur regardless of model behavior.
- ✓Sensitive data masking in transit
Sensitive fields in responses are masked before reaching the agent without disrupting the workflow.
- ✓DataMatrix simulation engine
Vorlon's patented engine, introduced April 2025, maintains a live behavioral model of every agent, app, identity, integration and data flow in the environment.
- ✓Broad agent threat coverage
Addresses indirect prompt injection, credential and OAuth token abuse, supply chain compromise, agent-to-agent manipulation, excessive agency and MCP server attacks.
Capabilities
Use Cases
- •Preventing agent-caused data destruction
Read-only protocol enforcement stops incidents like the April 2026 case in which an AI coding agent deleted PocketOS's entire production database and backups in nine seconds despite explicit safety rules.
- •Securing agent access to SaaS systems of record
Policy is enforced per connected system across platforms such as Salesforce and Workday as well as internal APIs.
- •Governing internally built AI agents
Covers apps and agents built with AI coding assistants like Claude Code and OpenAI Codex, which often ship without security review.
Ideal For
Best For
- ✓Preventing destructive AI agent actions in production SaaS and cloud data stores
- ✓Enforcing read-only agent access at the protocol level
- ✓Masking sensitive data in transit to AI agents without breaking workflows
- ✓Securing MCP servers and agent-to-agent traffic against prompt injection and token abuse
Market Analysis
Pros
- ✓Closes a real and well-documented gap between agent observability and control
- ✓Deploys in minutes against anything with an API or MCP server
- ✓Integrates with existing DLP, SIEM and SOAR investments rather than replacing them
- ✓Threat model is specific to agentic AI rather than repackaged API security
Cons
- ✗No published pricing or free trial
- ✗An inline gateway adds a control point in the critical path of agent traffic
- ✗Small, venture-stage vendor relative to platform incumbents
- ✗Key market statistics come from Vorlon's own survey report
Pricing
Guardian
Contact for pricing
- ✓Inline MCP and REST layer enforcement
- ✓Real-time blocking, data masking and read-only modes
- ✓DataMatrix behavioral modeling
- ✓SIEM, SOAR, ITSM and DLP integrations
No pricing was disclosed at launch.
Sources
This page was written from 3 sources, 2 on domains other than vorlon.io.
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