AgentGuard
Identity Security for AI Agents
Autonomous AI agents need identity, permissions, and control.
AgentGuard protects autonomous software identities by enforcing least-privilege authorization, contextual policy, human approval workflows, and complete audit visibility.
The Problem
AI agents can act faster than humans can review them.
Traditional security models were designed around human users. Autonomous agents introduce a new challenge: software identities that can make decisions and execute actions independently.
No Agent Identity
Multiple AI systems often share credentials, making accountability difficult.
Excessive Permissions
Agents may have more access than required to complete their tasks.
Limited Visibility
Organizations need complete records of what agents did and why.
Security Architecture
Every AI action follows a controlled lifecycle.
Machine Identity
Every runtime receives a unique identity.
OAuth Authorization
Permissions are limited by scope.
Context Policy
Risk is evaluated before execution.
Human Approval
Sensitive actions require oversight.
Audit Trail
Every decision remains traceable.
Live Agent Simulation
Watch AgentGuard make security decisions in real time.
Follow autonomous agents as they request actions, pass authorization checks, trigger policies, and create verifiable security records.
Connected Agents
Sales Agent
Revenue Operations
Finance Agent
Financial Operations
Admin Runtime
Human Approval
Interactive Security Simulation
See how AgentGuard protects autonomous AI actions.
Four agents. Four security decisions. Watch how identity, permissions, policy, and human oversight determine what happens next.
AgentGuard Security Model
Every agent action follows a controlled lifecycle.
AgentGuard separates identity, authorization, policy decisions, human control, and audit history.
Machine Identity
Every autonomous agent operates with a distinct identity.
OAuth Authorization
Permissions determine what each agent can access.
Contextual Policy
Risk is evaluated before sensitive actions execute.
Human Approval
High-risk operations pause for authorized review.
Audit Trail
Every decision remains traceable and reviewable.
Technical Trace Explorer
Inspect every security decision.
Review how identity, authorization, approvals, and audit history connect together.
Authorized Agent
ALLOWEDA finance agent with the correct machine identity and permissions completed a low-risk action without requiring human intervention.
Trace System
AgentGuard Security Model
Action
Issue Refund
Risk Context
$100
Resource
acct_demo_001
Agent Identity
Finance Agent
Authenticated machine identity verified.
Scope Check
finance:refund
OAuth permission verified.
Contextual Policy
Low Risk Action
Refund amount is within autonomous execution limits.
Decision
Allowed
AgentGuard permitted the action.
Audit
Recorded
Security decision stored in the audit trail.
Complete security trace reconstructed from identity, authorization, policy enforcement, approval workflow, and audit history.
IDENTITY
Every agent is accountable
Separate machine identities prevent shared privileged access.
AUTHORIZATION
Permission before automation
Agents only access actions allowed by their scopes.
CONTROL
Autonomy with boundaries
Sensitive actions can require human approval.
Protect your AI workforce before it scales.
The administrator console provides protected identities, approval workflows, and complete audit visibility.
Administrator Login