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Give every AI agent a secure identity

This Agent Identity Toolkit from 1Password offers teams an architecture, framework, and resources for securing AI agent identity, from authentication and authorization to short-lived credential and workload identity management.

Agent identity challenges

Legacy IAM isn’t enough
for AI agent identity

Icon of a user profile representing stolen API keys in SaaS environments.
Long-Lived Credentials are a liability

A stolen API key gives attackers agent-level authority until the key is revoked.

Terminal window icon illustrating local AI agents in a SaaS architecture.
No clear identity for local agents

Local agents need to prove which process is requesting access.

Robot icon representing AI agent authorization scope and security.
Agents move at machine speed

Authorization must be scoped, short-lived, and auditable.

The 1Password Agent Identity Toolkit

Build your AI agent identity stack with 1Password

1Password Unified Access

Unify access across humans, AI agents, and machine identities.

1Password SDK

Issue short-lived, scoped credentials to any AI agent with a single SDK call, no hardcoded secrets required.

1Password Service Accounts

Automate secrets management in your applications and infrastructure without the need to deploy additional services.

1Password Environments

Inject the right secrets into the right environment destinations automatically, without hardcoding credentials into your agent workflows.

1Password Device Trust MCP

Let AI agents check device health and trust posture before taking action, via the Model Context Protocol.

1Password Agentic Autofill

Allow agents to fill credentials into web workflows securely, without exposing secrets in plaintext or storing them in prompts.

Device Trust AI Discovery

Surface every AI tool and agent running on your managed devices, so you know what's running before you govern it.

Local Agent Broker

A code-signed local broker that handles credential lifecycle for agents running on developer machines, with no secrets in code. Coming soon.

Local Agent Identity Attestation

Give fully autonomous agents cryptographically signed proof of their delegated authority, verifiable at every step. Coming soon.

A three-step framework for AI agent identity

AI agent identity starts before monitoring. Classify authority, deployment, and access to move from reaction to control.

Step 01

Classify by authority type

Human delegated

These agents use delegated access from the person who launched it, carrying their permissions and their identity, with credentials that expire. Examples include: Coding assistants, workplace scheduling agents, and operations and CRM support agents.

Machine
bound

A workload identity for AI agents is scoped exactly for what the job needs, reducing over permissioning and eliminating shared credentials. Examples include: CI/CD pipeline agents, pull request review agents, HR provisioning assistants.

Fully autonomous

Autonomous agents are high risk and should operate with tightly defined guardrails, least-privilege access, and continuously verify trust as conditions change. Examples include: Full build-and-deploy agents, supply chain rerouting agents, and security remediation agents.

Step 02

Classify where agents run

Local deployment

Agents run on developer devices, IDE plugins, local MCP servers, or desktop AI assistants. They are close to users, but harder to govern.

Remote deployment

Agents run in containers, CI/CD pipelines, or SaaS platforms, where shared service accounts and API keys can blur identity.

Hybrid deployment

Agents move between local tools and remote APIs, creating credential exposure when identity does not carry end to end.

Step 03

Classify what agents access

User data and
personal resources

Agents accessing calendars, email, documents, or files on behalf of a named user. The delegation scope must match exactly what the user intended to share, nothing more. 

Diagram showing user data and personal resources like calendars, documents, and emails.

Internal tools
and applications

Agents accessing corporate SaaS, internal APIs, ticketing systems, code repositories, or databases. Often authorized via OAuth apps with permissions granted once and never reviewed.

Internal SaaS tools like Salesforce, Slack, and GitHub protected by a central security shield.

External APIs and
third-party services

Agents calling external providers, like AI APIs, payment systems, partner platforms, or public web services. API keys are typically long-lived and stored wherever the agent can find them.

Secure external APIs and third-party integrations linking to OpenAI and Salesforce.

Infrastructure and
cloud resources

Agents with access to AWS, GCP, Azure, databases, or storage buckets. These carry a very high blast radius.

Secure external APIs and third-party integrations linking to OpenAI and Salesforce.

Three scenarios, one AI agent identity architecture

No matter your role, 1Password gives you the architecture and playbook for operating safely in an AI-first world.

Blue schematic diagram illustrating the Agent Identity Toolkit architecture for securing AI workflows in three scenarios.

Frequently asked questions

What is AI agent identity?

AI agent identity is a verifiable identity assigned to a software agent, not just the human or service account behind it. It helps teams authenticate the agent, authorize what it can access, issue short-lived credentials, and audit actions back to the right user, workload, device, or policy.

How is Agent Identity Toolkit different from AI agent security tools?

What is the 1Password Agent Identity Toolkit?

What are the three agent architectures, and how do I pick one?

What is a workload identity, and why does my agent need one?

What is OAuth Token Exchange (RFC 8693) and how does it work here?

What is DPoP and why does it matter?

What is WIMSE and is it production-ready?

How long do agent tokens last?

Does the kit work with my existing identity provider?

What is the local broker and why do I need it?

Can I use the Agent Identity Toolkit with agents I didn't build myself — like Claude, GPT-4o, or a third-party agentic platform?

Do I need to replace my existing secrets management setup to use this?