Service

Give every AI agent the right identity and no more access

An AI agent that acts across business systems becomes a new kind of enterprise identity. It may act for an employee, call several APIs and handle sensitive data in one workflow. 360ISS combines enterprise IAM delivery with agentic AI architecture to make that access explicit, limited and traceable.

Identity security for AI agentsLast updated

Talk to us about identity security for AI agents Common questions

Who it's for

  • Security teams preparing to govern AI agents, service accounts and other non-human identities
  • AI teams connecting agents to Microsoft 365, ServiceNow, internal APIs, databases or MCP servers
  • Organizations that need delegated actions without sharing a user's full permissions or credentials

What we design

We map each agent, the person or service it represents, the resources it can reach and the actions it may take. We then design authentication, authorization, consent, secrets, approvals, monitoring and revocation around least privilege and Zero Trust principles.

The design can cover Entra ID and managed identities, SailPoint governance, ServiceNow workflows, OAuth/OIDC, role-based access, workload federation, API gateways, MCP tools and agent-to-agent connections. Recommendations follow the existing identity stack and its supported controls.

What you get

  • Agent and non-human identity inventory with accountable owners
  • Actor-resource-action map and least-privilege role design
  • Delegated authorization and human-approval patterns
  • MCP, API, secret and credential trust-boundary review
  • Lifecycle, attestation, monitoring, audit and emergency-revocation design
  • Prioritized remediation roadmap and reference control implementation

From access request to audit evidence

Agent access needs an owner, purpose, expiry and review path just like human access. We define how identities are requested, approved, provisioned, changed, attested and removed. Logs preserve who authorized an agent, which identity it used, what tool it called and whether a person approved the result.

Frequently asked questions

Why does an AI agent need its own identity?

A distinct identity makes its permissions, actions and owner visible. Shared user credentials hide accountability and usually grant more access than the workflow needs.

Can an agent act on behalf of an employee?

Yes, with a delegated authorization pattern that limits the action, resource and duration. The design should preserve both the employee context and the agent identity in the audit trail.

Do you replace our IAM platform?

Usually not. We design around supported controls in the existing identity, cloud and application stack, then identify only the gaps that need an added component or custom policy.

Can you secure MCP servers and tools?

Yes. We review tool discovery, authentication, authorization, input boundaries, secrets, approvals and logging. An MCP connection does not make the underlying tool safe by itself.

Is this a security assessment or an implementation?

It can be either. We offer a focused architecture and risk review, a control prototype, or implementation support with the platform and application owners.

Guides for this service

Guide, updated October 15, 2026

AI agent identity security: a 10-point checklist

A practical checklist for AI agent identity, least privilege, delegated access, MCP tools, approvals, audit, attestation and revocation.

Guide, updated October 15, 2026

AI agents for small business: uses, costs and guardrails

AI agents for small business: practical uses, costs, limits, privacy and seven guardrails before an agent can use company tools.

Guide, updated October 8, 2026

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A copyable business process mapping template, how to run a mapping session, AS-IS vs TO-BE, swimlanes, and how a map drives automation decisions.

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