Comparison Guide

AIM vs Azure IAM for AI Agents

Compare open source agent identity management with Azure RBAC and managed identities. Different scopes, complementary purposes.

AIM

by OpenA2A

Purpose-built for AI agents. Cryptographic identity, capability-based access, and continuous trust scoring. Open source and self-hosted.

Open SourceAgent-NativeFree Forever

Azure IAM

by Microsoft

Resource-level access control for Azure. Azure RBAC manages who can do what on which Azure resources. Managed identities for workloads.

Managed ServiceResource AccessAzure Native

Key Distinction: Agent Identity vs Resource Access

Azure IAM (RBAC) controls access to Azure resources (who can perform which operations on Azure services). AIM manages AI agent identity (cryptographic proof, behavioral trust, capabilities). Azure asks "can this principal perform this action on this resource?" while AIM asks "is this agent trustworthy to perform this capability?" Managed identities provide machine identity for Azure access, but not AI-specific trust scoring or capability enforcement.

Feature Comparison

FeatureAIMAzure IAM
Primary FocusAI agent identityAzure resource access control
Licensing Apache-2.0 (Free)Included with Azure (pay for resources)
Deployment Self-hosted or CloudAzure managed only
Cryptographic Agent Identity Ed25519 per agentManaged identities / Service principals
Continuous Trust Scoring 8-factor real-time Not available
Capability-Based Access Code-level enforcementRole-based (built-in + custom roles)
MCP Server Attestation Native support Not supported
AI Framework Integration LangChain, CrewAI, etc. Not applicable
Managed IdentitiesNot applicable System & User-assigned
Role-Based Access ControlNot applicable 100+ built-in roles
Management Groups / HierarchyNot applicable Subscriptions, resource groups
Vendor Lock-in None (portable)Azure ecosystem
Source Code Access Full access Closed source
Cost Model Free foreverFree (pay for Azure resources)

Different Layers of Security

AIM: Agent Identity Layer

AIM asks: "Is this AI agent trustworthy?"

  • Cryptographic proof of agent identity
  • Behavioral trust that evolves over time
  • Capability boundaries at the code level
  • Works across any cloud or on-premises

Azure IAM: Resource Access Layer

Azure IAM asks: "Can this principal access this resource?"

  • Control access to Azure services
  • Role-based permissions (Reader, Contributor, Owner)
  • Managed identities for workloads
  • Subscription and resource group inheritance

When to Choose Each Solution

Choose AIM if you...

  • Are building or deploying AI agents
  • Need to secure autonomous software (not just resources)
  • Use LangChain, CrewAI, or Claude Desktop
  • Want cryptographic identity per agent
  • Need continuous behavioral trust evaluation
  • Require MCP server attestation
  • Want to avoid cloud vendor lock-in

Choose Azure IAM if you...

  • Need to control access to Azure resources
  • Managing human user access to Azure portal
  • Need managed identities for VMs, Functions, AKS
  • Want organization-wide security policies
  • Using Azure-native services (Functions, AKS, CosmosDB)
  • Need cross-subscription resource access
  • Managing Blob Storage, SQL Database access

Time to Secure Your First Agent

5 Minutes

with AIM

pip install → secure() → done

N/A

with Azure IAM

Azure IAM manages resource access, not agent identity

Different Approaches

AIM secures the agent itself. Azure IAM controls what Azure resources it can access.

AIM: Agent Identity

from aim_sdk import secure

# Secure the AI agent itself
# Cryptographic identity + trust

agent = secure(
  "data-processor",
  capabilities=[
    "database:read",
    "api:call"
  ]
)

# Agent identity is verified
# before any action

Azure IAM: Resource Access

# Grant access via Azure RBAC
# Role assignment on scope

az role assignment create \
  --assignee "$MANAGED_ID" \
  --role "Reader" \
  --scope "/subscriptions/..."

# Controls Azure resource access
# Not agent-level identity

Use Both Together

AIM and Azure IAM operate at different layers and complement each other:

  • AIM verifies and manages agent identity with trust scoring
  • Azure IAM controls what Azure resources the agent can access
  • AIM trust score can gate managed identity access
  • AIM can run on AKS with workload identity

Agent identity (AIM) + Resource access (Azure IAM) = Defense in depth for AI agents on Azure.

Building with Azure OpenAI?

If you're building AI agents with Azure OpenAI Service, Azure IAM controls access to the OpenAI endpoints, but it doesn't manage the identity of the AI agents themselves. AIM provides the missing layer: cryptographic identity, capability enforcement, and trust scoring for your Azure-powered agents. Use Azure IAM for API access, AIM for agent identity.

Looking for Microsoft Entra?

Microsoft Entra ID (formerly Azure AD) handles human identity and SSO, while Azure IAM/RBAC handles resource access. Both are different from AIM, which handles AI agent identity.

See AIM vs Microsoft Entra comparison →

Start Securing Your AI Agents Today

AIM provides what Azure IAM can't: purpose-built identity for AI agents. Open source, self-hosted, free forever.

Apache-2.0 license • Self-hosted • Works alongside Azure IAM