Comparison Guide

AIM vs Google Cloud IAM for AI Agents

Compare open source agent identity management with Google Cloud IAM's resource access control. Different scopes, different 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

Google Cloud IAM

by Google Cloud

Resource-level access control for Google Cloud. Manage who (identity) can do what (roles) on which resources. Service accounts for workloads.

Managed ServiceResource AccessGCP Native

Key Distinction: Agent Identity vs Resource Access

Google Cloud IAM controls access to GCP resources (who can access what in your cloud). AIM manages AI agent identity (cryptographic proof, behavioral trust, capabilities). GCP IAM asks "can this principal access this resource?" while AIM asks "is this agent trustworthy?" Service accounts provide machine identity for GCP access, but not AI-specific trust scoring or capability enforcement.

Feature Comparison

FeatureAIMGoogle Cloud IAM
Primary FocusAI agent identityGCP resource access control
Licensing Apache-2.0 (Free)Included with GCP (pay for resources)
Deployment Self-hosted or CloudGCP managed only
Cryptographic Agent Identity Ed25519 per agentService account keys (not agent-specific)
Continuous Trust Scoring 8-factor real-time Not available
Capability-Based Access Code-level enforcementRole-based (predefined + custom)
MCP Server Attestation Native support Not supported
AI Framework Integration LangChain, CrewAI, etc. Not applicable
Service AccountsNot applicable Core feature
Workload Identity FederationNot applicable AWS, Azure, OIDC
Resource Hierarchy PoliciesNot applicable Org, folder, project
Vendor Lock-in None (portable)GCP ecosystem
Source Code Access Full access Closed source
Cost Model Free foreverFree (pay for GCP 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

GCP IAM: Resource Access Layer

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

  • Control access to GCP services
  • Role-based permissions (viewer, editor, owner)
  • Service accounts for workloads
  • Organization-wide policy 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 GCP IAM if you...

  • Need to control access to GCP resources
  • Managing human user access to cloud
  • Need service accounts for workloads
  • Want organization-wide security policies
  • Using GCP-native services (GKE, Cloud Run)
  • Need workload identity federation
  • Managing BigQuery, Cloud Storage access

Time to Secure Your First Agent

5 Minutes

with AIM

pip install → secure() → done

N/A

with GCP IAM

GCP IAM manages resource access, not agent identity

Different Approaches

AIM secures the agent itself. GCP IAM controls what 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

GCP IAM: Resource Access

# Grant access to GCP resources
# via service account

gcloud iam service-accounts \
  create my-agent-sa

gcloud projects add-iam-policy \
  --member="sa:my-agent-sa" \
  --role="roles/bigquery.user"

# Controls GCP resource access
# Not agent-level identity

Use Both Together

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

  • AIM verifies and manages agent identity with trust scoring
  • GCP IAM controls what GCP resources the agent can access
  • AIM trust score can gate service account access
  • AIM can run on GKE with Workload Identity

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

Building with Vertex AI?

If you're building AI agents with Vertex AI, GCP IAM controls access to Vertex AI resources, 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 Vertex-powered agents.

Start Securing Your AI Agents Today

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

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