What Is Cloud IAM → Authentication vs Authorization → IAM Roles vs Policies → AWS IAM Deep Dive
TL;DR
- Every cloud permission is atomic: one action (
s3:GetObject) on one resource class — the indivisible unit of access - Policies group permissions into documents with conditions; roles carry policies and are assigned to identities
- Never attach policies directly to users — roles are the indirection layer that makes access auditable and revocable
- AWS roles have two required configs: trust policy (who can assume) + permission policy (what they can do) — both must be right
- GCP binds roles to resources; AWS attaches policies to identities — the mental models run in opposite directions
iam:PassRolein AWS andiam.serviceAccounts.actAsin GCP are privilege escalation vectors — always scope to specific ARNs, never*
The Big Picture
Three primitives underlie every cloud IAM system. Learn how they connect and any cloud access model becomes readable.
THE THREE-LAYER STACK
Build bottom-up. Assign top-down. Change one layer without touching the others.
┌──────────────────────────────────────────────────────────────────────┐
│ LAYER 3 — IDENTITY │
│ [email protected] · backend-service · ci-runner@proj │
│ "who is acting — a human, a service, or a machine" │
├──────────────────────────────────────────────────────────────────────┤
│ LAYER 2 — ROLE │
│ BackendDeveloper · DataAnalyst · DeployBot · S3ReadOnly │
│ "what function does this identity serve — the job title" │
├──────────────────────────────────────────────────────────────────────┤
│ LAYER 1 — POLICY │
│ AllowS3Read · AllowECRPush · DenyProdDelete · RequireMFA │
│ "what is explicitly permitted or denied, under what conditions" │
├──────────────────────────────────────────────────────────────────────┤
│ LAYER 0 — PERMISSION │
│ s3:GetObject · ecr:PutImage · s3:DeleteObject · iam:PassRole│
│ "one verb on one class of resource — the atom of access control" │
└──────────────────────────────────────────────────────────────────────┘
When alice joins the backend team → assign her the BackendDeveloper role
When the S3 bucket changes → update the policy once; alice gets it automatically
When alice leaves → remove the role assignment; policy and permissions are untouched
If this maps better to something physical:
PHYSICAL WORLD → CLOUD IAM
A specific door rule Permission s3:GetObject
Keycard access profile → Policy AllowS3Read
Job title → Role BackendDeveloper
The employee → Identity [email protected]
When the employee leaves: revoke the role assignment.
The job title, the keycard profile, the door rules — all unchanged.
Next hire gets the same role. Same access. No manual work.
Introduction
IAM roles vs policies is a distinction that defines how cloud authorization actually works — and getting it wrong is how access sprawl starts. Every authentication vs authorization failure at the authorization layer traces back to how these three primitives are — or aren’t — structured.
Every cloud IAM system — AWS, GCP, Azure — is built on the same three primitives: permissions, policies, and roles. Learn these well and any cloud provider becomes readable. Skip them and you spend years pattern-matching without understanding why anything is structured the way it is.
What Is Cloud IAM established the foundation: IAM is the system that governs who can access what in cloud infrastructure, and its default answer is always deny. Authentication vs Authorization: AWS AccessDenied Explained drew the line between authentication — proving identity — and authorization — proving you’re allowed to act. This episode is about the authorization layer specifically. These three building blocks are how authorization is expressed in practice.
Before walking through each one, here’s what access control looks like without any of this structure — because that’s the fastest way to understand why the layers exist.
In 2015 I inherited an AWS account from a 12-engineer team that had been building for 18 months. When I ran aws iam list-attached-user-policies across the 23 users, 17 had policies attached directly to the user object — not to groups, not to roles. Directly. One engineer had left six months earlier. His access key was still active. Three policies still attached: read access to prod S3, write to a DynamoDB table, ability to invoke Lambda functions. When I asked what the DynamoDB table was for, nobody could tell me. The Lambda functions no longer existed.
That account wasn’t built by negligent engineers. It was built by engineers reaching for whatever granted access fastest, under deadline, without a framework. Permissions scattered. Nothing tracked. Nothing removed.
Roles, policies, and permissions are the framework that prevents that. Understanding them is the difference between an IAM configuration you can audit in an afternoon and one that takes a week and still leaves you uncertain.
What Are IAM Permissions? The Atomic Unit of Access Control
A permission is a single action on a class of resources. It is the most granular thing you can grant or deny — the atom of access control.
Cloud providers express permissions differently, but the structure is consistent: a service, a resource type, and an action verb.
# AWS: service:Action
s3:GetObject # read an object from S3
ec2:StartInstances # start EC2 instances
iam:PassRole # assign a role to an AWS service — one of the most dangerous
kms:Decrypt # use a KMS key to decrypt
# GCP: service.resource.verb
storage.objects.get
compute.instances.start
iam.serviceAccounts.actAs # impersonate a service account — equivalent risk to iam:PassRole
cloudkms.cryptoKeyVersions.useToDecrypt
# Azure: Provider/ResourceType/Action
Microsoft.Storage/storageAccounts/blobServices/containers/read
Microsoft.Compute/virtualMachines/start/action
Microsoft.Authorization/roleAssignments/write # grant roles — highest risk
Microsoft.KeyVault/vaults/secrets/getSecret/action
You generally don’t assign individual permissions directly to identities — that’s like handing someone 47 keys with no labels and expecting the system to remain auditable. Permissions are grouped into policies.
What Are IAM Policies? Grouping Permissions with Conditions
A policy is a document that groups permissions and defines the conditions under which they apply.
AWS policy structure
An AWS policy document is JSON. Every field is a deliberate decision:
{
"Version": "2012-10-17",
"Statement": [
{
"Sid": "AllowReadS3Backups",
"Effect": "Allow",
"Action": ["s3:GetObject", "s3:ListBucket"],
"Resource": [
"arn:aws:s3:::company-backups",
"arn:aws:s3:::company-backups/*"
],
"Condition": {
"StringEquals": { "s3:prefix": ["2024/", "2025/"] }
}
},
{
"Sid": "DenyDeleteEverywhere",
"Effect": "Deny",
"Action": "s3:DeleteObject",
"Resource": "*"
}
]
}
The Sid is a comment — use it. AllowReadS3Backups tells a future auditor why this statement exists. Statement1 is technical debt.
The Effect is either Allow or Deny. A Deny always wins — it cannot be overridden by any Allow anywhere in any policy on the same identity. If you have a Deny on s3:DeleteObject with "Resource": "*", nothing can grant delete access to that identity. This asymmetry is deliberate: it’s how guardrails work.
The Resource field is where access most often creeps wider than intended. "Resource": "*" on a write action means “every resource of this type in the account.” It works. It outlives the context that made it feel reasonable.
AWS policy types — which to reach for
┌──────────────────────────┬────────────────────────────┬────────────────────────────┐
│ Type │ Attached to │ What it does │
├──────────────────────────┼────────────────────────────┼────────────────────────────┤
│ Identity-based │ User, Group, Role │ What the identity can do │
│ Resource-based │ S3 bucket, KMS key, Lambda │ Who can touch this resource │
│ Permissions boundary │ User or Role │ Maximum possible — ceiling │
│ Service Control Policy │ AWS Org OU or Account │ Org-level guardrail │
│ Session policy │ AssumeRole session │ Restricts a specific session│
│ Resource Control Policy │ AWS Org resources │ Resource-level org guardrail│
└──────────────────────────┴────────────────────────────┴────────────────────────────┘
Critical: Permissions boundaries and SCPs do not grant permissions. They constrain them. A boundary that allows s3:* doesn’t mean the identity has S3 access — it means the identity can have at most S3 access, if an identity-based policy actually grants it. Many engineers set a boundary and expect it to work as a grant. It doesn’t.
GCP policy bindings
GCP doesn’t attach policy documents to identities. Each resource has an IAM policy — a set of bindings mapping roles to members:
{
"bindings": [
{
"role": "roles/storage.objectViewer",
"members": [
"user:[email protected]",
"serviceAccount:[email protected]"
]
},
{
"role": "roles/storage.objectCreator",
"members": ["serviceAccount:[email protected]"],
"condition": {
"title": "Business hours only",
"expression": "request.time.getHours('America/New_York') >= 9 && request.time.getHours('America/New_York') < 18"
}
}
]
}
The mental model shift: in AWS you ask “what can this identity do?” by looking at the identity. In GCP you ask “who can access this resource?” by looking at the resource. The question runs in the opposite direction.
Azure role definitions
Azure separates what a role grants (role definition) from who gets it where (role assignment). Define once, assign at multiple scopes.
{
"Name": "Custom Storage Reader",
"IsCustom": true,
"Actions": [
"Microsoft.Storage/storageAccounts/blobServices/containers/read",
"Microsoft.Storage/storageAccounts/blobServices/generateUserDelegationKey/action"
],
"DataActions": [
"Microsoft.Storage/storageAccounts/blobServices/containers/blobs/read"
],
"AssignableScopes": ["/subscriptions/SUB_ID"]
}
Actions vs DataActions catches people. Actions are control plane — you can see the storage account exists. DataActions are data plane — you can read actual blob contents. A user with Actions can list the container but cannot read a single byte without a DataAction. Both planes must be covered for the access to be complete.
What Are IAM Roles? The Layer That Scales Access Control
A role is a collection of policies assigned to identities. It’s the indirection layer that makes access manageable at scale.
Going back to the 2015 account: the problem wasn’t that engineers had access — they needed it. The problem was that access was scattered across 23 individual user objects with no shared structure. This is what what is cloud IAM establishes as the core problem IAM exists to solve — and roles are the structural answer.
The role model solves this:
Policy: S3ReadAccess (s3:GetObject, s3:ListBucket on s3:::app-data/*)
↓ attached to
Role: BackendDeveloper
↓ assigned to
Users: alice, bob, charlie, dave (and six more)
When the bucket changes → update one policy
When someone joins → assign one role
When someone leaves → remove one role
Access model stays coherent because it's structured.
AWS roles — the identity that issues temporary credentials
AWS roles are themselves IAM identities, not just permission containers. When something assumes a role, it gets temporary credentials from STS. Two things must be configured:
Trust policy — who can assume:
{
"Version": "2012-10-17",
"Statement": [{
"Effect": "Allow",
"Principal": { "Service": "ec2.amazonaws.com" },
"Action": "sts:AssumeRole"
}]
}
Without this, nobody can use the role regardless of its permissions. The trust policy is the gatekeeper.
Permission policy — what it can do:
aws iam create-role \
--role-name AppServerRole \
--assume-role-policy-document file://ec2-trust-policy.json
aws iam attach-role-policy \
--role-name AppServerRole \
--policy-arn arn:aws:iam::aws:policy/AmazonS3ReadOnlyAccess
When debugging “why can’t this Lambda/EC2/ECS task do X?”, the first thing I check is the trust policy. Many times the permission policy is correct — the service simply isn’t in the trust policy and cannot assume the role at all.
GCP role types
┌──────────────────┬──────────────────────────────┬──────────────────────────────────┐
│ Type │ Example │ When to use │
├──────────────────┼──────────────────────────────┼──────────────────────────────────┤
│ Basic/Primitive │ roles/editor, roles/owner │ Never in production │
│ Predefined │ roles/storage.objectViewer │ Default — service-specific │
│ Custom │ Your org defines │ When predefined is too broad │
└──────────────────┴──────────────────────────────┴──────────────────────────────────┘
roles/editor at the project level grants write access to almost every GCP service. I’ve seen it granted “temporarily” and found it attached six months later. Always use predefined roles.
# Find the right predefined role
gcloud iam roles list --filter="name:roles/storage" --format="table(name,title)"
# See exactly what permissions it includes
gcloud iam roles describe roles/storage.objectViewer
# Create a custom role when predefined is still too broad
cat > custom-log-reader.yaml << 'EOF'
title: "Log Reader"
description: "Read application logs — nothing else"
stage: "GA"
includedPermissions:
- logging.logEntries.list
- logging.logs.list
- logging.logMetrics.get
EOF
gcloud iam roles create LogReader --project=my-project --file=custom-log-reader.yaml
Azure built-in and custom roles
# List built-in roles containing "Storage"
az role definition list --output table | grep Storage
# View what a built-in role grants
az role definition list --name "Storage Blob Data Reader"
# Create a custom role
az role definition create --role-definition custom-app-storage.json
# Assign at a specific scope
az role assignment create \
--assignee [email protected] \
--role "Storage Blob Data Reader" \
--scope /subscriptions/SUB_ID/resourceGroups/rg-prod/providers/\
Microsoft.Storage/storageAccounts/prodstore
RBAC vs ABAC: Which Access Control Model to Use
RBAC — Role-Based Access Control
The dominant model. Access flows from role membership:
alice ∈ BackendDeveloper → s3:GetObject on app-data/*
bob ∈ DataAnalyst → athena:* on analytics-queries
ci-runner ∈ DeployRole → ecr:PutImage, ecs:UpdateService
RBAC degrades two ways: role explosion (200 roles, nobody can explain what they all do) and coarse roles (avoid explosion by making roles broad, now BackendDeveloper has prod access with no distinction from dev). Both look the same on a spreadsheet — lots of access, no clear principle.
ABAC — Attribute-Based Access Control
ABAC grants access based on attributes of the principal, resource, or environment — not role membership. This one policy replaced 12 team-specific policies in one account:
{
"Effect": "Allow",
"Action": "ec2:*",
"Resource": "*",
"Condition": {
"StringEquals": {
"aws:ResourceTag/Team": "${aws:PrincipalTag/Team}"
}
}
}
An engineer tagged Team=Platform can only act on EC2 resources tagged Team=Platform. Add a new team — tag their resources and their identity. No new policy. No new role.
The risk is tag drift. If someone tags a resource incorrectly, the access model breaks silently. I use ABAC for environment and team scoping, and explicit policies for sensitive services like KMS and IAM. How these primitives combine in a full AWS account is covered in the AWS IAM deep dive.
Conditions — when context determines access
// Require MFA for any IAM or Organizations action
{
"Effect": "Deny",
"Action": ["iam:*", "organizations:*"],
"Resource": "*",
"Condition": { "BoolIfExists": { "aws:MultiFactorAuthPresent": "false" } }
}
// Restrict to corporate IP range
{
"Effect": "Deny",
"Action": "*",
"Resource": "*",
"Condition": {
"NotIpAddress": { "aws:SourceIp": ["10.0.0.0/8", "172.16.0.0/12"] }
}
}
The MFA condition is in every account I manage. A compromised API key without an MFA session can’t escalate IAM privileges — the Deny blocks it at the condition level. This single statement meaningfully reduces the blast radius of a credential compromise.
⚠ Production Gotchas
╔══════════════════════════════════════════════════════════════════════╗
║ ⚠ GOTCHA 1 — Policies attached directly to users ║
║ ║
║ Feels fast. Creates the exact problem from 2015: access scattered ║
║ across individual user objects with no shared structure. ║
║ When the user leaves, their policies don't follow — they stay. ║
║ ║
║ Fix: always use roles. Attach policies to roles. Assign roles to ║
║ users. The role outlives the person. ║
╚══════════════════════════════════════════════════════════════════════╝
╔══════════════════════════════════════════════════════════════════════╗
║ ⚠ GOTCHA 2 — Using AWS managed policies in production ║
║ ║
║ AmazonS3FullAccess grants s3:* on *. For a Lambda that reads one ║
║ specific bucket, that's ~30 permissions you didn't need, all live. ║
║ ║
║ Fix: create customer managed policies scoped to the specific ║
║ actions and ARNs the workload actually uses. ║
╚══════════════════════════════════════════════════════════════════════╝
╔══════════════════════════════════════════════════════════════════════╗
║ ⚠ GOTCHA 3 — iam:PassRole with "Resource": "*" ║
║ ║
║ iam:PassRole lets an identity assign a role to an AWS service. ║
║ With Resource: *, it can pass ANY role — including ones with more ║
║ permissions than it currently has. That is a privilege escalation. ║
║ ║
║ Fix: always scope iam:PassRole to a specific role ARN: ║
║ "Resource": "arn:aws:iam::ACCOUNT:role/SpecificRoleName" ║
╚══════════════════════════════════════════════════════════════════════╝
╔══════════════════════════════════════════════════════════════════════╗
║ ⚠ GOTCHA 4 — Permissions boundary ≠ policy grant ║
║ ║
║ Setting a boundary that allows s3:* does NOT grant S3 access. ║
║ The boundary is a ceiling — it limits maximum possible permissions. ║
║ The identity-based policy still needs to explicitly Allow the ║
║ action. Both must be present for the access to work. ║
╚══════════════════════════════════════════════════════════════════════╝
Cross-Cloud Rosetta Stone
Same concepts, different names and different directions. Bookmark this table.
┌─────────────────────────┬──────────────────────────┬──────────────────────────┬──────────────────────────┐
│ Concept │ AWS │ GCP │ Azure │
├─────────────────────────┼──────────────────────────┼──────────────────────────┼──────────────────────────┤
│ Atomic permission │ s3:GetObject │ storage.objects.get │ .../blobs/read │
│ Permission document │ Policy (JSON) │ (built into role def) │ Role Definition │
│ Access grant │ Policy attachment │ IAM Binding │ Role Assignment │
│ Job-function identity │ IAM Role │ Predefined Role │ Built-in Role │
│ Non-human identity │ IAM Role (assumed) │ Service Account │ Managed Identity │
│ Org-level guardrail │ SCP │ Org Policy │ Management Group Policy │
│ Permission ceiling │ Permissions Boundary │ — │ — │
│ Session restriction │ Session Policy │ — │ — │
│ Attribute-based grant │ Tag conditions in policy │ IAM Conditions │ Conditions in assignment │
└─────────────────────────┴──────────────────────────┴──────────────────────────┴──────────────────────────┘
Quick Reference
┌──────────────────────────┬────────────────────────────────────────────────────────────┐
│ Term │ What it is │
├──────────────────────────┼────────────────────────────────────────────────────────────┤
│ Permission │ Atomic: one action on one resource class │
│ Policy │ Document grouping permissions + conditions │
│ Role (AWS) │ Assumable identity — carries policies, issues temp creds │
│ Trust policy (AWS) │ Who can assume this role — separate from permissions │
│ Permissions boundary │ Ceiling — limits max possible permissions; does not grant │
│ SCP │ Org guardrail — constrains all identities in scope │
│ IAM Binding (GCP) │ Maps a role to a member on a specific resource │
│ Role Assignment (Azure) │ Grants a role definition at a specific scope │
│ ABAC │ Access by tag/attribute — one policy replaces many roles │
│ RBAC │ Access by role membership — clean until roles proliferate │
│ iam:PassRole │ Privilege escalation vector — always scope to specific ARN │
└──────────────────────────┴────────────────────────────────────────────────────────────┘
Commands to know:
┌────────────────────────────────────────────────────────────────────────────────┐
│ # AWS — list policies attached to a role │
│ aws iam list-attached-role-policies --role-name MyRole │
│ │
│ # AWS — view what a managed policy actually grants │
│ aws iam get-policy-version \ │
│ --policy-arn arn:aws:iam::aws:policy/AmazonS3ReadOnlyAccess \ │
│ --version-id v1 │
│ │
│ # AWS — who can assume this role? │
│ aws iam get-role --role-name MyRole --query 'Role.AssumeRolePolicyDocument' │
│ │
│ # GCP — view the IAM policy on a project │
│ gcloud projects get-iam-policy PROJECT_ID --format=json │
│ │
│ # GCP — list all roles and what permissions they include │
│ gcloud iam roles describe roles/storage.objectViewer │
│ │
│ # Azure — list role assignments in a subscription │
│ az role assignment list --all --output table │
│ │
│ # Azure — view exactly what a built-in role grants │
│ az role definition list --name "Storage Blob Data Reader" │
└────────────────────────────────────────────────────────────────────────────────┘
Framework Alignment
| Framework | Reference | What It Covers Here |
|---|---|---|
| CISSP | Domain 5 — Identity and Access Management | RBAC and ABAC are the implementation models for authorization at scale |
| CISSP | Domain 1 — Security & Risk Management | Role design implements separation of duties and least privilege |
| ISO 27001:2022 | 5.15 Access control | Access control policy — roles and policies are the mechanism |
| ISO 27001:2022 | 5.18 Access rights | Provisioning, review, and removal of access rights — roles make this auditable |
| ISO 27001:2022 | 8.2 Privileged access rights | Permissions boundaries and conditions applied to elevated access |
| SOC 2 | CC6.1 | Logical access security — policy documents are the technical implementation |
| SOC 2 | CC6.3 | Access revocation — role-based model makes removal consistent and auditable |
Key Takeaways
- Permissions are atomic — one action on one resource class. Policies group permissions. Roles carry policies for assignment
- AWS roles have two required configs: trust policy (who can assume) and permission policy (what it can do) — both must be correct
- GCP binds roles to resources; AWS attaches policies to identities — the mental model runs in opposite directions
- Azure separates role definition (what) from role assignment (who, where) — define once, assign at multiple scopes
- RBAC scales through role design; ABAC scales through tag/attribute conditions — use ABAC where roles would proliferate
iam:PassRoleandiam.serviceAccounts.actAsare privilege escalation vectors — scope them to specific ARNs, never*- Conditions add context (MFA, IP, tags, time) to policies — the MFA condition on IAM actions is essential in every account
What’s Next
EP04 goes deep on AWS IAM — the most complex of the three cloud models. Policy evaluation order, cross-account trust, permissions boundaries in practice, SCPs, and IAM Identity Center for human access. We’ll work through the patterns that make AWS IAM maintainable at production scale.
Next: AWS IAM Deep Dive: Users, Groups, Roles, and Policies Explained
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