Picture this: your application works perfectly on your local machine. You deploy it to AWS, then immediately hit an “Access Denied” error.

If you’ve worked with AWS for any length of time, you’ve experienced this. What follows is usually a frustrating dive into IAM documentation, trial-and-error permission updates, and lost development momentum.

AWS Labs created IAM Policy Autopilot to solve exactly this problem.

IAM Policy Autopilot analyzes your application code and generates AWS IAM policies based on the actual SDK calls your code makes. No guessing. No hallucinated permissions. Just deterministic, repeatable policy generation.

What Is IAM Policy Autopilot?

IAM Policy Autopilot is an open-source tool from AWS Labs that generates IAM identity-based policies by statically analyzing your application code.

It was released publicly in November 2025 and is available as:

• A command-line tool
• A Model Context Protocol (MCP) server for AI coding assistants

Unlike AI-generated IAM snippets that often include invalid or overly broad permissions, IAM Policy Autopilot uses deterministic static analysis. The same input code will always produce the same policy.

Supported Languages

Currently supported:

• Python
• Go
• TypeScript

How IAM Policy Autopilot Works

Static Code Analysis (Not Guesswork)

IAM Policy Autopilot scans your source code and identifies AWS SDK calls. Each SDK call is mapped to the corresponding IAM action using AWS service references.

Example:

s3.put_object(…)

Generated permission:

“s3:PutObject”

Cross-Service Dependency Awareness

The tool understands common AWS service interactions.

For example:

• Writing to an S3 bucket with KMS encryption also requires:
  • kms:GenerateDataKey
• DynamoDB Streams involve both:
  • DynamoDB permissions
  • Stream processing permissions

These additional permissions are generated automatically when required.

Why IAM Policy Autopilot Is Different

1. Deterministic and Repeatable

This is not an LLM guessing permissions. The output is consistent and reproducible which is critical for CI/CD pipelines.

2. AI Assistant Integration via MCP

When integrated with tools like:

• Claude Code
• Cursor
• Amazon Q Developer
• Cline

Your AI assistant can generate IAM policies using real policy analysis, not hallucinated suggestions.

3. Designed for Rapid AWS Evolution

IAM Policy Autopilot is updated alongside AWS service references, reducing the risk of outdated permissions when AWS releases new features.

Ways to Use IAM Policy Autopilot

CLI Mode

Best for:

• Terminal-driven workflows
• CI/CD automation
• Infrastructure-as-code pipelines

MCP Server Mode

Best for:

• AI-assisted development
• Interactive policy generation while coding

Both modes generate identical policies.

Installing IAM Policy Autopilot

Quick Install (macOS/Linux)

curl -sSL https://github.com/awslabs/iam-policy-autopilot/raw/refs/heads/main/install.sh | sudo sh

Using uvx (No System Install)

uvx iam-policy-autopilot

Using pip

pip install iam-policy-autopilot

Real-World Use Cases

Microservices with Fine-Grained Permissions

Each service can generate policies tailored only to its actual AWS usage—no shared, over-permissive roles.

Event-Driven Architectures

Automatically generate permissions for:

• S3
• SQS
• EventBridge
• Lambda

Based solely on application behavior.

Reducing Over-Permissive Policies

When starting from Infrastructure Composer or templates with wildcard permissions, IAM Policy Autopilot helps tighten policies to reflect real usage.

Security Impact

According to internal AWS comparisons, policies generated by IAM Policy Autopilot contained up to 97% fewer permissions than typical manually written developer policies.

This doesn’t mean the output is always perfectly least-privilege, but it is a significantly safer starting point.

Limitations You Should Know

Dynamic Resource Names

Static analysis cannot infer runtime-generated ARNs. You must manually scope resources when needed.

Identity-Based Policies Only

IAM Policy Autopilot does not generate:

• S3 bucket policies
• KMS key policies
• SCPs or RCPs
• Permission boundaries

API Name Collisions

APIs like ListAccounts exist in multiple AWS services. Use –service-hints to disambiguate.

Best Practices for Production Use

1. Generate policies during development
2. Review and scope resources explicitly
3. Validate with IAM Access Analyzer
4. Monitor with CloudTrail
5. Continuously refine permissions over time

IAM Policy Autopilot accelerates development—but human review remains essential.

Conclusion

IAM Policy Autopilot changes how developers interact with AWS IAM. Instead of treating permissions as a painful afterthought, it makes them a natural part of the development workflow.

It won’t replace IAM expertise—but it dramatically reduces friction, errors, and wasted time.

If you build on AWS, this tool deserves a place in your workflow.

Resources:

• https://aws.amazon.com/about-aws/whats-new/2025/11/iam-policy-autopilot-generate-iam-policies-code/
• https://aws.amazon.com/blogs/aws/simplify-iam-policy-creation-with-iam-policy-autopilot-a-new-open-source-mcp-server-for-builders/
• https://github.com/awslabs/iam-policy-autopilot