An Airflow UI that Is Not on the Public Internet
webserver_access_mode defaults to PUBLIC_ONLY, and the Airflow UI is not a dashboard: anyone who reaches it can trigger a DAG, which is arbitrary Python running as the execution role. PRIVATE_ONLY here, all five log streams on, and a precondition refuses an unpinned requirements.txt or plugins.zip - where bucket write access is otherwise the same permission as code execution.
Verification
Static-verifiedPassed: validated and lint-clean (provider-schema-validated for AWS/Azure/GCP; Terraform-language lint elsewhere).
Conformance
- Static validation (fmt · validate · tflint)
- Security scan clean (Checkov)
- Plan tests (mocked: validation rules · outputs)
Provenance
- SHA-256 checksum
- Signature (pending)
Functional
- Live test pending (no cloud run yet)
Last verified 2026-09-13 · how we verify
Use it from the registry
terraform · opentofumodule "mwaa" {
source = "www.iac-bazaar.com/iac-bazaar/aws-mwaa/aws"
version = "1.0.0"
}Needs a registry token from /account/tokens. The module itself is free; the account is what identifies you. Full setup: registry docs.
Inputs & outputs
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Documentation
aws-mwaa
A Managed Workflows for Apache Airflow environment whose web UI is not on the
public internet, whose logs exist, and whose dependencies cannot be changed
from underneath it. Works with Terraform and OpenTofu (>= 1.6), AWS
provider >= 6.0, < 7.0.
webserver_access_mode defaults to PUBLIC_ONLY. The Airflow UI is not a
dashboard: anyone who reaches it can trigger a DAG, and a DAG is arbitrary
Python running as the environment's execution role. The endpoint does demand
IAM credentials, so the AWS default is not an open door - it is the entire
control surface of a data platform, published, one leaked console credential
away from code execution in your account. PRIVATE_ONLY here, and
webserver_on_public_internet is an output so a policy test can assert on it.
Every log stream is off by default. All five of them - DAG processing,
scheduler, task, webserver, worker. A DAG that fails leaves no record, and so
does a DAG that succeeded while doing something it should not have. All five on
here at INFO, written as five static blocks rather than a dynamic one so
configuration scanners can actually read them.
requirements.txt and plugins.zip are arbitrary code, and MWAA reads the
latest version unless you name one. requirements.txt installs packages onto
every scheduler and worker; plugins.zip is imported as Python into the
scheduler; the startup script runs before Airflow starts at all. Without an S3
object version, "who can write this bucket" is the same permission as "who
can run code in this environment" - and it takes effect on the next
environment update, not at apply time, so nothing in your plan shows it.
A precondition refuses any of the three paths without its version.
Smaller things: exactly two subnets in two AZs, checked before the
twenty-minute create fails on it; two schedulers minimum, because one is a
single point of failure for every DAG; and kms_key defaults to an AWS-owned
key that cannot be audited or revoked, so the module takes yours.
Verification
Static validation runs tofu fmt, init, validate, tflint and checkov.
This module has not yet had a live test, so it is published as statically
validated with its live test pending and does not carry the live-tested mark.
Usage code & full reference need an account
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- Usage
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