I'm trying to use the AssumeRole in such a way that i'm traversing multiple accounts and retrieving assets for those accounts. I've made it to this point:
import boto3 stsclient = boto3.client('sts') assumedRoleObject = sts_client.assume_role( RoleArn="arn:aws:iam::account-of-role-to-assume:role/name-of-role", RoleSessionName="AssumeRoleSession1")
Great, i have the assumedRoleObject. But now i want to use that to list things like ELBs or something that isn't a built-in low level resource.
How does one go about doing that? If i may ask - please code out a full example, so that everyone can benefit.
To assume a role, an application calls the AWS STS AssumeRole API operation and passes the ARN of the role to use. The operation creates a new session with temporary credentials. This session has the same permissions as the identity-based policies for that role.
Clients vs ResourcesResources are the recommended pattern to use boto3 as you don't have to worry about a lot of the underlying details when interacting with AWS services. As a result, code written with Resources tends to be simpler.
00:00 Boto3's primary function is to make AWS API calls for you. It extracts these APIs in two main ways: clients and resources. Clients give you low-level service access, while resources provide an object-oriented way of working with these services.
Here's a code snippet from the official AWS documentation where an s3
resource is created for listing all s3
buckets. boto3
resources or clients for other services can be built in a similar fashion.
# create an STS client object that represents a live connection to the # STS service sts_client = boto3.client('sts') # Call the assume_role method of the STSConnection object and pass the role # ARN and a role session name. assumed_role_object=sts_client.assume_role( RoleArn="arn:aws:iam::account-of-role-to-assume:role/name-of-role", RoleSessionName="AssumeRoleSession1" ) # From the response that contains the assumed role, get the temporary # credentials that can be used to make subsequent API calls credentials=assumed_role_object['Credentials'] # Use the temporary credentials that AssumeRole returns to make a # connection to Amazon S3 s3_resource=boto3.resource( 's3', aws_access_key_id=credentials['AccessKeyId'], aws_secret_access_key=credentials['SecretAccessKey'], aws_session_token=credentials['SessionToken'], ) # Use the Amazon S3 resource object that is now configured with the # credentials to access your S3 buckets. for bucket in s3_resource.buckets.all(): print(bucket.name)
You can assume role using STS token, like:
class Boto3STSService(object): def __init__(self, arn): sess = Session(aws_access_key_id=ARN_ACCESS_KEY, aws_secret_access_key=ARN_SECRET_KEY) sts_connection = sess.client('sts') assume_role_object = sts_connection.assume_role( RoleArn=arn, RoleSessionName=ARN_ROLE_SESSION_NAME, DurationSeconds=3600) self.credentials = assume_role_object['Credentials']
This will give you temporary access key and secret keys, with session token. With these temporary credentials, you can access any service. For Eg, if you want to access ELB, you can use the below code:
self.tmp_credentials = Boto3STSService(arn).credentials def get_boto3_session(self): tmp_access_key = self.tmp_credentials['AccessKeyId'] tmp_secret_key = self.tmp_credentials['SecretAccessKey'] security_token = self.tmp_credentials['SessionToken'] boto3_session = Session( aws_access_key_id=tmp_access_key, aws_secret_access_key=tmp_secret_key, aws_session_token=security_token ) return boto3_session def get_elb_boto3_connection(self, region): sess = self.get_boto3_session() elb_conn = sess.client(service_name='elb', region_name=region) return elb_conn
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With