I was provisioned some AWS keys. These keys give me access to certain directories in a s3 bucket. I want to use boto3 to interact with the directories that were exposed to me, however it seems that I can't actually do anything with the bucket at all, since I don't have access to the entire bucket.
This works for me from my terminal:
aws s3 ls s3://the_bucket/and/this/specific/path/
but if I do:
aws s3 ls s3://the_bucket/
I get:
An error occurred (AccessDenied) when calling the ListObjects
operation: Access Denied
which also happens when I try to access the directory via boto3.
session = boto3.Session(profile_name=my_creds)
client=session.client('s3')
list_of_objects = client.list_objects(Bucket='the_bucket', Prefix='and/this/specific/path', Delimiter='/')
Do I need to request access to the entire bucket for boto3 to be usable?
You need to set this Bucket Policy:
{
"Sid": "<SID>",
"Effect": "Allow",
"Principal": {
"AWS": "arn:aws:iam::<account>:user/<user_name>"
},
"Action": [
"s3:GetBucketLocation",
"s3:ListBucket"
],
"Resource": "arn:aws:s3:::<bucket_name>"
}
For more information about Specifying Permissions in a Policy
Related
I have an S3 bucket with a given access_key and secret_access_key. I use the following code to upload files into my S3 bucket successfully.
import boto3
import os
client = boto3.client('s3',
aws_access_key_id = access_key,
aws_secret_access_key = secret_access_key)
upload_file_bucket = 'my-bucket'
upload_file_key = 'my_folder/' + str(my_file)
client.upload_file(file, upload_file_bucket, upload_file_key)
Now, I want to upload my_file into another bucket that is owned by a new team. Therefore, I do not have access to access_key and secret_access_key. What is the best practice to do cross-account file upload using boto3 and Python?
You can actually use the same code, but the owner of the other AWS Account would need to add a Bucket Policy to the destination bucket that permits access from your IAM User. It would look something like this:
{
"Version": "2012-10-17",
"Statement": [
{
"Action": [
"s3:PutObject",
"s3:PutObjectAcl"
],
"Effect": "Allow",
"Resource": "arn:aws:s3:::their-bucket/*",
"Principal": {
"AWS": [
"arn:aws:iam::YOUR-ACCOUNT-ID:user/username"
]
}
}
]
}
When uploading objects to a bucket owned by another AWS Account I recommend adding ACL= bucket-owner-full-control , like this:
client.upload_file(file, upload_file_bucket, upload_file_key, ExtraArgs={'ACL':'bucket-owner-full-control'})
This grants ownership of the object to the bucket owner, rather than the account that did the upload.
I am uploading a file to s3 using the following code:
s3.meta.client.upload_file(file_location, bucket_name, key,ExtraArgs={'ACL': 'public-read'})
When I use ACL: Public read, my code returns with the following error that I do not have permission to do this.
"errorMessage": "Failed to upload test.xlsx: An error occurred (AccessDenied) when calling the PutObject operation: Access Denied"
"errorType": "S3UploadFailedError"
Below is an IAM policy attached to my user.
{
"Version": "2012-10-17",
"Statement": [
{
"Sid": "VisualEditor0",
"Effect": "Allow",
"Action": "s3:*",
"Resource": "*"
}
]
}
Amazon S3 block public access prevents the application of any settings that allow public access to data within S3 buckets. Right now ACL operation is denied.
Please turn on the
"Block public access to buckets and objects granted through new access control lists (ACLs)" settings from Permissions >> Block Public access
I'm using Amazon S3 in a Flask Python application, however, I don't want to hardcode my access keys as Amazon has problems with making the keys publicly available. Is there a way to get the keys into the application without exposing them. I saw a suggestion about using environment variables and another about IAM User roles but the documentation isn't helping.
Edit: I forgot to mention that I'm deploying this application on Docker and want to allow it so that if another user pulls the image from docker, my access keys won't be compromised. I'm not using AWS EC2
Following could be of help:
IAM Roles (If your application is already running in AWS, Instance Roles can help you fetch temporary tokens to access resources like S3. AWS CLIs OR official SDKs are already built with these capabilities and you need not implement any custom code. For this to work, you assign a Role 'X' to the EC2 instance, Role 'X' then needs to have a policy mapping, where you define the permissions)
A sample policy could be something like:
{
"Version": "2012-10-17",
"Statement": [
{
"Sid": "AllowAccessToObjects",
"Action": [
"s3:PutObject",
"s3:PutObjectAcl",
"s3:GetObject",
"s3:GetObjectAcl",
"s3:GetObjectVersion",
"s3:GetObjectVersionAcl",
"s3:ListMultipartUploadParts"
],
"Effect": "Allow",
"Resource": [
"arn:aws:s3:::<Bucket_Name>/*"
],
"Condition": {
"IpAddress": {
"aws:SourceIp": [
"w.x.y.z/32"
]
}
}
},
{
"Sid": "AllowAccessToBucket",
"Action": [
"s3:PutObject",
"s3:ListBucket",
"s3:GetBucketVersioning",
"s3:ListBucketVersions"
],
"Effect": "Allow",
"Resource": [
"arn:aws:s3:::<Bucket_Name>"
],
"Condition": {
"IpAddress": {
"aws:SourceIp": [
"a.b.c.d/32"
]
}
}
}
]
}
Usually the best approach is to never have any statically provisioned credentials at all. In case implementing something like that is not possible at all, then :
Other options could be storing the secrets in an external secret store like Vault etc., and when the container starts, the secrets can be fetched and injected before bootstrapping the application. These are then available as ENVs
The Python AWS SDK looks at several possible locations for credentials. The most pertinent here would be environment variables:
Boto3 will check these environment variables for credentials:
AWS_ACCESS_KEY_ID
The access key for your AWS account.
AWS_SECRET_ACCESS_KEY
The secret key for your AWS account.
You should create separate IAM users with appropriate permissions for each user or team you're going to distribute your docker image to, and they can set those environment variables via docker when running your image.
I have created a S3 bucket and created a file under my aws account. My account has trust relationship established with another account and I am able to put objects into the bucket in another account using Boto3. How can I copy objects from bucket in my account to bucket in another account using Boto3?
I see "access denied" when I use the code below -
source_session = boto3.Session(region_name = 'us-east-1')
source_conn = source_session.resource('s3')
src_conn = source_session.client('s3')
dest_session = __aws_session(role_arn=assumed_role_arn, session_name='dest_session')
dest_conn = dest_session.client ( 's3' )
copy_source = { 'Bucket': bucket_name , 'Key': key_value }
dest_conn.copy ( copy_source, dest_bucket_name , dest_key,ExtraArgs={'ServerSideEncryption':'AES256'}, SourceClient = src_conn )
In my case , src_conn has access to source bucket and dest_conn has access to destination bucket.
I believe the only way to achieve this by downloading and uploading the files.
AWS Session
client = boto3.client('sts')
response = client.assume_role(RoleArn=role_arn, RoleSessionName=session_name)
session = boto3.Session(
aws_access_key_id=response['Credentials']['AccessKeyId'],
aws_secret_access_key=response['Credentials']['SecretAccessKey'],
aws_session_token=response['Credentials']['SessionToken'])
Another approach is to attach a policy to the destination bucket permitting access from the account hosting the source bucket. eg. something like the following should work (although you may want to tighten up the permissions as appropriate):
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Principal": {
"AWS": "arn:aws:iam::<source account ID>:root"
},
"Action": "s3:*",
"Resource": [
"arn:aws:s3:::dst_bucket",
"arn:aws:s3:::dst_bucket/*"
]
}
]
}
Then your Lambda hosted in your source AWS account should have no problems writing to the bucket(s) in the destination AWS account.
Trying to follow this tutorial and I keep getting "Access Denied" when running my Lambda. The Lambda is the default s3-python-get-object.
The role for the lambda is
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"s3:GetObject",
"s3:DeleteObject"
],
"Resource": [
"arn:aws:s3:::*"
]
}
]
}
The user has admin privileges. I just don't get why it's going wrong.
From the docs:
If the object you request does not exist, the error Amazon S3 returns depends on whether you also have the s3:ListBucket permission.
If you have the s3:ListBucket permission on the bucket, Amazon S3 returns an HTTP status code 404 ("no such key") error.
If you don’t have the s3:ListBucket permission, Amazon S3 returns an HTTP status code 403 ("access denied") error.
The code above seems right for the operation you do.
Please make sure you have the key you are calling or add s3:ListBucket permission to be sure of the kind of error.