I'm working on an AWS SES project where I need to keep a trace of the metadata, content and attachments of sent emails for audit purposes. Specifically, I want to retrieve the data of an email that has already been sent using SES and save it in the .msg or .eml format.

Here's the scenario:

Emails are sent via SES. I want to retrieve the metadata (headers, subject, recipients, etc.) of a particular email that has already been sent. Save this metadata in a .msg file for auditing. I'm aware that SES doesn't provide direct support for retrieving sent email metadata in the .msg format. However, I'm looking for guidance on the best practices or alternative approaches to achieve this.

Is there a recommended way to retrieve data (such as headers, subjects, and recipients) of an email that has already been sent through SES? Additionally, how can I convert this metadata into the .msg format for archival and audit purposes?

Any code snippets, libraries, or architectural suggestions would be highly appreciated. Thank you!

In the context of an AWS SES project where you aim to retrieve and save metadata of sent emails in .msg or .eml format for auditing purposes, you can consider the following approach:

1. SES Configset Event Destinations:

Leverage SES Configset Event Destinations to capture metadata about sent emails. Although SES doesn't directly support saving in .msg it .eml format, you can store the metadata in a structured manner (e.g., JSON) in an S3 bucket or a database.

2. AWS Lambda Integration:

Utilize AWS Lambda to process SES events and extract relevant metadata. Convert the extracted metadata into the desired .msg format using libraries like email.message in Python. Here's a simple example in Python:

import email.message
import json

def process_ses_event(event, context):
    # Extract metadata from SES event
    message_id = event['Records'][0]['ses']['mail']['messageId']
    subject = event['Records'][0]['ses']['mail']['commonHeaders']['subject']
    recipients = event['Records'][0]['ses']['receipt']['recipients']

    # Create an EmailMessage object
    msg = email.message.EmailMessage()
    msg['Message-ID'] = message_id
    msg['Subject'] = subject
    msg['To'] = ', '.join(recipients)

    # Convert metadata to .msg format
    msg_data = msg.as_bytes()

    # Save .msg file to S3 or local storage
    # Add your storage logic here

    print("Metadata saved successfully.")

Customize this Lambda function according to your needs.

Remember to set up SES event destinations to trigger the Lambda function.

Archival Storage: Decide on a storage solution (S3, database, etc.) based on your needs. Implement logic to organize and store metadata, ensuring it aligns with your auditing requirements. Remember, the example provided is a basic illustration. Adjust it based on your specific use case and language preferences.

Additional Resources: AWS SES Configset Event Destinations

Feel free to adapt and expand upon this solution to fit your project's requirements. Good luck!