Project Description

Gathers evidence, performs testing, and creates audit reports in ~25 lines of code per provider (AWS, GitHub, etc).

This project is maintained and published by AuditOps.io.

Use cases:

• Vendor Due Diligence: Evaluate your vendors actual security posture using transparent and timely reports.
• Audits: Automatically collect and share high quality evidence directly to your auditor (no screenshots required).

Getting Started (AWS Example)

1. Install pre-requisites:
   • Python Tutorial
   • AWS CLI
     • Windows Tutorial
     • Mac Tutorial
2. Run these commands to check if everything is installed correctly. If you receive an error, go back to the videos in Step 1.

   python --version
   aws --version
   

3. Install the latest version of the AuditOps-SDK python library.

   pip install -U <package_name>
   

4. Create an IAM user (or Identity Center user) in the AWS management console.
   • The user needs Security Audit permissions.
5. Create an access key for the IAM user created in the previous step: AWS Docs
   • NOTE: Configure the access key on your local machine using the 'aws configure' command Video Tutorial.
   • NOTE: Access keys can only be viewed once, at the time of creation. They must be stored securely elsewhere for future use.
6. Copy the code below and name the file auditops_example.py.

   from auditops.core.models import Audit, AuditHelpers
   from auditops.providers.aws import AWSCollector, AWSTester, AWSConfig
   from auditops.core.utils import aws_create_session
   import boto3
   from datetime import datetime
   
   def main():
      session = aws_create_session()
      aws_config = AWSConfig(in_scope_regions=['us-east-1'])
      helpers = AuditHelpers.create()
   
      audit = Audit(helpers = helpers, title = "AWS Audit Report", config=aws_config, auditor_name = "AJ Dehn",
      audit_folder = "aws", delete_cached_evidence=True, summary_mode=True, exclusions=None)
   
      audit.run(collector=AWSCollector(session), tester=AWSTester())
   
      # Upload to AuditOps (for vendor due diligence and/or audit requests)
      audit.upload(destination="auditops", package="pdf", client_email="john@acme.com")    
   
      # OPTIONAL: Upload to S3 (for data retention). NOTE: Please replace the "BUCKET_NAME".
      bucket_save_path = datetime.now().strftime("%Y/%m/%d/aws")
      audit.upload(destination="s3", package="full", client=boto3.client("s3"), bucket="BUCKET_NAME", key=bucket_save_path)
   
   if __name__ == "__main__":
      main()
   
   

7. Run the code:

       python auditops_example.py
   

8. A new folder will be created for the audit. Within that folder, the library will collect and store the evidence in the 'audit_evidence' folder. Once collected, it will begin performing the testing and the audit reports will be stored in the 'reports' folder.

Design Philosophy:

1. Lightweight: You can setup this library in minutes, and it doesn't require intensive integrations with your cloud providers. This eliminates vendor lock-in and gives you control over how your data is processed.
2. Repeatability: Clear instructions explain how evidence was gathered and describes the test procedures that were performed. Share your AuditOps report + supporting evidence, and kindly ask your auditor to re-perform the work that was already done.
3. Anti-Checkbox: We all know that compliance has become a check-box exercise. We hope you'll use this library to fight against it and start holding everyone to higher standard.