Hammer

Dow Jones Hammer manages identifying and mitigating misconfigurations and insecure data exposures across multiple AWS accounts and regions. This tool leverages a robust technical architecture that includes AWS services such as Lambda, DynamoDB, EC2, SNS, CloudWatch, and CloudFormation, along with Terraform for infrastructure management.

At its core, Hammer uses Python 3.6 to execute its logic, integrating with various AWS resources to scan for security vulnerabilities like S3 ACL and policy public access, IAM user inactive keys and key rotation issues, CloudTrail logging problems, unencrypted EBS volumes and RDS instances, and public access to SQS, AMIs, and RDS snapshots. The tool provides near real-time reporting through integrations with JIRA and Slack, enabling quick feedback and remediation actions.

Operationally, Hammer allows for auto-remediation of some misconfigurations, which helps in maintaining secure guardrails around cloud deployments. However, it is important to note that the effectiveness of auto-remediation can be limited by the complexity of the misconfiguration and the permissions granted to the tool. Additionally, while Hammer offers comprehensive visibility, managing and scaling the tool across large, multi-account AWS environments can introduce complexities, particularly in terms of resource utilization and cost management.

From a technical standpoint, Hammer's use of AWS Lambda for event-driven processing and DynamoDB for data storage ensures scalable and efficient operation. However, the tool's performance and cost efficiency can be impacted by the volume of resources being monitored and the frequency of scans. For example, frequent scans can lead to increased Lambda invocation costs and DynamoDB read/write operations, which need to be carefully managed to avoid unexpected expenses.