Lacework Cloud Security Assessment

A tool for automating the detection of vulnerabilities, compliance violations, and exposed secrets in cloud environments, particularly AWS.

AWS Proprietary Cloud Service Only
Category Security Assessment & Audit
This page updated 22 days ago
Pricing Details Contact Lacework for pricing details.
Target Audience Cloud security teams, DevOps, and compliance officers.

The Lacework Cloud Security Assessment (CSA) addresses the complex challenge of maintaining comprehensive visibility and security in cloud environments, particularly in large and dynamic AWS deployments. This tool leverages the Lacework Polygraph® Data Platform to automate the detection of vulnerabilities, compliance violations, and exposed secrets.

Technically, the CSA deploys quickly through AWS CloudFormation, requiring only about 5 minutes of setup time. It integrates with AWS services, including CloudTrail, to collect and analyze cloud events and configuration data. This integration allows for a detailed inventory of cloud assets and the identification of misconfigurations, vulnerabilities, and anomalous behavior. The platform uses a behavior-driven approach, continuously monitoring user, application, process, and network activities to surface unknown threats and prioritize risks based on their potential impact.

Operationally, the CSA is designed for minimal manual intervention. It automates compliance reporting and evidence gathering, supporting various standards such as PCI, HIPAA, and NIST. However, it does require some post-assessment cleanup, such as manually emptying and deleting the S3 bucket created for CloudTrail logs. The assessment is typically left to run for a week or two to gather comprehensive data, after which detailed reports can be generated to highlight security and compliance issues.

Key technical details include the ability to correlate data from disparate sources, such as cloud logs, container activity, and network traffic, to provide a unified view of cloud security posture. The platform also reduces alert fatigue by filtering out false positives and focusing on critical events, which can lead to a significant reduction in manual effort and SIEM costs.

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