"As we started plugging in all the tools to Dazz, we could easily see the value that Dazz provides and how that value would grow in the future."

Mike Britton, CISO


Abnormal Security

Annual Revenue


- Azure


- Issue prioritization

- Tedious de-duplication

- Finding code owners for fixes


- Reduced issues to root causes: 1 ticket vs. 100s

- Reduced mean time to remediation: days or less for critical issues

- Comprehensive reporting

About the customer

Abnormal Security is a rapidly-growing technology company that provides advanced email security to prevent credential phishing, business email compromise, account takeover, and more. The team maintains its code base in GitHub and uses GitHub Actions and Terraform to run its CI/CD process and define its infrastructure.

The environment

Abnormal is a cloud-first, largely remote, rapidly-growing technology company. Its cloud environment is hosted on both Amazon Web Services (AWS) and Microsoft Azure. They maintain a modern, microservices- based environment to enable highly-elastic spikes in usage, with the ability to scale from zero to the equivalent of 20 data centers and back down again in a matter of minutes.

Efforts to secure development

To ensure a secure cloud environment and find vulnerabilities and misconfigurations, the team uses industry-leading security posture management and cloud security vulnerability solutions.

The challenges:

1. Issue prioritization

The team needed a way to quickly discover and prioritize the most critical issues in all of their alerts. For example, given 350 alerts, 300 might be low risk, 10 might be critical, and 40 might be high risk. Knowing where to focus first was important for efficiency.

2. Tedious de-duplication

The team spent too much time - often nights and weekends - manually de-duplicating the noise coming from their security tools. This meant downloading CSV files from each tool, mapping like alerts, deleting false positives, and searching for code owners.

3. Finding code owners for fixes

It was challenging to find the right code owners for fixes and arm them with context on root causes.

The solution: Dazz

The company connected the Dazz Unified Remediation Platform to their code repository and security tools via a simple API-based integration, and discovered and mapped its code-to-production development environment. In addition to connecting to code repos and security tooling, Dazz correlates data from AWS services, such as CloudTrail, ECR, and SecurityHub to unify security visibility across the customer’s development and infrastructure. This allows customers to easily prioritize and triage millions of security findings down to a few high priority remediation actions, measurably reducing risk exposure.

In a single pane of glass, Dazz showed them de-duplicated alerts and their root causes grouped by asset, vastly simplifying the view of the ephemeral virtual machines in their auto-scaling environment. Beyond reducing issues, the Dazz platform also identifies code owners, so those developers can take corrective action in a fraction of the time as before.

Finally, because of the single, cohesive view and comprehensive reporting in Dazz, the security and engineering teams are now able to audit infrastructure changes in Terraform as well as track remediation SLA adherence.

  • Discover - Understand the deployment process from code to cloud, unify cloud risk from all tools, and identify architecture gaps.
  • Reduce - Clean up the noise: deduplicate and prioritize CVEs and misconfigurations based on their unique root causes, and automatically find their owners.
  • Fix - Concise, contextual, and actionable process for remediation, from detection to deployment.

What's next?

The team is in the process of shifting all vulnerability detections to Dazz, as well as taking advantage of the automation in Dazz to further cut its remediation time.

Results summary

Reduced issues to root causes: 1 ticket vs. 100

Reduced mean time to remediation: days or less for critical issues

Comprehensive reporting

See Dazz for  yourself.

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