Release 4.22

Release date: March 12th, 2026

Key benefits

• Custom Project Requirements: Tailor security activities directly within each project, allowing for technical adjustments without affecting global organization templates.
• Enhanced Data Classification: A major upgrade to our Asset risk engine that incorporates data sensitivity (from Public to Critical) into the final risk score.

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Introduction

Release 4.22 focuses on providing the flexibility and precision required for modern AppSec programs. With the launch of Custom Project Requirements, we are empowering teams to move away from rigid, "one-size-fits-all" checklists toward a more contextualized security backlog.

Additionally, we have refined our risk intelligence with Enhanced Data Classification. By integrating data sensitivity into the Asset Management workflow, the Conviso Platform now provides a more accurate view of your true risk exposure.

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Custom Project Requirements: Security with Context

Standardized security templates are essential for governance, but every project has unique technical nuances. Custom Project Requirements allows teams to bridge this gap.

When a requirement template is applied to a project, users can now:

• Customize Activities: Edit the descriptions and specific steps of an activity to match the project's tech stack.
• Refine the Scope: Ensure that stakeholders only see activities that are relevant to their specific project.
• Preserve Templates: All changes are local to the project, meaning your organizational "Golden Templates" remain consistent and secure.

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Enhanced Data Classification & Risk Scoring

We have upgraded the risk calculation within our Asset Management module. The risk of a vulnerability is now intrinsically linked to the sensitivity of the data the asset handles.

By using the new Data Classification tiers—Public, Internal, Restricted, Confidential and Critical—the platform automatically adjusts the Asset's risk priority. This ensures that security teams are always alerted first to threats affecting their most sensitive data environments.