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Security App for Jira || Feasability Doc

Security App for Jira || Feasability Doc

Owned by Naveen Kumar C, created
Last updated: Nov 26, 2024
2 min read

Objective

Develop and deploy a Jira Secret Scanner to identify sensitive information such as passwords, API keys, private keys, and other secrets in Jira projects, issues, and histories, mitigating the risk of data leakage and privilege escalation.

Key Features

  1. Automated Scanning Capabilities

    • Project and Issue Scanning: Perform scans on entire projects or specific issues to detect sensitive content.

    • Issue History Review: Include issue history to ensure sensitive data in older updates is identified.

  2. Built-in and Custom Patterns

    • Predefined Patterns: Out-of-the-box support for detecting common sensitive data types (e.g., AWS keys, OAuth tokens, SSH keys, and passwords).

    • Custom Regex Rules: Administrators can define organization-specific patterns for scanning.

  3. Regulatory Compliance

    • Demonstrates adherence to standards like GDPR, HIPAA, and CAIQ by detecting and managing sensitive information.

  4. User-friendly Interface

    • Security Analysis Dashboard:

      • Accessible via the Jira sidebar for project administrators.

      • Displays scan results with actionable insights.

    • Easy navigation to scan individual issues.

  5. Future Capabilities (Planned Enhancements)

    • Comment and Attachment Scanning: Extend the scanning scope to include issue comments and attachments.

 

Business Impact

Risk Mitigation

  • Prevent attackers or malicious insiders from accessing sensitive information that could lead to privilege escalation.

  • Reduce the likelihood of breaches resulting from improperly stored secrets.

Regulatory Compliance

  • Enhance compliance with security standards, reducing penalties for non-compliance.

Operational Efficiency

  • Automate the identification of sensitive information, minimizing the need for manual audits.

 

Technical Feasibility

Integration with Jira Cloud

  • Leverage Jira’s APIs to fetch project, issue, and history data for scanning.

Detection Mechanisms

  • Regex-based Rules: Efficient and highly customizable for detecting predefined and organization-specific sensitive patterns.

Security Considerations

  • Data in transit and storage should be encrypted to protect sensitive findings.

  • Restrict access to Security Analysis tools to Jira and project administrators.

Scalability

  • Scanning workflows can be batched to handle large Jira instances without performance degradation.

  • Use paginated requests for issues to optimize API calls.

 

Implementation Phases

Phase 1: Core Features

  • Project and issue scanning.

  • Regex-based detection for built-in patterns.

  • Security Analysis dashboard for findings display.

Phase 2: Enhancements

  • Comment and attachment scanning.

  • Advanced false positive workflows.

  • Custom rule builder for non-technical users.

 

Potential Risks and Mitigation

Risk

Impact

Mitigation Strategy

Risk

Impact

Mitigation Strategy

High false positive rate

Reduced usability

Implement robust regex and allow false-positive management.

Large data volumes slowing performance

Delayed workflows

Batch scans and use paginated API calls.

Unauthorized access to scan results

Data breach

Implement role-based access and encrypt stored results.

Conclusion

The development of the Security for Jira app is technically and operationally feasible. It addresses a critical gap in Jira’s functionality, with strong market potential due to the increasing emphasis on data security.

We can add extra feature as to generate the downloadable reports for identified issues.