1. Understand the Purpose of Data Scans

Before initiating a data scan, clearly define your objectives. Common goals include:

• Identifying sensitive data like Social Security numbers, credit card numbers, or passwords.
• Detecting misconfigured files or improper data storage.
• Supporting compliance with regulations like GDPR, HIPAA, or PCI-DSS.
• Gaining insight into the organization’s data exposure.

2. Preparation Before Running a Data Scan

a. Define the Scope of the Scan

• Targeted Data Types: Choose specific categories to scan (e.g., financial information, healthcare records).
• Locations: Identify areas to scan, such as endpoints, servers, cloud storage (OneDrive, Google Drive), or email systems.
• Sample Size: For large datasets, start with a sample to avoid overwhelming the scan process.

b. Ensure Proper Permissions

• Confirm that your scanning agents have the necessary permissions for the selected data sources.
• If scanning Office 365 or Google Workspace, validate that app registrations and permissions are correctly configured.

c. Prepare the Environment

• Ensure devices are powered on and connected to the network for endpoint scans.
• Designate a machine with sufficient resources if using a local cloud agent for large scans.

3. Running the Scan

a. Choose the Right Scan Type

• Probing Scans: Use one agent to scan multiple endpoints or directories. Ideal for prospecting scenarios.
• Full Agent Scans: Deploy agents across all endpoints to gather comprehensive data.

b. Select Scan Parameters

• Use default categories for common sensitive data like Social Security numbers, credit card numbers, and passwords.
• Add custom regex patterns for unique identifiers or client-specific data needs.
• Limit the scan range (e.g., 30, 60, or 90 days) to reduce processing time and focus on recent activity.

c. Optimize Scanning Speed

• For large environments, use local cloud agents to bypass shared agent queues and expedite results.
• Avoid scanning massive datasets in a single session. Instead, scan in manageable chunks.

4. Analyze Scan Results Effectively

Once the scan is complete, follow these steps to maximize the impact of the findings:

a. Review Results in Detail

• Filter results by data type, location, or severity.
• Prioritize high-risk items, such as sensitive data stored in unsecured locations or exposed to unauthorized users.

b. Validate Findings

• Cross-check flagged data to ensure accuracy and reduce false positives.
• Use context to determine whether flagged items pose a genuine risk.

c. Act on Findings

• Share results with relevant stakeholders, such as IT or compliance teams.
• Take immediate action to secure sensitive data or remediate vulnerabilities.

5. Post-Scan Recommendations

a. Schedule Regular Scans

• Set up periodic scans (e.g., monthly, quarterly) to maintain an up-to-date understanding of your data landscape.

b. Create Actionable Reports

• Use CYRISMA’s reporting features to generate executive summaries or detailed technical reports.
• Include recommendations and next steps to help stakeholders act on the findings.

c. Monitor Changes Over Time

• Use duration-based reports to compare scans over time and track progress in securing sensitive data.

6. Best Practices for Specific Data Scenarios

a. Email Scans

• Focus on email accounts likely to contain sensitive information (e.g., C-level executives, finance team).
• Limit the scan to recent email history (e.g., 90 days) to capture relevant data without overwhelming the system.

b. Cloud Storage Scans

• Target high-priority areas like shared folders or external collaboration spaces.
• Identify and secure sensitive files stored in OneDrive, Google Drive, or SharePoint.

c. Endpoint Scans

• Deploy agents on a sample of endpoints if conducting a prospecting scan.
• For full scans, ensure all critical devices are covered to reduce blind spots.

7. Common Pitfalls to Avoid

• Overloading the Scan: Scanning too many locations or data types at once can delay results. Use a phased approach for large environments.
• Inadequate Permissions: Scans may fail or yield incomplete results if agents lack the required access.
• Neglecting Follow-Up: Scanning without acting on findings diminishes the value of the process.

8. Conclusion

Data scans are a cornerstone of any robust cybersecurity strategy. By following these best practices, you can ensure your scans are effective, actionable, and aligned with organizational goals. CYRISMA’s powerful data scanning tools, combined with thoughtful preparation and analysis, provide a comprehensive approach to managing sensitive data and mitigating risks.