Analysis Tools - Source Data Concerns Index
Per-Source Report Directory
Hashmire/Analysis_Tools 0.3.0
What am I looking at?
Click to learn how to use this dashboard
The Source Data Concern Dashboard is designed to help CVE Program stakeholders systematically review and refine the data they have contributed to CVE records for improved platform identification automation. Targeting Problem Domain #3 Source Data Contribution Usefulness, this dashboard guides organizations on how they may improve the usefulness of platform identification data they provide. The dashboard displays and organizes analysis of source data contributions within CVE 5.X formatted records and identifies specific data quality concerns that may exascerbate platform automation challenges related to CPE Base String Determination and CPE Applicability Statement Generation.
Goals:
Dramatically improve the usefulness of platform identification data within the CVE List. This goal is limited based on the active involvement and response of external data contributors.
Dramatically reduce the amount of customized parsing and post-processing required by downstream consumers of CVE data for all use cases.
For technical issues, feature requests, or questions; please visit the Repository Issues page.
Community feedback and contributions to improve the dashboard's functionality and user experience are always encouraged!
🎯 How to Use
- Review Summary - Examine aggregate statistics across all sources
- Browse Sources - Scan the table for source-specific metrics
- Open Individual Report - Review detailed source data concern information about a specific source
📊 Understanding Metrics
- Total CVEs - Number of CVE records processed for this source
- Total Entries - Platform entries contributed by this source
- With Concerns - Entries that triggered one or more data quality concerns
- Without Concerns - Clean entries with no detected issues
- Concern % - Percentage of entries with concerns
Summary Statistics
Aggregate metrics across all sources
Source Reports
Per-source data quality analysis