BOF: Vulnerability Data Consumers
summary
People describe concrete pain: brittle JSON/XML parsing, lots of one-off checks, and mass flattening of nested arrays; common tooling is bash + jq and Splunk for normalization. Data quality issues include missing/NA fields, shifting CPE semantics and schema changes (NVD CPE 5.1.1), and no easy bulk dump or delta feed — 70 open quality issues exist. Operational needs called out are need a change feed, flat-file export, and using canonical IDs so EPSS tracks CVE IDs for exploit correlation.
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chapters (13)
- 0:00Vulnerability data challenges
- 1:27Pain points in CVE/NVD data
- 3:58Data parsing and quality issues
- 6:57Data accuracy and normalization
- 9:08Handling severity shifts
- 10:59CVE configuration challenges
- 12:47Improving data quality
- 14:31Change tracking and backfills
- 16:43Vulnerabilities to threat intel
- 18:28CVE IDs for threat tracking
- 19:32Event streams for vulnerability data
- 21:19CVE as a product
- 23:30Sustaining the conversation
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