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# Analytics Query Library
This document provides ready-to-use SQL queries for common analytics use cases. All queries are optimized for the analytics star schema.
## Executive Dashboard Queries
### 1. Top Supplier Concentration (Supply Chain Risk)
Identifies suppliers with the highest component footprint, indicating supply chain concentration risk.
```sql
-- Via stored procedure (recommended, optional environment filter)
SELECT analytics.sp_top_suppliers(20, 'prod');
-- Direct query
SELECT
supplier,
component_count,
artifact_count,
team_count,
critical_vuln_count,
high_vuln_count,
environments
FROM analytics.mv_supplier_concentration
ORDER BY component_count DESC
LIMIT 20;
```
**Use case**: Identify vendors that, if compromised, would affect the most artifacts.
### 2. License Risk Heatmap
Shows distribution of components by license category for compliance review.
```sql
-- Via stored procedure (optional environment filter)
SELECT analytics.sp_license_heatmap('prod');
-- Direct query with grouping
SELECT
license_category,
SUM(component_count) AS total_components,
SUM(artifact_count) AS total_artifacts,
COUNT(DISTINCT license_concluded) AS unique_licenses
FROM analytics.mv_license_distribution
GROUP BY license_category
ORDER BY
CASE license_category
WHEN 'copyleft-strong' THEN 1
WHEN 'proprietary' THEN 2
WHEN 'unknown' THEN 3
WHEN 'copyleft-weak' THEN 4
ELSE 5
END;
```
**Use case**: Compliance review, identify components requiring legal review.
### 3. CVE Exposure Adjusted by VEX
Shows true vulnerability exposure after applying VEX mitigations.
```sql
-- Via stored procedure
SELECT analytics.sp_vuln_exposure('prod', 'high');
-- Direct query showing VEX effectiveness (global view; use sp_vuln_exposure for environment filtering)
SELECT
vuln_id,
severity::TEXT,
cvss_score,
epss_score,
kev_listed,
fix_available,
raw_artifact_count AS total_affected,
effective_artifact_count AS actually_affected,
raw_artifact_count - effective_artifact_count AS vex_mitigated,
ROUND(100.0 * (raw_artifact_count - effective_artifact_count) / NULLIF(raw_artifact_count, 0), 1) AS mitigation_rate
FROM analytics.mv_vuln_exposure
WHERE effective_artifact_count > 0
ORDER BY
CASE severity
WHEN 'critical' THEN 1
WHEN 'high' THEN 2
WHEN 'medium' THEN 3
ELSE 4
END,
effective_artifact_count DESC
LIMIT 50;
```
**Use case**: Show executives the "real" risk after VEX assessment.
### 4. Fixable Vulnerability Backlog
Lists vulnerabilities that can be fixed today (fix available, not VEX-mitigated).
```sql
-- Via stored procedure
SELECT analytics.sp_fixable_backlog('prod');
-- Direct query with priority scoring
SELECT
a.name AS service,
a.environment,
a.team,
c.name AS component,
c.version AS current_version,
cv.vuln_id,
cv.severity::TEXT,
cv.cvss_score,
cv.epss_score,
cv.fixed_version,
cv.kev_listed,
-- Priority score: higher = fix first
(
CASE cv.severity
WHEN 'critical' THEN 100
WHEN 'high' THEN 75
WHEN 'medium' THEN 50
ELSE 25
END
+ COALESCE(cv.epss_score * 100, 0)
+ (CASE WHEN cv.kev_listed THEN 50 ELSE 0 END)
)::INT AS priority_score
FROM analytics.component_vulns cv
JOIN analytics.components c ON c.component_id = cv.component_id
JOIN analytics.artifact_components ac ON ac.component_id = c.component_id
JOIN analytics.artifacts a ON a.artifact_id = ac.artifact_id
LEFT JOIN analytics.vex_overrides vo ON vo.artifact_id = a.artifact_id
AND vo.vuln_id = cv.vuln_id
AND vo.status = 'not_affected'
AND vo.valid_from <= now()
AND (vo.valid_until IS NULL OR vo.valid_until > now())
WHERE cv.affects = TRUE
AND cv.fix_available = TRUE
AND vo.override_id IS NULL
AND a.environment = 'prod'
ORDER BY priority_score DESC, a.name
LIMIT 100;
```
**Use case**: Prioritize remediation work based on risk and fixability.
### 5. Build Integrity / Attestation Coverage
Shows attestation gaps by environment and team.
```sql
-- Via stored procedure
SELECT analytics.sp_attestation_gaps('prod');
-- Direct query with gap analysis
SELECT
environment,
team,
total_artifacts,
with_provenance,
total_artifacts - with_provenance AS missing_provenance,
provenance_pct,
slsa_level_2_plus,
slsa2_pct,
with_sbom_attestation,
with_vex_attestation
FROM analytics.mv_attestation_coverage
WHERE environment = 'prod'
ORDER BY provenance_pct ASC;
```
**Use case**: Identify teams/environments not meeting attestation requirements.
## Trend Analysis Queries
### 6. Vulnerability Trend (30 Days)
```sql
SELECT
snapshot_date,
environment,
SUM(total_vulns) AS total_vulns,
SUM(fixable_vulns) AS fixable_vulns,
SUM(vex_mitigated) AS vex_mitigated,
SUM(total_vulns) - SUM(vex_mitigated) AS net_exposure,
SUM(kev_vulns) AS kev_vulns
FROM analytics.daily_vulnerability_counts
WHERE snapshot_date >= CURRENT_DATE - INTERVAL '30 days'
GROUP BY snapshot_date, environment
ORDER BY environment, snapshot_date;
```
### 7. Vulnerability Trend by Severity
```sql
SELECT
snapshot_date,
severity::TEXT,
SUM(total_vulns) AS total_vulns
FROM analytics.daily_vulnerability_counts
WHERE snapshot_date >= CURRENT_DATE - INTERVAL '30 days'
AND environment = 'prod'
GROUP BY snapshot_date, severity
ORDER BY snapshot_date,
CASE severity
WHEN 'critical' THEN 1
WHEN 'high' THEN 2
WHEN 'medium' THEN 3
ELSE 4
END;
```
### 8. Component Growth Trend
```sql
SELECT
snapshot_date,
environment,
SUM(total_components) AS total_components,
SUM(unique_suppliers) AS unique_suppliers
FROM analytics.daily_component_counts
WHERE snapshot_date >= CURRENT_DATE - INTERVAL '30 days'
GROUP BY snapshot_date, environment
ORDER BY environment, snapshot_date;
```
## Deep-Dive Queries
### 9. Component Impact Analysis
Find all artifacts affected by a specific component.
```sql
SELECT
a.name AS artifact,
a.version,
a.environment,
a.team,
ac.depth AS dependency_depth,
ac.introduced_via
FROM analytics.components c
JOIN analytics.artifact_components ac ON ac.component_id = c.component_id
JOIN analytics.artifacts a ON a.artifact_id = ac.artifact_id
WHERE c.purl LIKE 'pkg:maven/org.apache.logging.log4j/log4j-core%'
ORDER BY a.environment, a.name;
```
### 10. CVE Impact Analysis
Find all artifacts affected by a specific CVE.
```sql
SELECT DISTINCT
a.name AS artifact,
a.version,
a.environment,
a.team,
c.name AS component,
c.version AS component_version,
cv.cvss_score,
cv.fixed_version,
CASE
WHEN vo.status = 'not_affected' THEN 'VEX Mitigated'
WHEN cv.fix_available THEN 'Fix Available'
ELSE 'Vulnerable'
END AS status
FROM analytics.component_vulns cv
JOIN analytics.components c ON c.component_id = cv.component_id
JOIN analytics.artifact_components ac ON ac.component_id = c.component_id
JOIN analytics.artifacts a ON a.artifact_id = ac.artifact_id
LEFT JOIN analytics.vex_overrides vo ON vo.artifact_id = a.artifact_id
AND vo.vuln_id = cv.vuln_id
AND vo.valid_from <= now()
AND (vo.valid_until IS NULL OR vo.valid_until > now())
WHERE cv.vuln_id = 'CVE-2021-44228'
ORDER BY a.environment, a.name;
```
### 11. Supplier Vulnerability Profile
Detailed vulnerability breakdown for a specific supplier.
```sql
SELECT
c.supplier_normalized AS supplier,
c.name AS component,
c.version,
cv.vuln_id,
cv.severity::TEXT,
cv.cvss_score,
cv.kev_listed,
cv.fix_available,
cv.fixed_version
FROM analytics.components c
JOIN analytics.component_vulns cv ON cv.component_id = c.component_id
WHERE c.supplier_normalized = 'apache software foundation'
AND cv.affects = TRUE
ORDER BY
CASE cv.severity
WHEN 'critical' THEN 1
WHEN 'high' THEN 2
ELSE 3
END,
cv.cvss_score DESC;
```
### 12. License Compliance Report
Components with concerning licenses in production.
```sql
SELECT
c.name AS component,
c.version,
c.license_concluded,
c.license_category::TEXT,
c.supplier_normalized AS supplier,
COUNT(DISTINCT a.artifact_id) AS artifact_count,
ARRAY_AGG(DISTINCT a.name ORDER BY a.name) AS affected_artifacts
FROM analytics.components c
JOIN analytics.artifact_components ac ON ac.component_id = c.component_id
JOIN analytics.artifacts a ON a.artifact_id = ac.artifact_id
WHERE c.license_category IN ('copyleft-strong', 'proprietary', 'unknown')
AND a.environment = 'prod'
GROUP BY c.component_id, c.name, c.version, c.license_concluded, c.license_category, c.supplier_normalized
ORDER BY c.license_category, artifact_count DESC;
```
### 13. MTTR Analysis
Mean time to remediate by severity.
```sql
SELECT
cv.severity::TEXT,
COUNT(*) AS remediated_vulns,
AVG(EXTRACT(EPOCH FROM (vo.valid_from - cv.published_at)) / 86400)::NUMERIC(10,2) AS avg_days_to_mitigate,
PERCENTILE_CONT(0.5) WITHIN GROUP (
ORDER BY EXTRACT(EPOCH FROM (vo.valid_from - cv.published_at)) / 86400
)::NUMERIC(10,2) AS median_days,
PERCENTILE_CONT(0.9) WITHIN GROUP (
ORDER BY EXTRACT(EPOCH FROM (vo.valid_from - cv.published_at)) / 86400
)::NUMERIC(10,2) AS p90_days
FROM analytics.component_vulns cv
JOIN analytics.vex_overrides vo ON vo.vuln_id = cv.vuln_id
AND vo.status = 'not_affected'
AND vo.valid_from <= now()
AND (vo.valid_until IS NULL OR vo.valid_until > now())
WHERE cv.published_at >= now() - INTERVAL '90 days'
AND cv.published_at IS NOT NULL
GROUP BY cv.severity
ORDER BY
CASE cv.severity
WHEN 'critical' THEN 1
WHEN 'high' THEN 2
WHEN 'medium' THEN 3
ELSE 4
END;
```
### 14. Transitive Dependency Risk
Components introduced through transitive dependencies.
```sql
SELECT
c.name AS transitive_component,
c.version,
ac.introduced_via AS direct_dependency,
ac.depth,
COUNT(DISTINCT cv.vuln_id) AS vuln_count,
SUM(CASE WHEN cv.severity = 'critical' THEN 1 ELSE 0 END) AS critical_count,
COUNT(DISTINCT a.artifact_id) AS affected_artifacts
FROM analytics.components c
JOIN analytics.artifact_components ac ON ac.component_id = c.component_id
JOIN analytics.artifacts a ON a.artifact_id = ac.artifact_id
LEFT JOIN analytics.component_vulns cv ON cv.component_id = c.component_id AND cv.affects = TRUE
WHERE ac.depth > 0 -- Transitive only
AND a.environment = 'prod'
GROUP BY c.component_id, c.name, c.version, ac.introduced_via, ac.depth
HAVING COUNT(cv.vuln_id) > 0
ORDER BY critical_count DESC, vuln_count DESC
LIMIT 50;
```
### 15. VEX Effectiveness Report
How effective is the VEX program at reducing noise?
```sql
SELECT
DATE_TRUNC('week', vo.created_at)::DATE AS week,
COUNT(*) AS total_overrides,
COUNT(*) FILTER (WHERE vo.status = 'not_affected') AS not_affected,
COUNT(*) FILTER (WHERE vo.status = 'affected') AS confirmed_affected,
COUNT(*) FILTER (WHERE vo.status = 'under_investigation') AS under_investigation,
COUNT(*) FILTER (WHERE vo.status = 'fixed') AS marked_fixed,
-- Noise reduction rate
ROUND(100.0 * COUNT(*) FILTER (WHERE vo.status = 'not_affected') / NULLIF(COUNT(*), 0), 1) AS noise_reduction_pct
FROM analytics.vex_overrides vo
WHERE vo.created_at >= now() - INTERVAL '90 days'
GROUP BY DATE_TRUNC('week', vo.created_at)
ORDER BY week;
```
## Performance Tips
1. **Use materialized views**: Queries prefixed with `mv_` are pre-computed and fast
2. **Add environment filter**: Most queries benefit from `WHERE environment = 'prod'`
3. **Use stored procedures**: `sp_*` functions return JSON and handle caching
4. **Limit results**: Always use `LIMIT` for large result sets
5. **Check refresh times**: Views are refreshed daily; data may be up to 24h stale
## Query Parameters
Common filter parameters:
| Parameter | Type | Example | Notes |
|-----------|------|---------|-------|
| `environment` | TEXT | `'prod'`, `'stage'` | Filter by deployment environment |
| `team` | TEXT | `'platform'` | Filter by owning team |
| `severity` | TEXT | `'critical'`, `'high'` | Minimum severity level |
| `days` | INT | `30`, `90` | Lookback period |
| `limit` | INT | `20`, `100` | Max results |