---
license: cc0-1.0
tags:
- security
- cybersecurity
- cve
- cisa
- kev
- nvd
- parquet
- rag
- public-domain
pretty_name: CVE-KEV Snapshot (2025-10-29)
viewer: true
configs:
- config_name: preview
  data_files:
  - split: train
    path: parquet/preview.parquet
- config_name: cve
  data_files:
  - split: train
    path: parquet/cve.parquet
- config_name: nvd_meta
  data_files:
  - split: train
    path: parquet/nvd_meta.parquet
- config_name: kev
  data_files:
  - split: train
    path: parquet/kev.parquet
- config_name: edges
  data_files:
  - split: train
    path: parquet/edges.parquet
- config_name: rag_meta
  data_files:
  - split: train
    path: rag/meta.parquet
- config_name: rag_mapping
  data_files:
  - split: train
    path: rag/mapping.parquet
---

# CVE-KEV Snapshot (one-time, offline bundle)

This bundle lets you rank likely exploited CVEs and cite official sources without any APIs or accounts, fully offline. It’s a one-time snapshot of the last 90 days of NVD, aligned with CISA KEV for immediate focus on likely exploited CVEs. Query-ready Parquet tables and an optional small RAG pack let you rank by severity, pivot by CWE, and fetch references for briefings. Every row includes provenance; validation metrics and an integrity manifest are included. The compiled dataset is dedicated to the public domain (CC0).

## Quick start (60 seconds)

- Open `demo/OVX_quickstart.html` (no network) or `demo/OVX_quickstart.ipynb`.
- Or run this DuckDB query for top KEV CVEs by severity:

```sql
SELECT c.cve_id, m.cvss_v3_score, k.date_added
FROM read_parquet('parquet/kev.parquet') k
JOIN read_parquet('parquet/cve.parquet') c USING (cve_id)
LEFT JOIN read_parquet('parquet/nvd_meta.parquet') m USING (cve_id)
ORDER BY (m.cvss_v3_score IS NULL) ASC, m.cvss_v3_score DESC, k.date_added DESC
LIMIT 20;
```

Snapshot as of (UTC): 2025-10-29T13:51:37Z
NVD window (days): 90

## Accuracy at a glance

- Total CVE rows: 12307
- Total KEV rows: 28
- Artifacts: [Validation Report](docs/VALIDATION.json) · [Integrity Check](docs/INTEGRITY.txt) · [Build Manifest](docs/BUILD_MANIFEST.json)
  - KEV is window‑aligned; within‑window coverage = 1.0 by design. See `docs/VALIDATION.json` for `kev_rows_total_fetched`, `kev_rows_within_window`, `kev_rows_filtered_out`, and `kev_within_window_over_global_ratio`.

## What this is

A single, immutable dataset combining:
- CVE records (IDs, summaries) with CVSS and CWE from NVD (public domain)
- KEV flags from CISA (CC0)
- Provenance on every row and edge (source, source_url, retrieved_at, source_record_hash)
- A tiny RAG pack (embeddings + FAISS index) built only from PD/CC0 text

## Who this is for

- Security ML teams: feature prototyping (KEV=true, CVSS, CWE signals)
- RAG/QA prototypers: grounded retrieval with official citations
- Analysts: local, verifiable artifact (no APIs/accounts)

## What you can do quickly (offline)

- Rank KEV CVEs by severity; pivot by CWE categories
- Retrieve references for a CVE (official NVD/KEV links)
- Trial RAG with a tiny index (if the embedding model is cached locally)
- Inspect validation metrics and per-row provenance

## Files

- parquet/: cve.parquet, nvd_meta.parquet, kev.parquet, edges.parquet, preview.parquet (~1000 CVEs; see preview criteria)
- rag/: index.faiss, meta.parquet, mapping.parquet, vectors.npy (optional)
- docs/: LICENSES.md, LICENCE.md (CC0 legal code), NOTICE.md, INTEGRITY.txt, VALIDATION.json (if enabled), BUILD_MANIFEST.json
- demo/: OVX_quickstart.ipynb (offline quickstart)

## Validation and integrity

- VALIDATION.json includes: counts, cvss_v3_presence_ratio, cwe_presence_ratio, kev_cve_coverage_ratio, kev_cve_coverage_ratio_within_window, kev_rows_total_fetched, kev_rows_within_window, kev_within_window_over_global_ratio, rejected_cve_count, url_shape_failures, http_head_failures_hard, http_head_failures_flaky, dead_reference_links, duplicate_edges_dropped, snapshot_as_of
- URL checks (if present in this snapshot’s validation step) were executed conservatively with a single worker to reduce flakiness and rate limiting.
- INTEGRITY.txt: SHA-256 list of all files in this bundle. Verify locally:
  - macOS:
    ```bash
    shasum -a 256 -c docs/INTEGRITY.txt
    ```
  - Linux:
    ```bash
    sha256sum -c docs/INTEGRITY.txt
    ```

- Build metadata: see `docs/BUILD_MANIFEST.json` for snapshot parameters (timestamp, NVD window, tool/version info, internal commit/config). Provided for transparency; the build system is not included.

## RAG constraints

- Texts are PD/CC0-only (NVD short descriptions, KEV notes)
- meta.parquet: normalize=true, metric="IP", pinned model_name="BAAI/bge-small-en-v1.5" and dimension=384
- Retrieval requires the model to be present in local cache; no downloads
- If `rag/mapping.parquet` is present, it maps FAISS `row_index` → `cve_id` with columns: `row_index` (int32), `cve_id` (string)

## Preview parquet

- `parquet/preview.parquet` is a convenience subset for quick inspection.
- Selection: first 1000 rows by `cve_id` ordering from `parquet/cve.parquet`.
- Columns: `cve_id`, `summary`, `published_date`, `modified_date` (when available); otherwise falls back to a best-effort subset.

## Non-affiliation and license

- Not affiliated with NIST/NVD, CISA/KEV, or FIRST/EPSS
- NVD non-endorsement: "This product uses data from the NVD API but is not endorsed or certified by the NVD."
- Compiled artifact dedicated to the public domain under CC0 1.0 (see docs/LICENCE.md)
- Upstream sources: NVD (public domain), CISA KEV (CC0). Third‑party pages reached via reference URLs are governed by their own terms

## Start here

- Open [demo/OVX_quickstart.ipynb](demo/OVX_quickstart.ipynb) (no network calls)
- Or open [demo/OVX_quickstart.html](demo/OVX_quickstart.html) for a view-only quickstart
- Or query with DuckDB directly:

```
SELECT c.cve_id, m.cvss_v3_score, k.date_added
FROM read_parquet('parquet/kev.parquet') k
JOIN read_parquet('parquet/cve.parquet') c USING (cve_id)
LEFT JOIN read_parquet('parquet/nvd_meta.parquet') m USING (cve_id)
ORDER BY (m.cvss_v3_score IS NULL) ASC, m.cvss_v3_score DESC, k.date_added DESC
LIMIT 20;
```

### Top queries to try (DuckDB)

```sql
-- Top KEV CVEs by CVSS
SELECT c.cve_id, m.cvss_v3_score, k.date_added
FROM read_parquet('parquet/kev.parquet') k
JOIN read_parquet('parquet/cve.parquet') c USING (cve_id)
LEFT JOIN read_parquet('parquet/nvd_meta.parquet') m USING (cve_id)
ORDER BY (m.cvss_v3_score IS NULL) ASC, m.cvss_v3_score DESC, k.date_added DESC
LIMIT 20;

-- Count malformed or missing CVSS
SELECT SUM(cvss_v3_score IS NULL) AS missing_cvss_v3, COUNT(*) AS total
FROM read_parquet('parquet/nvd_meta.parquet');

-- Top CWE categories by count
WITH u AS (
  SELECT UNNEST(cwe_ids) AS cwe FROM read_parquet('parquet/nvd_meta.parquet')
)
SELECT cwe, COUNT(*) AS cnt
FROM u
GROUP BY cwe
ORDER BY cnt DESC
LIMIT 20;

-- References for a specific CVE
SELECT dst_id AS reference_url
FROM read_parquet('parquet/edges.parquet')
WHERE src_type='cve' AND src_id='CVE-2021-44228' AND edge_type='cve_ref_url'
ORDER BY reference_url;
```

## Validation notes

- Where URL reachability checks were included, they used a single worker by default and domain-specific pacing (e.g., stricter for `vuldb.com`). Counts of malformed URLs and network failures are summarized in `docs/VALIDATION.json`.

## Limitations

- Some CVEs may lack CVSS vectors/scores in the NVD window (nulls are expected).
- URL checks are conservative and may still include dead or redirected links; always verify with official sources.
- KEV rows are filtered to the NVD window by design; KEV counts reflect in-window coverage, not global totals.

## Scope and KEV alignment

- KEV is filtered to the same NVD window; only KEV CVEs that are also in the NVD window are included. Edges never reference out‑of‑window CVEs.
- Coverage metric naming: `kev_cve_coverage_ratio_within_window` reflects this alignment and is expected to be 1.0 by design. The legacy key `kev_cve_coverage_ratio` is retained and equals the within-window value.
- Global context ratio: `kev_within_window_over_global_ratio = kev_rows_within_window / kev_rows_total_fetched` (share of KEV entries that fall into this snapshot’s NVD window).


## Schemas (columns and types)

- parquet/cve.parquet
  - cve_id: string
  - summary: string
  - description_hash: string
  - published_date: timestamp[us, UTC]
  - modified_date: timestamp[us, UTC]
  - is_rejected: boolean
  - source: string
  - source_url: string
  - retrieved_at: timestamp[us, UTC]
  - source_record_hash: string

- parquet/nvd_meta.parquet
  - cve_id: string
  - cvss_v3_score: float64 (nullable)
  - cvss_v3_vector: string (nullable)
  - cvss_v2_score: float64 (nullable)
  - cwe_ids: list<string>
  - reference_urls: list<string>
  - ref_tags: list<string>
  - source: string
  - source_url: string
  - retrieved_at: timestamp[us, UTC]
  - source_record_hash: string

- parquet/kev.parquet
  - cve_id: string
  - date_added: date32[day]
  - notes: string (nullable)
  - source: string
  - source_url: string
  - retrieved_at: timestamp[us, UTC]
  - source_record_hash: string

- parquet/edges.parquet
  - src_type: string
  - src_id: string
  - edge_type: string
  - dst_type: string
  - dst_id: string
  - source: string
  - source_url: string
  - retrieved_at: timestamp[us, UTC]

- rag/meta.parquet
  - model_name: string
  - dim: int32
  - normalize: boolean
  - metric: string
  - texts_count: int64

## Storage and performance notes

- Parquet compression: `snappy` (writer default).
- Disk footprint: varies by window; see your build output directory sizes to estimate download needs.

### Uniqueness rules

- Primary keys:
  - `cve.parquet`: `cve_id`
  - `nvd_meta.parquet`: `cve_id`
  - `kev.parquet`: `cve_id`
- Edges composite uniqueness:
  - Unique on (`src_type`, `src_id`, `edge_type`, `dst_type`, `dst_id`, `source`)
  - Duplicates are dropped; see `duplicate_edges_dropped` in `docs/VALIDATION.json`.

## Citation

If you use this snapshot, please cite:

```
"CVE-KEV Snapshot (2025-10-29T13:51:37Z)", CC0-1.0, https://huggingface.co/datasets/NostromoHub/cve-kev-snapshot-90d-2025-10-29
```

## Usage

- DuckDB
```sql
SELECT c.cve_id, m.cvss_v3_score, k.date_added
FROM read_parquet('parquet/kev.parquet') k
JOIN read_parquet('parquet/cve.parquet') c USING (cve_id)
LEFT JOIN read_parquet('parquet/nvd_meta.parquet') m USING (cve_id)
ORDER BY (m.cvss_v3_score IS NULL) ASC, m.cvss_v3_score DESC, k.date_added DESC
LIMIT 20;
```

- Python (Pandas)
```python
import pandas as pd
k = pd.read_parquet('parquet/kev.parquet')
c = pd.read_parquet('parquet/cve.parquet')
m = pd.read_parquet('parquet/nvd_meta.parquet')
df = k.merge(c, on='cve_id').merge(m[['cve_id','cvss_v3_score']], on='cve_id', how='left')
print(df.head())
```

- Python (Polars)
```python
import polars as pl
k = pl.read_parquet('parquet/kev.parquet')
c = pl.read_parquet('parquet/cve.parquet')
m = pl.read_parquet('parquet/nvd_meta.parquet').select('cve_id','cvss_v3_score')
df = k.join(c, on='cve_id').join(m, on='cve_id', how='left')
print(df.head())
```