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.gitattributes

@@ -57,3 +57,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
+rag/index.faiss filter=lfs diff=lfs merge=lfs -text

90-days.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cc5f0733ff67e793c19d5e645ce4693b5b9e2c2c1dc2213607875829931b06e1
+size 39290478

README.md

@@ -1,56 +1,27 @@
 ---
 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
+  - security
+  - cybersecurity
+  - cve
+  - cisa
+  - kev
+  - nvd
+  - parquet
+  - rag
+  - public-domain
+pretty_name: CVE-KEV Snapshot (2025-10-29T13:51:37Z)
 ---
 
-## CVE-KEV Snapshot (one-time, offline bundle)
+# 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](demo/OVX_quickstart.ipynb).
+- 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
@@ -60,54 +31,219 @@ ORDER BY (m.cvss_v3_score IS NULL) ASC, m.cvss_v3_score DESC, k.date_added DESC
 LIMIT 20;
 ```
 
-## Snapshot
-
-- Snapshot as of (UTC): 2025-09-05T02:12:27Z
-- NVD window (days): 90
+Snapshot as of (UTC): 2025-10-29T13:51:37Z
+NVD window (days): 90
 
 ## Accuracy at a glance
 
-- Total CVE rows: 11,344
-- Total KEV rows: 27
-- Artifacts: [Validation Report](docs/VALIDATION.json) · [Integrity Check](docs/INTEGRITY.txt) · [Build Manifest](docs/BUILD_MANIFEST.json)  
+- 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`.
 
-## Contents
+## 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/` (optional): `index.faiss`, `meta.parquet`, `mapping.parquet`, `vectors.npy`
-- `docs/`: `LICENSES.md`, `LICENCE.md` (CC0 legal code), `NOTICE.md`, `INTEGRITY.txt`, `VALIDATION.json`, `BUILD_MANIFEST.json`
-- `demo/`: `OVX_quickstart.ipynb`, `OVX_quickstart.html`
+- 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)
 
-## RAG note
+## Validation and integrity
 
-Optional RAG pack built from PD/CC0 text using `BAAI/bge-small-en-v1.5` (384‑dim), normalized vectors with inner product (cosine) similarity. Retrieval is offline-only; query embedding requires the model to be already cached locally.
+- 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](parquet/preview.parquet) is a convenience subset for quick inspection.
+- `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); falls back to a best‑effort subset if needed.
+- 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:
 
-## Validation, integrity, build metadata
+```
+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;
+```
 
-- `docs/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) were executed conservatively with a single worker.
-- Verify integrity locally:
-  - macOS: `shasum -a 256 -c docs/INTEGRITY.txt`
-  - Linux: `sha256sum -c docs/INTEGRITY.txt`
-- Build metadata (transparency): 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.
+### Top queries to try (DuckDB)
 
-## Storage and performance
+```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;
 
-- Parquet compression: `snappy`.
-- Disk footprint varies by window size; see file sizes before downloading.
+-- 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 within the window (nulls are expected).
-- URL checks are conservative and may still include dead/redirected links; verify with official sources.
-- KEV rows are filtered to the NVD window; counts reflect in‑window coverage, not global totals.
+- 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
 
@@ -141,16 +277,4 @@ df = k.join(c, on='cve_id').join(m, on='cve_id', how='left')
 print(df.head())
 ```
 
-## Non-affiliation and licensing
-
-- 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). Linked third‑party pages (vendor advisories, blogs, etc.) are governed by their own terms.
 
-## Citation
-
-If you use this snapshot, please cite:
-```
-"CVE-KEV Snapshot (${snapshot_as_of})", CC0-1.0, https://huggingface.co/datasets/NostromoHub/cve-kev-snapshot-90d-2025-10-29
-```

demo/OVX_quickstart.html

@@ -0,0 +1,425 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+  <meta charset="UTF-8" />
+  <meta name="viewport" content="width=device-width, initial-scale=1.0" />
+  <title>CVE-KEV Snapshot — Offline Quickstart (HTML)</title>
+  <style>
+    body { font-family: -apple-system, BlinkMacSystemFont, Segoe UI, Roboto, Helvetica, Arial, sans-serif; margin: 24px; line-height: 1.45; }
+    h1, h2, h3 { margin-top: 1.2em; }
+    code, pre { background: #f6f8fa; padding: 2px 4px; border-radius: 4px; }
+    table { border-collapse: collapse; width: 100%; margin: 12px 0; }
+    th, td { text-align: left; border: 1px solid #e1e4e8; padding: 6px 8px; }
+    th { background: #fafbfc; }
+    .meta { color: #555; }
+    .links a { margin-right: 12px; }
+    .empty { color: #777; font-style: italic; }
+  </style>
+  <!-- This file is static. Values are substituted at build time. -->
+</head>
+<body>
+  <h1>CVE-KEV Snapshot — Offline Quickstart</h1>
+  <p class="meta">Snapshot as of (UTC): <strong>2025-10-29T13:51:37Z</strong></p>
+  <p class="meta">Total CVE rows: <strong>12307</strong> · Total KEV rows: <strong>28</strong></p>
+  <p class="links">
+    <a href="../docs/VALIDATION.json">Validation Report</a>
+    <a href="../docs/INTEGRITY.txt">Integrity Check</a>
+    <a href="../docs/BUILD_MANIFEST.json">Build Manifest</a>
+  </p>
+
+  <h2>Accuracy at a glance</h2>
+  <div><table><tbody><tr><th>cvss_v3_presence_ratio</th><td>0.760137</td></tr><tr><th>cwe_presence_ratio</th><td>0.827659</td></tr><tr><th>kev_cve_coverage_ratio_within_window</th><td>1.0</td></tr><tr><th>kev_rows_total_fetched</th><td>1451</td></tr><tr><th>kev_rows_within_window</th><td>28</td></tr><tr><th>kev_rows_filtered_out</th><td>1423</td></tr><tr><th>kev_within_window_over_global_ratio</th><td>0.019297</td></tr><tr><th>rejected_cve_count</th><td>103</td></tr><tr><th>url_shape_failures</th><td>0</td></tr><tr><th>http_head_failures_hard</th><td>744</td></tr><tr><th>http_head_failures_flaky</th><td>5487</td></tr><tr><th>dead_reference_links</th><td>6231</td></tr><tr><th>duplicate_edges_dropped</th><td>2027</td></tr></tbody></table></div>
+  <p class="meta">Notes: <code>http_head_failures_hard</code> are definitive HTTP errors (4xx/5xx); <code>http_head_failures_flaky</code> are timeouts or rate limiting. <code>dead_reference_links</code> equals the sum of these categories in this snapshot.</p>
+
+  <h2>Data previews</h2>
+  <h3>Top KEV CVEs by CVSS (max 20)</h3>
+  <div><table border="1" class="dataframe">
+  <thead>
+    <tr style="text-align: right;">
+      <th>cve_id</th>
+      <th>cvss_v3_score</th>
+      <th>date_added</th>
+      <th>notes</th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr>
+      <td>CVE-2025-54253</td>
+      <td>10.0</td>
+      <td>2025-10-15</td>
+      <td>https://helpx.adobe.com/security/products/aem-forms/apsb25-82.html ; https://nvd.nist.gov/vuln/detail/CVE-2025-54253</td>
+    </tr>
+    <tr>
+      <td>CVE-2025-10035</td>
+      <td>10.0</td>
+      <td>2025-09-29</td>
+      <td>https://www.fortra.com/security/advisories/product-security/fi-2025-012 ; https://nvd.nist.gov/vuln/detail/CVE-2025-10035</td>
+    </tr>
+    <tr>
+      <td>CVE-2025-20333</td>
+      <td>9.9</td>
+      <td>2025-09-25</td>
+      <td>CISA Mitigation Instructions: https://www.cisa.gov/news-events/directives/ed-25-03-identify-and-mitigate-potential-compromise-cisco-devices ; https://www.cisa.gov/news-events/directives/supplemental-direction-ed-25-03-core-dump-and-hunt-instructions ; https://www.cisa.gov/eviction-strategies-tool/create-from-template ; https://sec.cloudapps.cisco.com/security/center/resources/asa_ftd_continued_attacks ;    https://sec.cloudapps.cisco.com/security/center/private/resources/asa_ftd_continued_attacks#Details ; https://sec.cloudapps.cisco.com/security/center/content/CiscoSecurityAdvisory/cisco-sa-asaftd-webvpn-z5xP8EUB ; https://nvd.nist.gov/vuln/detail/CVE-2025-20333</td>
+    </tr>
+    <tr>
+      <td>CVE-2025-59287</td>
+      <td>9.8</td>
+      <td>2025-10-24</td>
+      <td>https://msrc.microsoft.com/update-guide/en-US/vulnerability/CVE-2025-59287 ; https://nvd.nist.gov/vuln/detail/CVE-2025-59287</td>
+    </tr>
+    <tr>
+      <td>CVE-2025-61932</td>
+      <td>9.8</td>
+      <td>2025-10-22</td>
+      <td>https://www.motex.co.jp/news/notice/2025/release251020/ ; https://nvd.nist.gov/vuln/detail/CVE-2025-61932</td>
+    </tr>
+    <tr>
+      <td>CVE-2025-61882</td>
+      <td>9.8</td>
+      <td>2025-10-06</td>
+      <td>https://www.oracle.com/security-alerts/alert-cve-2025-61882.html ; https://nvd.nist.gov/vuln/detail/CVE-2025-61882</td>
+    </tr>
+    <tr>
+      <td>CVE-2025-10585</td>
+      <td>9.8</td>
+      <td>2025-09-23</td>
+      <td>https://chromereleases.googleblog.com/2025/09/stable-channel-update-for-desktop_17.html ; https://nvd.nist.gov/vuln/detail/CVE-2025-10585</td>
+    </tr>
+    <tr>
+      <td>CVE-2025-57819</td>
+      <td>9.8</td>
+      <td>2025-08-29</td>
+      <td>https://github.com/FreePBX/security-reporting/security/advisories/GHSA-m42g-xg4c-5f3h ; https://nvd.nist.gov/vuln/detail/CVE-2025-57819</td>
+    </tr>
+    <tr>
+      <td>CVE-2025-7775</td>
+      <td>9.8</td>
+      <td>2025-08-26</td>
+      <td>https://support.citrix.com/support-home/kbsearch/article?articleNumber=CTX694938 ; https://nvd.nist.gov/vuln/detail/CVE-2025-7775</td>
+    </tr>
+    <tr>
+      <td>CVE-2025-54948</td>
+      <td>9.4</td>
+      <td>2025-08-18</td>
+      <td>https://success.trendmicro.com/en-US/solution/KA-0020652 ; N/A ; https://nvd.nist.gov/vuln/detail/CVE-2025-54948</td>
+    </tr>
+    <tr>
+      <td>CVE-2025-6205</td>
+      <td>9.1</td>
+      <td>2025-10-28</td>
+      <td>https://www.3ds.com/trust-center/security/security-advisories/cve-2025-6205 ; https://nvd.nist.gov/vuln/detail/CVE-2025-6205</td>
+    </tr>
+    <tr>
+      <td>CVE-2025-54236</td>
+      <td>9.1</td>
+      <td>2025-10-24</td>
+      <td>https://experienceleague.adobe.com/en/docs/experience-cloud-kcs/kbarticles/ka-27397 ; https://nvd.nist.gov/vuln/detail/CVE-2025-54236</td>
+    </tr>
+    <tr>
+      <td>CVE-2025-53690</td>
+      <td>9.0</td>
+      <td>2025-09-04</td>
+      <td>https://support.sitecore.com/kb?id=kb_article_view&amp;sysparm_article=KB1003865 ; https://nvd.nist.gov/vuln/detail/CVE-2025-53690</td>
+    </tr>
+    <tr>
+      <td>CVE-2025-21043</td>
+      <td>8.8</td>
+      <td>2025-10-02</td>
+      <td>https://security.samsungmobile.com/securityUpdate.smsb?year=2025&amp;month=09 ; https://nvd.nist.gov/vuln/detail/CVE-2025-21043</td>
+    </tr>
+    <tr>
+      <td>CVE-2025-48543</td>
+      <td>8.8</td>
+      <td>2025-09-04</td>
+      <td>https://source.android.com/docs/security/bulletin/2025-09-01 ; https://nvd.nist.gov/vuln/detail/CVE-2025-48543</td>
+    </tr>
+    <tr>
+      <td>CVE-2025-43300</td>
+      <td>8.8</td>
+      <td>2025-08-21</td>
+      <td>https://support.apple.com/en-us/124925 ; https://support.apple.com/en-us/124926 ; https://support.apple.com/en-us/124927 ; https://support.apple.com/en-us/124928 ; https://support.apple.com/en-us/124929 ; https://nvd.nist.gov/vuln/detail/CVE-2025-43300</td>
+    </tr>
+    <tr>
+      <td>CVE-2025-8876</td>
+      <td>8.8</td>
+      <td>2025-08-13</td>
+      <td>https://status.n-able.com/2025/08/13/announcing-the-ga-of-n-central-2025-3-1/ ; https://nvd.nist.gov/vuln/detail/CVE-2025-8876</td>
+    </tr>
+    <tr>
+      <td>CVE-2025-8088</td>
+      <td>8.8</td>
+      <td>2025-08-12</td>
+      <td>https://www.win-rar.com/singlenewsview.html?&amp;L=0&amp;tx_ttnews%5Btt_news%5D=283&amp;cHash=a64b4a8f662d3639dec8d65f47bc93c5 ; https://nvd.nist.gov/vuln/detail/CVE-2025-8088</td>
+    </tr>
+    <tr>
+      <td>CVE-2025-6204</td>
+      <td>8.0</td>
+      <td>2025-10-28</td>
+      <td>https://www.3ds.com/trust-center/security/security-advisories/cve-2025-6204 ; https://nvd.nist.gov/vuln/detail/CVE-2025-6204</td>
+    </tr>
+    <tr>
+      <td>CVE-2025-59230</td>
+      <td>7.8</td>
+      <td>2025-10-14</td>
+      <td>https://msrc.microsoft.com/update-guide/en-US/vulnerability/CVE-2025-59230 ; https://nvd.nist.gov/vuln/detail/CVE-2025-59230</td>
+    </tr>
+  </tbody>
+</table></div>
+
+  <h3>CWE pivot (max 20)</h3>
+  <div><table border="1" class="dataframe">
+  <thead>
+    <tr style="text-align: right;">
+      <th>cwe</th>
+      <th>cnt</th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr>
+      <td>CWE-79</td>
+      <td>1941</td>
+    </tr>
+    <tr>
+      <td>CWE-89</td>
+      <td>1179</td>
+    </tr>
+    <tr>
+      <td>CWE-74</td>
+      <td>686</td>
+    </tr>
+    <tr>
+      <td>CWE-862</td>
+      <td>462</td>
+    </tr>
+    <tr>
+      <td>CWE-94</td>
+      <td>411</td>
+    </tr>
+    <tr>
+      <td>CWE-284</td>
+      <td>348</td>
+    </tr>
+    <tr>
+      <td>CWE-352</td>
+      <td>332</td>
+    </tr>
+    <tr>
+      <td>CWE-78</td>
+      <td>321</td>
+    </tr>
+    <tr>
+      <td>CWE-121</td>
+      <td>296</td>
+    </tr>
+    <tr>
+      <td>CWE-434</td>
+      <td>276</td>
+    </tr>
+    <tr>
+      <td>CWE-22</td>
+      <td>264</td>
+    </tr>
+    <tr>
+      <td>CWE-119</td>
+      <td>242</td>
+    </tr>
+    <tr>
+      <td>CWE-77</td>
+      <td>239</td>
+    </tr>
+    <tr>
+      <td>CWE-200</td>
+      <td>229</td>
+    </tr>
+    <tr>
+      <td>CWE-416</td>
+      <td>218</td>
+    </tr>
+    <tr>
+      <td>CWE-125</td>
+      <td>205</td>
+    </tr>
+    <tr>
+      <td>CWE-787</td>
+      <td>192</td>
+    </tr>
+    <tr>
+      <td>CWE-20</td>
+      <td>171</td>
+    </tr>
+    <tr>
+      <td>CWE-502</td>
+      <td>169</td>
+    </tr>
+    <tr>
+      <td>CWE-918</td>
+      <td>167</td>
+    </tr>
+  </tbody>
+</table></div>
+
+  <h3>Citations for a CVE (sample)</h3>
+  <div><table border="1" class="dataframe">
+  <thead>
+    <tr style="text-align: right;">
+      <th>cve_id</th>
+      <th>reference_url</th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr>
+      <td>CVE-2025-54589</td>
+      <td>https://github.com/9001/copyparty/commit/a8705e611d05eeb22be5d3d7d9ab5c020fe54c62</td>
+    </tr>
+    <tr>
+      <td>CVE-2025-54589</td>
+      <td>https://github.com/9001/copyparty/releases/tag/v1.18.7</td>
+    </tr>
+    <tr>
+      <td>CVE-2025-54589</td>
+      <td>https://github.com/9001/copyparty/security/advisories/GHSA-8mx2-rjh8-q3jq</td>
+    </tr>
+    <tr>
+      <td>CVE-2025-7738</td>
+      <td>https://access.redhat.com/errata/RHSA-2025:12772</td>
+    </tr>
+    <tr>
+      <td>CVE-2025-7738</td>
+      <td>https://access.redhat.com/security/cve/CVE-2025-7738</td>
+    </tr>
+    <tr>
+      <td>CVE-2025-7738</td>
+      <td>https://bugzilla.redhat.com/show_bug.cgi?id=2381589</td>
+    </tr>
+    <tr>
+      <td>CVE-2025-8407</td>
+      <td>https://code-projects.org/</td>
+    </tr>
+    <tr>
+      <td>CVE-2025-8407</td>
+      <td>https://github.com/wllovemy/cve/issues/3</td>
+    </tr>
+    <tr>
+      <td>CVE-2025-8407</td>
+      <td>https://vuldb.com/?ctiid.318395</td>
+    </tr>
+    <tr>
+      <td>CVE-2025-8407</td>
+      <td>https://vuldb.com/?id.318395</td>
+    </tr>
+    <tr>
+      <td>CVE-2025-8407</td>
+      <td>https://vuldb.com/?submit.624009</td>
+    </tr>
+    <tr>
+      <td>CVE-2011-10008</td>
+      <td>https://raw.githubusercontent.com/rapid7/metasploit-framework/master/modules/exploits/windows/fileformat/mplayer_m3u_bof.rb</td>
+    </tr>
+    <tr>
+      <td>CVE-2011-10008</td>
+      <td>https://www.exploit-db.com/exploits/17013</td>
+    </tr>
+    <tr>
+      <td>CVE-2011-10008</td>
+      <td>https://www.vulncheck.com/advisories/mplayer-lite-r33064-m3u-stack-based-buffer-overflow</td>
+    </tr>
+    <tr>
+      <td>CVE-2012-10021</td>
+      <td>https://forums.dlink.com/index.php?topic=51923.0</td>
+    </tr>
+    <tr>
+      <td>CVE-2012-10021</td>
+      <td>https://raw.githubusercontent.com/rapid7/metasploit-framework/master/modules/exploits/linux/http/dlink_dir605l_captcha_bof.rb</td>
+    </tr>
+    <tr>
+      <td>CVE-2012-10021</td>
+      <td>https://web.archive.org/web/20121012062554/http://www.devttys0.com/2012/10/exploiting-a-mips-stack-overflow/</td>
+    </tr>
+    <tr>
+      <td>CVE-2012-10021</td>
+      <td>https://www.exploit-db.com/exploits/29127</td>
+    </tr>
+    <tr>
+      <td>CVE-2012-10021</td>
+      <td>https://www.vulncheck.com/advisories/dlink-dir605l-captcha-handling-stack-based-buffer-overflow</td>
+    </tr>
+    <tr>
+      <td>CVE-2013-10033</td>
+      <td>https://raw.githubusercontent.com/rapid7/metasploit-framework/master/modules/exploits/unix/webapp/kimai_sqli.rb</td>
+    </tr>
+  </tbody>
+</table></div>
+
+  <h3>Provenance sample</h3>
+  <div><table border="1" class="dataframe">
+  <thead>
+    <tr style="text-align: right;">
+      <th>cve_id</th>
+      <th>source</th>
+      <th>source_url</th>
+      <th>retrieved_at</th>
+      <th>source_record_hash</th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr>
+      <td>CVE-2005-10004</td>
+      <td>nvd</td>
+      <td>https://services.nvd.nist.gov/rest/json/cves/2.0?pubStartDate=2025-07-31T13:51:37.000Z&amp;pubEndDate=2025-10-29T13:51:37.000Z&amp;resultsPerPage=2000&amp;startIndex=2000</td>
+      <td>2025-10-29 06:52:01.759408-07:00</td>
+      <td>2a55c362bb75b1cf2ccee02b7ac3b31a11e1e546ad68e5fc28f0cd656375de41</td>
+    </tr>
+    <tr>
+      <td>CVE-2008-20001</td>
+      <td>nvd</td>
+      <td>https://services.nvd.nist.gov/rest/json/cves/2.0?pubStartDate=2025-07-31T13:51:37.000Z&amp;pubEndDate=2025-10-29T13:51:37.000Z&amp;resultsPerPage=2000&amp;startIndex=2000</td>
+      <td>2025-10-29 06:52:01.759408-07:00</td>
+      <td>d95f6a12b98c9caebea1c431ba26e4a8b8b77711cd94eccd7abc43a9ec39aa94</td>
+    </tr>
+    <tr>
+      <td>CVE-2009-10005</td>
+      <td>nvd</td>
+      <td>https://services.nvd.nist.gov/rest/json/cves/2.0?pubStartDate=2025-07-31T13:51:37.000Z&amp;pubEndDate=2025-10-29T13:51:37.000Z&amp;resultsPerPage=2000&amp;startIndex=2000</td>
+      <td>2025-10-29 06:52:01.759408-07:00</td>
+      <td>a40b9fda78392a9207ebb108cfcc38f34ecca7f4028b4d98f96abbba244b48f4</td>
+    </tr>
+    <tr>
+      <td>CVE-2009-10006</td>
+      <td>nvd</td>
+      <td>https://services.nvd.nist.gov/rest/json/cves/2.0?pubStartDate=2025-07-31T13:51:37.000Z&amp;pubEndDate=2025-10-29T13:51:37.000Z&amp;resultsPerPage=2000&amp;startIndex=2000</td>
+      <td>2025-10-29 06:52:01.759408-07:00</td>
+      <td>a06f93253a5961c5dcdfafc518d6f70b1b57faef5f20cdd9e0368f927f6e5c23</td>
+    </tr>
+    <tr>
+      <td>CVE-2009-20002</td>
+      <td>nvd</td>
+      <td>https://services.nvd.nist.gov/rest/json/cves/2.0?pubStartDate=2025-07-31T13:51:37.000Z&amp;pubEndDate=2025-10-29T13:51:37.000Z&amp;resultsPerPage=2000&amp;startIndex=2000</td>
+      <td>2025-10-29 06:52:01.759408-07:00</td>
+      <td>a0293a64b504ab0094417c0feeb192786b5d5c857b944f287f28fa6ab8e28453</td>
+    </tr>
+  </tbody>
+</table></div>
+
+  <h2>RAG configuration</h2>
+  <p>model_name=BAAI/bge-small-en-v1.5, dim=384, normalize=True, metric=IP, texts_count=12335</p>
+  <p class="meta">Retrieval requires the model to be present in the local cache; no downloads are attempted.</p>
+
+  <h2>Limits & assumptions</h2>
+  <ul>
+    <li>Point-in-time snapshot; no update cadence.</li>
+    <li>Upstream truth: reflects NVD (PD) and CISA KEV (CC0).</li>
+    <li>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.</li>
+    <li>URL checks are bounded; timeouts possible.</li>
+    <li>Texts for RAG are PD/CC0-only.</li>
+  </ul>
+
+  <h2>Links</h2>
+  <ul>
+    <li><a href="OVX_quickstart.ipynb">OVX_quickstart.ipynb</a></li>
+    <li><a href="../parquet/">parquet/</a></li>
+    <li><a href="../docs/">docs/</a></li>
+  </ul>
+</body>
+</html>
+
+

demo/OVX_quickstart.ipynb

@@ -0,0 +1,485 @@
+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "# CVE-KEV Snapshot — Offline Quickstart\n",
+        "\n",
+        "Audience: security ML/RAG practitioners and analysts. Runs fully offline; no network calls.\n",
+        "\n",
+        "- What this does:\n",
+        "  - Loads Parquet tables and shows quick triage and retrieval examples\n",
+        "  - Surfaces integrity and validation signals (accuracy)\n",
+        "  - Skips RAG if the embedding model isn't cached locally\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "HF_DATASET_URL = 'https://huggingface.co/datasets/NostromoHub/cve-kev-snapshot-90d-2025-09-04/resolve/main'  # used only in hosted runtimes for optional installs\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Running in Colab or Kaggle?\n",
+        "\n",
+        "- This offline notebook does not install dependencies by default.\n",
+        "- If you're in an online runtime (Colab/Kaggle), you can opt-in to install deps below.\n",
+        "- Local/offline users should pre-install packages (see demo/requirements-colab.txt).\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Optional: install dependencies when running in Colab/Kaggle (online only)\n",
+        "# By default, offline users should pre-install packages and skip this cell.\n",
+        "try:\n",
+        "    import os\n",
+        "    IN_COLAB = 'COLAB_GPU' in os.environ or 'COLAB_RELEASE_TAG' in os.environ\n",
+        "    IN_KAGGLE = 'KAGGLE_URL_BASE' in os.environ\n",
+        "    if IN_COLAB or IN_KAGGLE:\n",
+        "        if not HF_DATASET_URL:\n",
+        "            raise RuntimeError('HF_DATASET_URL is empty; set it at the top of the notebook to enable online install.')\n",
+        "        url = HF_DATASET_URL.rstrip('/') + '/demo/requirements-colab.txt'\n",
+        "        print('Detected hosted runtime. Installing from:', url)\n",
+        "        import subprocess, sys\n",
+        "        subprocess.check_call([sys.executable, '-m', 'pip', 'install', '-r', url])\n",
+        "    else:\n",
+        "        print('Hosted runtime not detected; skipping online install.')\n",
+        "except Exception as e:\n",
+        "    print('Dependency install skipped or failed:', e)\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Optional: dependency check (offline-safe). Set ENABLE_AUTO_INSTALL=True to pip install.\n",
+        "import importlib, sys, subprocess\n",
+        "\n",
+        "ENABLE_AUTO_INSTALL = False  # change to True to auto-install missing deps\n",
+        "REQUIRED_PACKAGES = [\"duckdb\", \"pandas\", \"pyarrow\"]\n",
+        "missing = []\n",
+        "for pkg in REQUIRED_PACKAGES:\n",
+        "    try:\n",
+        "        importlib.import_module(pkg)\n",
+        "    except Exception:\n",
+        "        missing.append(pkg)\n",
+        "\n",
+        "if missing:\n",
+        "    print(\"Missing packages:\", missing)\n",
+        "    if ENABLE_AUTO_INSTALL:\n",
+        "        try:\n",
+        "            subprocess.check_call([sys.executable, \"-m\", \"pip\", \"install\", *missing])\n",
+        "            # Re-validate imports\n",
+        "            for pkg in list(missing):\n",
+        "                importlib.import_module(pkg)\n",
+        "            print(\"Installed successfully.\")\n",
+        "        except Exception as install_err:\n",
+        "            print(\"Auto-install failed:\", install_err)\n",
+        "            print(\"Run manually:\", \"pip install \" + \" \".join(missing))\n",
+        "    else:\n",
+        "        print(\"Set ENABLE_AUTO_INSTALL=True above or run:\")\n",
+        "        print(\"pip install \" + \" \".join(missing))\n",
+        "else:\n",
+        "    print(\"All required packages are present.\")\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Artifacts (click to view): [Validation Report](../docs/VALIDATION.json) · [Integrity Check](../docs/INTEGRITY.txt) · [Build Manifest](../docs/BUILD_MANIFEST.json)\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "from pathlib import Path\n",
+        "import json\n",
+        "\n",
+        "BASE = Path('..').resolve()\n",
+        "PARQ = BASE / 'parquet'\n",
+        "DOCS = BASE / 'docs'\n",
+        "RAG = BASE / 'rag'\n",
+        "\n",
+        "assert PARQ.exists() and DOCS.exists(), 'Missing required directories. Ensure you are running the notebook from the snapshot \"demo\" directory.'\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Snapshot metadata\n",
+        "manifest = json.loads((DOCS / 'BUILD_MANIFEST.json').read_text())\n",
+        "print('snapshot_as_of:', manifest.get('snapshot_as_of'))\n",
+        "# Prefer manifest-provided window; fallback to parsing README if absent\n",
+        "window_days = manifest.get('nvd_window_days')\n",
+        "if window_days is None:\n",
+        "    try:\n",
+        "        txt = (BASE / 'README.md').read_text(encoding='utf-8')\n",
+        "        marker = 'NVD window (days): '\n",
+        "        i = txt.find(marker)\n",
+        "        if i != -1:\n",
+        "            j = i + len(marker)\n",
+        "            k = j\n",
+        "            while k < len(txt) and txt[k].isdigit():\n",
+        "                k += 1\n",
+        "            window_days = int(txt[j:k]) if k > j else None\n",
+        "    except Exception:\n",
+        "        window_days = None\n",
+        "print('nvd_window_days:', window_days)\n",
+        "print('model:', manifest.get('model_name'), 'dim:', manifest.get('model_dim'))\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Integrity spot-check (first 5 entries)\n",
+        "import hashlib\n",
+        "\n",
+        "def sha256(path: Path) -> str:\n",
+        "    h = hashlib.sha256()\n",
+        "    with path.open('rb') as f:\n",
+        "        for chunk in iter(lambda: f.read(1024*1024), b''):\n",
+        "            h.update(chunk)\n",
+        "    return h.hexdigest()\n",
+        "\n",
+        "lines = (DOCS / 'INTEGRITY.txt').read_text().splitlines()\n",
+        "# Parse lines robustly on whitespace: '<digest>  <relative_path>'\n",
+        "pairs = []\n",
+        "for ln in lines:\n",
+        "    if not ln.strip():\n",
+        "        continue\n",
+        "    parts = ln.split()\n",
+        "    digest_expected, rel = parts[0], ' '.join(parts[1:])\n",
+        "    pairs.append((rel, digest_expected))\n",
+        "\n",
+        "subset = [rel for rel, _ in pairs[:5]]\n",
+        "issues = []\n",
+        "for rel in subset:\n",
+        "    digest_expected = next(d for r, d in pairs if r == rel)\n",
+        "    actual = sha256(BASE / rel)\n",
+        "    if actual != digest_expected:\n",
+        "        issues.append(rel)\n",
+        "print('integrity_spotcheck_mismatches:', issues)\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Load with DuckDB; fallback to pandas if needed\n",
+        "try:\n",
+        "    import duckdb as dd\n",
+        "    con = dd.connect()\n",
+        "    con.execute('PRAGMA threads=4')\n",
+        "    engine = 'duckdb'\n",
+        "except Exception as e:\n",
+        "    import pandas as pd\n",
+        "    engine = 'pandas'\n",
+        "    print('DuckDB unavailable, using pandas:', e)\n",
+        "\n",
+        "if engine == 'duckdb':\n",
+        "    total_cve = con.execute(\"SELECT COUNT(*) FROM read_parquet(?)\", [str(PARQ/'cve.parquet')]).fetchone()[0]\n",
+        "    total_kev = con.execute(\"SELECT COUNT(*) FROM read_parquet(?)\", [str(PARQ/'kev.parquet')]).fetchone()[0]\n",
+        "else:\n",
+        "    import pandas as pd\n",
+        "    total_cve = len(pd.read_parquet(PARQ/'cve.parquet'))\n",
+        "    total_kev = len(pd.read_parquet(PARQ/'kev.parquet'))\n",
+        "print('rows:', {'cve': total_cve, 'kev': total_kev})\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Accuracy panel\n",
+        "import os\n",
+        "val_path = DOCS / 'VALIDATION.json'\n",
+        "if val_path.exists():\n",
+        "    validation = json.loads(val_path.read_text())\n",
+        "    keys = [\n",
+        "        'counts',\n",
+        "        'cvss_v3_presence_ratio',\n",
+        "        'cwe_presence_ratio',\n",
+        "        'kev_cve_coverage_ratio',\n",
+        "        'kev_cve_coverage_ratio_within_window',\n",
+        "        'kev_rows_total_fetched',\n",
+        "        'kev_rows_within_window',\n",
+        "        'kev_rows_filtered_out',\n",
+        "        'kev_within_window_over_global_ratio',\n",
+        "        'url_shape_failures',\n",
+        "        'http_head_failures_hard',\n",
+        "        'http_head_failures_flaky',\n",
+        "        'dead_reference_links',\n",
+        "        'duplicate_edges_dropped',\n",
+        "        'snapshot_as_of',\n",
+        "    ]\n",
+        "    summary = {k: validation.get(k) for k in keys}\n",
+        "    print(summary)\n",
+        "else:\n",
+        "    # Minimal local signal if validation omitted\n",
+        "    if engine == 'duckdb':\n",
+        "        cvss_ratio = con.execute(\"\"\"\n",
+        "          WITH t AS (\n",
+        "            SELECT COUNT(*) AS n, SUM(CASE WHEN cvss_v3_score IS NOT NULL THEN 1 ELSE 0 END) AS v\n",
+        "            FROM read_parquet(?)\n",
+        "          ) SELECT CAST(v AS DOUBLE)/n FROM t\n",
+        "        \"\"\", [str(PARQ/'nvd_meta.parquet')]).fetchone()[0]\n",
+        "    else:\n",
+        "        import pandas as pd\n",
+        "        m = pd.read_parquet(PARQ/'nvd_meta.parquet')\n",
+        "        cvss_ratio = float((m['cvss_v3_score'].notnull()).mean())\n",
+        "    print({'cvss_v3_presence_ratio': cvss_ratio})\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Provenance proof (sample rows)\n",
+        "if engine == 'duckdb':\n",
+        "    df = con.execute(\"\"\"\n",
+        "    SELECT c.cve_id, c.source, c.source_url, c.retrieved_at, c.source_record_hash\n",
+        "    FROM read_parquet(?) c\n",
+        "    ORDER BY c.cve_id\n",
+        "    LIMIT 5\n",
+        "    \"\"\", [str(PARQ/'cve.parquet')]).df()\n",
+        "else:\n",
+        "    import pandas as pd\n",
+        "    c = pd.read_parquet(PARQ/'cve.parquet', columns=['cve_id','source','source_url','retrieved_at','source_record_hash'])\n",
+        "    df = c.sort_values('cve_id').head(5)\n",
+        "from IPython.display import display\n",
+        "display(df)\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# KEV triage (top 20 by CVSS)\n",
+        "if engine == 'duckdb':\n",
+        "    df = con.execute(\"\"\"\n",
+        "    SELECT c.cve_id, m.cvss_v3_score, k.date_added, k.notes\n",
+        "    FROM read_parquet(?) k\n",
+        "    JOIN read_parquet(?) c ON c.cve_id = k.cve_id\n",
+        "    LEFT JOIN read_parquet(?) m ON m.cve_id = c.cve_id\n",
+        "    ORDER BY (m.cvss_v3_score IS NULL) ASC, m.cvss_v3_score DESC, k.date_added DESC\n",
+        "    LIMIT 20\n",
+        "    \"\"\", [str(PARQ/'kev.parquet'), str(PARQ/'cve.parquet'), str(PARQ/'nvd_meta.parquet')]).df()\n",
+        "else:\n",
+        "    import pandas as pd\n",
+        "    k = pd.read_parquet(PARQ/'kev.parquet')\n",
+        "    c = pd.read_parquet(PARQ/'cve.parquet')\n",
+        "    m = pd.read_parquet(PARQ/'nvd_meta.parquet')\n",
+        "    df = k.merge(c, on='cve_id').merge(m[['cve_id','cvss_v3_score']], on='cve_id', how='left')\n",
+        "    df = df.sort_values(['cvss_v3_score','date_added'], ascending=[False, False]).head(20)\n",
+        "from IPython.display import display\n",
+        "# Export first CVE id for downstream default in citations\n",
+        "try:\n",
+        "    DEFAULT_CVE_FOR_CITATIONS = df['cve_id'].iloc[0] if len(df) else None\n",
+        "except Exception:\n",
+        "    DEFAULT_CVE_FOR_CITATIONS = None\n",
+        "display(df)\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# CWE pivot (top 20)\n",
+        "if engine == 'duckdb':\n",
+        "    df = con.execute(\"\"\"\n",
+        "    SELECT u.cwe, COUNT(*) AS cnt\n",
+        "    FROM read_parquet(?) t, UNNEST(t.cwe_ids) AS u(cwe)\n",
+        "    GROUP BY 1\n",
+        "    ORDER BY cnt DESC\n",
+        "    LIMIT 20\n",
+        "    \"\"\", [str(PARQ/'nvd_meta.parquet')]).df()\n",
+        "else:\n",
+        "    import pandas as pd\n",
+        "    m = pd.read_parquet(PARQ/'nvd_meta.parquet')\n",
+        "    rows = []\n",
+        "    for _, r in m.iterrows():\n",
+        "        for c in (r['cwe_ids'] or []):\n",
+        "            rows.append(c)\n",
+        "    import collections\n",
+        "    cc = collections.Counter(rows)\n",
+        "    df = pd.DataFrame({'cwe': list(cc.keys()), 'cnt': list(cc.values())}).sort_values('cnt', ascending=False).head(20)\n",
+        "from IPython.display import display\n",
+        "display(df)\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Citations for a specific CVE\n",
+        "# Default: take the first CVE from KEV triage if available; otherwise use the placeholder below.\n",
+        "try:\n",
+        "    TARGET\n",
+        "except NameError:\n",
+        "    try:\n",
+        "        TARGET = DEFAULT_CVE_FOR_CITATIONS  # set by KEV triage cell\n",
+        "    except NameError:\n",
+        "        TARGET = None\n",
+        "    if TARGET is None:\n",
+        "        TARGET = 'CVE-2021-44228'  # change as desired\n",
+        "print('TARGET:', TARGET, '(set TARGET to override)')\n",
+        "\n",
+        "if engine == 'duckdb':\n",
+        "    df = con.execute(\"\"\"\n",
+        "    SELECT dst_id AS reference_url\n",
+        "    FROM read_parquet(?)\n",
+        "    WHERE src_type='cve' AND src_id=? AND edge_type='cve_ref_url'\n",
+        "    ORDER BY reference_url\n",
+        "    \"\"\", [str(PARQ/'edges.parquet'), TARGET]).df()\n",
+        "else:\n",
+        "    import pandas as pd\n",
+        "    e = pd.read_parquet(PARQ/'edges.parquet')\n",
+        "    df = (\n",
+        "        e[(e['src_type']=='cve') & (e['src_id']==TARGET) & (e['edge_type']=='cve_ref_url')]\n",
+        "        [['dst_id']].rename(columns={'dst_id':'reference_url'})\n",
+        "        .sort_values('reference_url')\n",
+        "    )\n",
+        "from IPython.display import display\n",
+        "display(df)\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# RAG config and retrieval (offline-only if model cached)\n",
+        "import pandas as pd\n",
+        "\n",
+        "# Read meta and print config\n",
+        "meta = pd.read_parquet(RAG/'meta.parquet')\n",
+        "assert bool(meta['normalize'][0]) and meta['metric'][0] == 'IP'\n",
+        "model_name = meta['model_name'][0]\n",
+        "dim = int(meta['dim'][0])\n",
+        "texts_count = int(meta.get('texts_count', pd.Series([None]))[0])\n",
+        "print({'model_name': model_name, 'dim': dim, 'normalize': True, 'metric': 'IP', 'texts_count': texts_count})\n",
+        "\n",
+        "# Enforce offline HF/Transformers and guard imports\n",
+        "import os\n",
+        "os.environ['HF_HUB_OFFLINE'] = '1'\n",
+        "os.environ['TRANSFORMERS_OFFLINE'] = '1'\n",
+        "\n",
+        "rag_enabled = True\n",
+        "try:\n",
+        "    from sentence_transformers import SentenceTransformer\n",
+        "    import faiss, numpy as np\n",
+        "except Exception as e:\n",
+        "    print('RAG disabled (missing sentence-transformers or faiss):', e)\n",
+        "    rag_enabled = False\n",
+        "\n",
+        "if rag_enabled:\n",
+        "    try:\n",
+        "        model = SentenceTransformer(model_name)\n",
+        "        index = faiss.read_index(str(RAG/'index.faiss'))\n",
+        "        id_map = pd.read_parquet(RAG/'mapping.parquet')\n",
+        "\n",
+        "        query = 'recent OpenSSL remote exploit'\n",
+        "        qvec = model.encode([query], normalize_embeddings=True)\n",
+        "        D, I = index.search(np.asarray(qvec, dtype='float32'), 10)\n",
+        "        print('scores:', D[0].tolist())\n",
+        "        from IPython.display import display\n",
+        "        hits = id_map[id_map['row_index'].isin(I[0].tolist())].merge(\n",
+        "            pd.DataFrame({'row_index': I[0].tolist()}), on='row_index', how='right'\n",
+        "        )\n",
+        "        display(hits)\n",
+        "    except Exception as e:\n",
+        "        print('RAG skipped (model not cached or index missing):', e)\n",
+        "        print('Tip: pre-cache once online, then re-run offline:')\n",
+        "        print(\"from sentence_transformers import SentenceTransformer; SentenceTransformer('BAAI/bge-small-en-v1.5')\")\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Consistency checks (fast)\n",
+        "if engine == 'duckdb':\n",
+        "    kev_total = con.execute(\"SELECT COUNT(*) FROM read_parquet(?)\", [str(PARQ/'kev.parquet')]).fetchone()[0]\n",
+        "    kev_without_cve = con.execute(\"\"\"\n",
+        "    SELECT COUNT(*) FROM read_parquet(?) k\n",
+        "    LEFT JOIN read_parquet(?) c ON c.cve_id = k.cve_id\n",
+        "    WHERE c.cve_id IS NULL\n",
+        "    \"\"\", [str(PARQ/'kev.parquet'), str(PARQ/'cve.parquet')]).fetchone()[0]\n",
+        "\n",
+        "    edges_with_missing_cve = con.execute(\"\"\"\n",
+        "    SELECT COUNT(*) FROM read_parquet(?) e\n",
+        "    LEFT JOIN read_parquet(?) c ON c.cve_id = e.src_id\n",
+        "    WHERE e.src_type='cve' AND c.cve_id IS NULL\n",
+        "    \"\"\", [str(PARQ/'edges.parquet'), str(PARQ/'cve.parquet')]).fetchone()[0]\n",
+        "\n",
+        "    sample_missing = [r[0] for r in con.execute(\"\"\"\n",
+        "    SELECT k.cve_id\n",
+        "    FROM read_parquet(?) k\n",
+        "    LEFT JOIN read_parquet(?) c ON c.cve_id = k.cve_id\n",
+        "    WHERE c.cve_id IS NULL\n",
+        "    ORDER BY k.cve_id\n",
+        "    LIMIT 5\n",
+        "    \"\"\", [str(PARQ/'kev.parquet'), str(PARQ/'cve.parquet')]).fetchall()]\n",
+        "\n",
+        "    kev_with_cve = int(kev_total) - int(kev_without_cve)\n",
+        "    coverage_ratio = (kev_with_cve / kev_total) if kev_total else 0.0\n",
+        "\n",
+        "    print({\n",
+        "        'kev_total': int(kev_total),\n",
+        "        'kev_with_cve': int(kev_with_cve),\n",
+        "        'kev_without_cve': int(kev_without_cve),\n",
+        "        'kev_cve_coverage_ratio': coverage_ratio,\n",
+        "        'edges_with_missing_cve': int(edges_with_missing_cve),\n",
+        "        'sample_missing_cves': sample_missing,\n",
+        "    })\n",
+        "else:\n",
+        "    print('Consistency checks require DuckDB for speed; skipped.')\n"
+      ]
+    }
+  ],
+  "metadata": {
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 2
+}

demo/requirements-colab.txt

@@ -0,0 +1,8 @@
+duckdb>=1.0.0
+pandas>=2.0.0
+pyarrow>=15.0.0
+numpy>=1.26.0
+faiss-cpu>=1.7.4
+sentence-transformers<3.0.0
+huggingface_hub>=0.20.0
+

docs/BUILD_MANIFEST.json

@@ -0,0 +1 @@
+{"snapshot_as_of":"2025-10-29T13:51:37Z","build_started_at":"2025-10-29T17:49:43Z","build_finished_at":"2025-10-29T17:49:43Z","python_version":"3.12.2","platform":"macOS-15.6.1-arm64-arm-64bit","os_release":"24.6.0","packages":{},"model_name":"BAAI/bge-small-en-v1.5","model_dim":384,"nvd_window_days":90,"git_commit":"d5ac518dcf3118f1c02eed15d147f71f23e0c3ea"}

docs/INTEGRITY.txt

@@ -0,0 +1,11 @@
+2813808c65fde193a159b6ae5d101e66c35995a03bbc38f33057e0592c92d2a0  docs/VALIDATION.json
+4c26c49fac2c2288ed78fce5e1620cfa9b36320a393543ae939d1533e0cf35da  parquet/.counts.json
+1224f3dd4152fb70e523a47bf244ba01582445fa25ff1b2a4000b2847e06f6f1  parquet/cve.parquet
+036f9af67420d301078c4a88f1caa4eda1c63354e429d8ea73198617b8c5c911  parquet/edges.parquet
+6268b8d528b37604dc8846e8a19c212dcd85d61dee9542d1d79ea92e6eeef1fc  parquet/kev.parquet
+a6ad1ddf69d59486a91850d5b0ea810bf181c7c6b10830adbc38d80da908de03  parquet/nvd_meta.parquet
+d07b58ecb437b479af8a02fc49f46f80166ccdd2c2f4abd1418e207cda38e84a  parquet/preview.parquet
+b60669f24f2050cd441139a4f58dc07d2e2e8330ebce75fc3b88ebc44f6e557c  rag/index.faiss
+380b434b36326888988f02fe47dff53e4a8b079a563e8352477c3ff8a3623052  rag/mapping.parquet
+95c0c3c104e28012ebf0cbacbf20346d992a6ed3960aa9792a6436743de726f3  rag/meta.parquet
+9dd9c208dc7bceef09351a5b3e807bf50e7f5e0a5e51c4768e65b29634c4fca6  rag/vectors.npy

docs/LICENCE.md

@@ -0,0 +1,121 @@
+Creative Commons Legal Code
+
+CC0 1.0 Universal
+
+    CREATIVE COMMONS CORPORATION IS NOT A LAW FIRM AND DOES NOT PROVIDE
+    LEGAL SERVICES. DISTRIBUTION OF THIS DOCUMENT DOES NOT CREATE AN
+    ATTORNEY-CLIENT RELATIONSHIP. CREATIVE COMMONS PROVIDES THIS
+    INFORMATION ON AN "AS-IS" BASIS. CREATIVE COMMONS MAKES NO WARRANTIES
+    REGARDING THE USE OF THIS DOCUMENT OR THE INFORMATION OR WORKS
+    PROVIDED HEREUNDER, AND DISCLAIMS LIABILITY FOR DAMAGES RESULTING FROM
+    THE USE OF THIS DOCUMENT OR THE INFORMATION OR WORKS PROVIDED
+    HEREUNDER.
+
+Statement of Purpose
+
+The laws of most jurisdictions throughout the world automatically confer
+exclusive Copyright and Related Rights (defined below) upon the creator
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+1. Copyright and Related Rights. A Work made available under CC0 may be
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+
+3. Public License Fallback. Should any part of the Waiver for any reason
+be judged legally invalid or ineffective under applicable law, then the
+Waiver shall be preserved to the maximum extent permitted taking into
+account Affirmer's express Statement of Purpose. In addition, to the
+extent the Waiver is so judged Affirmer hereby grants to each affected
+person a royalty-free, non transferable, non sublicensable, non exclusive,
+irrevocable and unconditional license to exercise Affirmer's Copyright and
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+limitation commercial, advertising or promotional purposes (the
+"License"). The License shall be deemed effective as of the date CC0 was
+applied by Affirmer to the Work. Should any part of the License for any
+reason be judged legally invalid or ineffective under applicable law, such
+partial invalidity or ineffectiveness shall not invalidate the remainder
+of the License, and in such case Affirmer hereby affirms that he or she
+will not (i) exercise any of his or her remaining Copyright and Related
+Rights in the Work or (ii) assert any associated claims and causes of
+action with respect to the Work, in either case contrary to Affirmer's
+express Statement of Purpose.
+
+4. Limitations and Disclaimers.
+  a. No trademark or patent rights held by Affirmer are waived, abandoned,
+     surrendered, licensed or otherwise affected by this document.
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+     warranties of any kind concerning the Work, express, implied,
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+     the present or absence of errors, whether or not discoverable, all to
+     the greatest extent permissible under applicable law.
+  c. Affirmer disclaims responsibility for clearing rights of other persons
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+     Further, Affirmer disclaims responsibility for obtaining any necessary
+     consents, permissions or other rights required for any use of the
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+  d. Affirmer understands and acknowledges that Creative Commons is not a
+     party to this document and has no duty or obligation with respect to
+     this CC0 or use of the Work.
+
+

docs/LICENSES.md

@@ -0,0 +1,41 @@
+## Licenses and Source Status
+
+Snapshot timestamp (UTC): 2025-10-29T13:51:37Z
+
+### Compiled artifact license (this dataset)
+
+- License: CC0 1.0 Universal (Public Domain Dedication)
+- Intent: Dedicate the compiled snapshot to the public domain.
+- See: `https://creativecommons.org/publicdomain/zero/1.0/`
+
+### Upstream sources included in the core snapshot
+
+- NVD (National Vulnerability Database)
+  - Status: Public Domain (U.S. Government work; not subject to copyright)
+  - Site: `https://nvd.nist.gov`
+  - Notes: The snapshot includes minimal, factual metadata derived from NVD records (e.g., CVE IDs, short descriptions, CVSS/CWE, reference URLs). Reference URLs are preserved exactly.
+  - Additional note: NVD data are U.S. Government works (public domain). Some material may be subject to foreign copyright.
+
+- CISA Known Exploited Vulnerabilities (KEV) Catalog
+  - License: CC0 1.0
+  - Site: `https://www.cisa.gov/known-exploited-vulnerabilities-catalog`
+  - License text: `https://www.cisa.gov/sites/default/files/licenses/kev/license.txt`
+  - Notes: The snapshot includes KEV fields such as `cveID`, `dateAdded`, and `notes`.
+
+### Explicit exclusions (not part of the core snapshot)
+
+- GitHub Security Advisories (GHSA): CC-BY-4.0; attribution required. Excluded from the core to keep the artifact PD/CC0-only.
+- OSV (Open Source Vulnerabilities): licenses vary by upstream source. Excluded from the core to avoid mixed licensing.
+
+### RAG pack content
+
+- The retrieval index (FAISS) is constructed only from PD/CC0 text fields (NVD short descriptions and KEV notes).
+
+### Notes
+
+- This file summarizes license posture for the released snapshot: PD/CC0-only inputs, compiled artifact dedicated under CC0 1.0.
+- See `NOTICE.md` for non-affiliation and warranty disclaimers.
+
+### Scope
+
+This licensing summary applies to the **dataset** only. Any code or notebooks in this repository (if present) are licensed separately; see the license file at the repository root (e.g., MIT).

docs/NOTICE.md

@@ -0,0 +1,25 @@
+## Notice
+
+Snapshot timestamp (UTC): 2025-10-29T13:51:37Z
+
+### Non-affiliation
+
+- This project is not affiliated with NIST/NVD, CISA/KEV, FIRST/EPSS, or any of their programs. Names and links are used for descriptive purposes only.
+- NVD non-endorsement: "This product uses data from the NVD API but is not endorsed or certified by the NVD."
+- All product names, logos, and brands are property of their respective owners; use here is for identification only and does not imply endorsement.
+
+### Warranty and usage
+
+- WITHOUT WARRANTIES OF ANY KIND, express or implied, including merchantability, fitness for a particular purpose, and non-infringement. Verify with linked official sources before relying operationally.
+- The snapshot is an immutable, one-time data drop intended for evaluation, prototyping, and research.
+- No SLA or support is provided. Issues/Discussions are welcome for feedback only.
+
+### Licensing summary
+
+- The compiled artifact is dedicated to the public domain under CC0 1.0.
+- Inputs are PD/CC0-only (NVD public domain; CISA KEV under CC0). Attribution-required sources (e.g., GHSA/OSV) are intentionally excluded from the core snapshot.
+- Linked third-party pages (vendor advisories, blogs, etc.) are not covered by this dataset’s CC0 dedication; their terms apply.
+
+### Integrity and transparency
+
+- Verify `docs/INTEGRITY.txt` (SHA-256 list) using standard tools.

docs/VALIDATION.json

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parquet/.counts.json

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