Reserved CVEs by Reference Count

import os
import vulncheck_sdk
import pandas as pd
from datetime import datetime
from dotenv import load_dotenv
from vulncheck_sdk.models.api_nvd20_cve_extended import ApiNVD20CVEExtended

load_dotenv()

DEFAULT_HOST = "https://api.vulncheck.com"
DEFAULT_API = DEFAULT_HOST + "/v3"
TOKEN = os.environ["VULNCHECK_API_TOKEN"]

# Configure API client
configuration = vulncheck_sdk.Configuration(host=DEFAULT_API)
configuration.api_key["Bearer"] = TOKEN

# Container for collected data
cve_data = []

# Use your preconfigured 'configuration' object (do NOT reinitialize it)
with vulncheck_sdk.ApiClient(configuration) as api_client:
    indices_client = vulncheck_sdk.IndicesApi(api_client)
    limit = 2000  # Adjust as needed

    def process_entry(entry: ApiNVD20CVEExtended):
        try:
            # Extract CVE ID
            cve_id = entry.id

            # Extract and format published date
            published = getattr(entry, "published", None)
            published_date = (
                datetime.fromisoformat(published.replace("Z", "")).date()
                if published else None
            )

            # Extract all references
            references = getattr(entry, "references", [])
            ref_count = len(references)  # Count all references

            # Get first reference URL and date
            first_ref_url = references[0].url if references else None
            first_ref_date_raw = references[0].date_added if references else None
            first_ref_date = (
                datetime.fromisoformat(first_ref_date_raw.replace("Z", "")).date()
                if first_ref_date_raw else None
            )

            # Append to data collection
            cve_data.append({
                "CVE": cve_id,
                "Published Date": published_date,
                "Reference Count": ref_count,
                "First Reference URL": first_ref_url,
                "First Reference Date": first_ref_date
            })

        except Exception as e:
            print(f"Error processing entry {getattr(entry, 'id', '[unknown]')}: {e}")

    # Initial fetch
    api_response = indices_client.index_vulncheck_nvd2_get(start_cursor="true", limit=limit)
    for entry in api_response.data:
        process_entry(entry)

    # Pagination loop
    while api_response.meta.next_cursor is not None:
        api_response = indices_client.index_vulncheck_nvd2_get(cursor=api_response.meta.next_cursor, limit=limit)
        for entry in api_response.data:
            process_entry(entry)

# Create DataFrame
df = pd.DataFrame(cve_data)

# Display results
display(df.head())

This list includes reserved CVEs that have not yet been published, sorted in descending order based on the number of references associated with each.

from IPython.display import display, HTML
import pandas as pd

# Step 1: Filter only on Published Date being 1970-01-01
df_filtered = df[df["Published Date"] == pd.to_datetime("1970-01-01").date()].copy()

# Step 2: Sort by highest reference count
df_sorted = df_filtered.sort_values("Reference Count", ascending=False).reset_index(drop=True)

# Step 3: Truncate to Top 50
top_50 = df_sorted.head(50).copy()

# Step 4: Replace any NaNs with "-"
columns_to_clean = ["CVE", "Published Date", "Reference Count", "First Reference URL", "First Reference Date"]
for col in columns_to_clean:
    top_50[col] = top_50[col].fillna("-")

# Step 5: Format and render HTML
title_html = f"""
<h2 style="margin-bottom: 5px;">Top 50 Reserved CVEs by Public Reference Count</h2>
<p><strong>Total Matching CVEs: {len(df_filtered)}</strong></p>
"""

table_html = top_50[[
    "CVE",
    "Reference Count",
    "First Reference URL",
    "First Reference Date"
]].to_html(index=False, escape=False)

scrollable_html = f"""
{title_html}
<div style="max-height: 500px; overflow-y: scroll; border: 1px solid #ccc; padding: 10px">
    {table_html}
</div>
"""

display(HTML(scrollable_html))

Reserved CVE's

Reserved But Exploited CVEs

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Reserved CVEs by Reference Count¶