Check the setup
- Python 3.10 or newer
- A notebook environment such as Jupyter or Google Colab
- An internet connection
CVE records enriched with severity, weakness, reference, and affected-product data for building vulnerability monitors and exposure triage tools.
From source to product signal
The NVD enriches CVE records with CVSS metrics, weaknesses, references, and affected-product configurations. Start with records modified during one recent week. NVD analysis can lag publication, CPE matching is imperfect, and CVSS severity does not measure exposure or business impact.
Install the packages, then run the notebook cell.
python -m pip install pandas requests
from datetime import datetime, timedelta, timezone
import pandas as pd
import requests
end = datetime.now(timezone.utc)
start = end - timedelta(days=7)
response = requests.get(
"https://services.nvd.nist.gov/rest/json/cves/2.0",
params={
"lastModStartDate": start.isoformat(timespec="milliseconds"),
"lastModEndDate": end.isoformat(timespec="milliseconds"),
"resultsPerPage": 100,
"noRejected": "",
},
timeout=30,
)
response.raise_for_status()
records = pd.json_normalize([item["cve"] for item in response.json()["vulnerabilities"]])
print(records[["id", "published", "lastModified", "vulnStatus"]].head(20))Test a useful signal
Identify CVE records modified during the last seven days and review their analysis status.
National Institute of Standards and Technology is a government source. Last verified 2026-08-13. Temporal coverage: 1999-present.