Cve-search - Common Vulnerabilities and Exposures local search tool

cve-search is a tool to import CVE (Common Vulnerabilities and Exposures) and CPE (Common Platform Enumeration) into a MongoDB to facilitate search and processing of CVEs.

Download .zip Download .tar.gz View on GitHub


cve-search is a tool to import CVE (Common Vulnerabilities and Exposures) and CPE (Common Platform Enumeration) into a MongoDB to facilitate search and processing of CVEs.

The main objective of the software is to avoid doing direct and public lookup into the public CVE databases. This is usually faster to do local lookups and limits your sensitive queries via the Internet.

cve-search visualization


If you are planning to use the full-text indexer, you'll need:

Installation of MongoDB

First, you'll need to have a Python 3 installation (3.2 or 3.3 preferred). Then you need to install MongoDB (2.2) from source (this should also work with any standard packages from your favorite distribution). Don't forget to install the headers for development while installing MongoDB.

Then, you'll need to install PyMongo to access from Python 3 the MongoDB databases. For installing PyMongo, you can download the source from the original website .

git clone
cd mongo-python-driver
python3 build
sudo python3 install

Populating the database

For the initial run, you need to populate the CVE database by running:

./ -p

It will fetch all the existing XML files from the Common Vulnerabilities and Exposures database and the Common Platform Enumeration.

By default, there is no secondary indexes created in MongoDB for the CVE/CPE database. You might want to create indexes on the fields that are commonly used for your searches. As the example, you can create the index for the following collection and key:

db.cpe.ensureIndex( {id:1 } )
db.cves.ensureIndex( {id:1} )
db.cves.ensureIndex( {vulnerable_configuration:1} )
db.vfeed.ensureIndex( {id:1} )
db.vendor.ensureIndex( {id:1} )

Database and collections

The MongoDB database is called cvedb and there are 6 collections:

  • cves (Common Vulnerabilities and Exposure items) - source NVD NIST
  • cpe (Common Platform Enumeration items) - source NVD NIST
  • vendor (Official Vendor Statements on CVE Vulnerabilities) - source NVD NIST
  • cwe (Common Weakness Enumeration items) - source NVD NIST
  • ranking (ranking rules per group) - local cve-search
  • vfeed (cross-references to CVE ids (e.g. OVAL, OpenVAS, ...)) - source vfeed
  • info (metadata of each collection like last-modified) - local cve-search

Updating the database

An updater script helps to start the db_mgmt_*

./ -v

You can run it in a crontab, logging is done in syslog by default.


You can search the database using

./ -p cisco:ios:12.4
./ -p cisco:ios:12.4 -o json
./ -f nagios -n
./ -p microsoft:windows_7 -o html

If you want to search all the WebEx vulnerabilities and only printing the official references from the supplier.

./ -p webex: -o csv  -v "cisco"

You can also dump the JSON for a specific CVE ID.

./ -c CVE-2010-3333

Or you can use the XMPP bot

./ -j -p strongpassword

Or dump the last 2 CVE entries in RSS or Atom format

./ -f atom -l 2

Usage of the ranking database

There is a ranking database allowing to rank software vulnerabilities based on their common platform enumeration name. The ranking can be done per organization or department within your organization or any meaningful name for you.

As an example, you can add a partial CPE name like "sap:netweaver" which is very critical for your accounting department.

./python3.3  -c "sap:netweaver" -g "accounting" -r 3

and then you can lookup the ranking (-r option) for a specific CVE-ID:

./python3.3 -c CVE-2012-4341  -r  -n

Fulltext indexing

If you want to index all the CVEs from your current MongoDB collection:


and you query the fulltext index (to get a list of matching CVE-ID):

./python3.3 -q NFS -q Linux

or to query the fulltext index and output the JSON object for each CVE-ID:

./python3.3 -q NFS -q Linux -j

Fulltext visualization

The fulltext indexer visualization is using the fulltext indexes to build a list of the most common keywords used in CVE. NLTK is required to generate the keywords with the most common English stopwords and lemmatize the output. NTLK for Python 3 exists but you need to use the alpha version of NLTK.

./python3.3  -g -s >cve.json

You can see a visualization on the demo site.

Web interface

The web interface is a minimal interface to see the last CVE entries and query a specific CVE. You'll need flask in order to run the website and Flask-PyMongo. To start the web interface:

cd ./web

Then you can connect on to browser the last CVE.


cve-search is free software released under the "Modified BSD license"

Copyright (c) 2012 Wim Remes -
Copyright (c) 2012-2013 Alexandre Dulaunoy -