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 lookups into the public CVE databases. Local lookups are usually faster and you can limit your sensitive queries via the Internet.
CVE-Search includes a back-end to store vulnerabilities and related information, an intuitive web interface for search and managing vulnerabilities, a series of tools to query the system and a web API interface.
First, you’ll need to have a Python 3 installation (3.3 or higher). 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. You can go to http://docs.mongodb.org/manual/installation/ for to get the packages for your distribution, or http://www.mongodb.org/downloads for the source code.
Also Read Armory – Tool To Take Lot Of External & Discovery Data
For the initial run, you need to populate the CVE database by running:
./sbin/db_mgmt.py -p
./sbin/db_mgmt_cpe_dictionary.py
./sbin/db_updater.py -c
It will fetch all the existing XML files from the Common Vulnerabilities and Exposures database and the Common Platform Enumeration. The initial Common Platform Enumeration (CPE) import might take some time depending of your configuration.
If you want to add the cross-references from NIST, Red Hat and other vendors:
./sbin/db_mgmt_ref.py
An updater script helps to start the db_mgmt_*
./sbin/db_updater.py -v
You can run it in a crontab, logging is done in syslog by default.
To easily drop and re-populate all the databases
./sbin/db_updater.py -v -f
This will drop all the existing external sources and reimport everything. This operation can take some time and it’s usually only required when new attributes parsing are added in cve-search.
You can search the database using search.py
./bin/search.py -p cisco:ios:12.4
./bin/search.py -p cisco:ios:12.4 -o json
./bin/search.py -f nagios -n
./bin/search.py -p microsoft:windows_7 -o html
If you want to search all the WebEx vulnerabilities and only printing the official references from the supplier.
./bin/search.py -p webex: -o csv -v "cisco"
You can also dump the JSON for a specific CVE ID.
./bin/search.py -c CVE-2010-3333
Or you can use the XMPP bot
./bin/search_xmpp.py -j mybot@jabber.org -p strongpassword
Or dump the last 2 CVE entries in RSS or Atom format
./bin/dump_last.py -f atom -l 2
Or you can use the webinterface.
./web/index.py
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.
./sbin/db_ranking.py -c "sap:netweaver" -g "accounting" -r 3
and then you can lookup the ranking (-r option) for a specific CVE-ID:
./bin/search.py -c CVE-2012-4341 -r -n
As cve-search is based on a set of tools, it can be used and combined with standard Unix tools. If you ever wonder what are the top vendors using the term “unknown” for their vulnerabilities:
python3 bin/search_fulltext.py -q unknown -f | jq -c '. | .vulnerable_configuration[0]' | cut -f5 -d: | sort | uniq -c | sort -nr | head -10
1500 oracle
381 sun
372 hp
232 google
208 ibm
126 mozilla
103 microsoft
100 adobe
78 apple
68 linux
You can compare CVSS (Common Vulnerability Scoring System ) values of some products based on their CPE name. Like comparing oracle:java versus sun:jre and using R to make some statistics about their CVSS values:
python3 bin/search.py -p oracle:java -o json | jq -r '.cvss' | Rscript -e 'summary(as.numeric(read.table(file("stdin"))[,1]))'
Min. 1st Qu. Median Mean 3rd Qu. Max.
1.800 5.350 9.300 7.832 10.000 10.000
python3 bin/search.py -p sun:jre -o json | jq -r '.cvss' | Rscript -e 'summary(as.numeric(read.table(file("stdin"))[,1]))'
Min. 1st Qu. Median Mean 3rd Qu. Max.
0.000 5.000 7.500 7.333 10.000 10.000
If you want to index all the CVEs from your current MongoDB collection:
./sbin/db_fulltext.py
and you query the fulltext index (to get a list of matching CVE-ID):
./bin/search_fulltext.py -q NFS -q Linux
or to query the fulltext index and output the JSON object for each CVE-ID:
./bin/search_fulltext.py -q NFS -q Linux -f
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.
./bin/search_fulltext.py -g -s >cve.json
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
./index.py
Then you can connect on http://127.0.0.1:5000/ to browser the last CVE.
The web interface includes a minimal JSON API to get CVE by ID, by vendor or product. A public version of the API is also accessible on cve.circl.lu.
List the know vendors in JSON
curl http://127.0.0.1:5000/api/browse/
Dump the product of a specific vendor in JSON
curl http://127.0.0.1:5000/api/browse/zyxel
{
"product": [
"n300_netusb_nbg-419n",
"n300_netusb_nbg-419n_firmware",
"p-660h-61",
"p-660h-63",
"p-660h-67",
"p-660h-d1",
"p-660h-d3",
"p-660h-t1",
"p-660h-t3",
"p-660hw",
"p-660hw_d1",
"p-660hw_d3",
"p-660hw_t3"
],
"vendor": "zyxel"
}
Find the associated vulnerabilities to a vendor and a product
curl http://127.0.0.1:5000/api/search/zyxel/p-660hw
[{"cwe": "CWE-352", "references": ["http://www.exploit-db.com/exploits/33518", "http://secunia.com/advisories/58513", "h
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