5.1 KiB
CPE guesser
CPE Guesser is a command-line tool or web service designed to guess the CPE name based on one or more keywords. The resulting CPE can then be used with tools like cve-search or vulnerability-lookup to perform actual searches using CPE names.
Requirements
- Valkey
- Python
Usage
To use CPE Guesser, you need to initialize the Valkey database with import.py
.
Once initialized, you can use the software with lookup.py
to find the most probable CPE matching the provided keywords.
Alternatively, you can call the web server (after running server.py
). For example:
curl -s -X POST http://localhost:8000/search -d '{"query": ["tomcat"]}' | jq .
Installation
git clone https://github.com/cve-search/cpe-guesser.git
cd cpe-guesser
- Download the CPE dictionary & populate the database with
python3 ./bin/import.py
. - Take a cup of black or green tea ().
python3 ./bin/server.py
to run the local HTTP server.
If you don't want to install it locally, there is a public online version. Check below.
Docker
Single image with existing Valkey
docker build . -t cpe-guesser:l.0
# Edit settings.yaml content and/or path
docker run cpe-guesser:l.0 -v $(pwd)/config/settings.yaml:/app/config/settings.yaml
# Please wait for full import
Docker-compose
cd docker
# Edit docker/settings.yaml as you want
docker-compose up --build -d
# Please wait for full import
Specific usage
If you do not want to use the Web server, lookup.py
can still be used. Example: docker exec -it cpe-guesser python3 /app/bin/lookup.py tomcat
Public online version
cpe-guesser.cve-search.org is public online version of CPE guesser which can be used via
a simple API. The endpoint is /search
and the JSON is composed of a query list with the list of keyword(s) to search for.
curl -s -X POST https://cpe-guesser.cve-search.org/search -d "{\"query\": [\"outlook\", \"connector\"]}" | jq .
[
[
18117,
"cpe:2.3:a:microsoft:outlook_connector"
],
[
60947,
"cpe:2.3:a:oracle:oracle_communications_unified_communications_suite_connector_for_microsoft_outlook"
],
[
68306,
"cpe:2.3:a:oracle:corporate_time_outlook_connector"
]
]
The endpoint /unique
is available to retrieve only the best-matching CPE entry.
curl -s -X POST https://cpe-guesser.cve-search.org/unique -d "{\"query\": [\"outlook\", \"connector\"]}" | jq .
"cpe:2.3:a:oracle:corporate_time_outlook_connector"
Command line - lookup.py
usage: lookup.py [-h] [--unique] WORD [WORD ...]
Find potential CPE names from a list of keyword(s) and return a JSON of the results
positional arguments:
WORD One or more keyword(s) to lookup
options:
-h, --help show this help message and exit
--unique Return the best CPE matching the keywords given
python3 lookup.py microsoft sql server | jq .
[
[
51325,
"cpe:2.3:a:microsoft:sql_server_2017_reporting_services"
],
[
51326,
"cpe:2.3:a:microsoft:sql_server_2019_reporting_services"
],
[
57898,
"cpe:2.3:a:quest:intrust_knowledge_pack_for_microsoft_sql_server"
],
[
60386,
"cpe:2.3:o:microsoft:sql_server"
],
[
60961,
"cpe:2.3:a:microsoft:sql_server_desktop_engine"
],
[
64810,
"cpe:2.3:a:microsoft:sql_server_reporting_services"
],
[
75858,
"cpe:2.3:a:microsoft:sql_server_management_studio"
],
[
77570,
"cpe:2.3:a:microsoft:sql_server"
],
[
78206,
"cpe:2.3:a:ibm:tivoli_storage_manager_for_databases_data_protection_for_microsoft_sql_server"
]
]
How does this work?
A CPE entry is composed of a human readable name with some references and the structured CPE name.
<cpe-item name="cpe:/a:10web:form_maker:1.7.17::~~~wordpress~~">
<title xml:lang="en-US">10web Form Maker 1.7.17 for WordPress</title>
<references>
<reference href="https://wordpress.org/plugins/form-maker/#developers">Change Log</reference>
</references>
<cpe-23:cpe23-item name="cpe:2.3:a:10web:form_maker:1.7.17:*:*:*:*:wordpress:*:*"/>
</cpe-item>
The CPE name is structured with a vendor name, a product name and some additional information. CPE name can be easily changed due to vendor name or product name changes, some vendor/product are sharing common names or name is composed of multiple words.
Data
Split vendor name and product name (such as _
) into single word(s) and then canonize the word. Building an inverse index using
the cpe vendor:product format as value and the canonized word as key. Then cpe guesser creates a ranked set with the most common
cpe (vendor:product) per version to give a probability of the CPE appearance.
Valkey structure
w:<word>
sets:<word>
sorted set with a score depending of the number of appearance
License
Software is open source and released under a 2-Clause BSD License
Copyright (C) 2021-2024 Alexandre Dulaunoy Copyright (C) 2021-2024 Esa Jokinen