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Tool to guess CPE name based on common software name

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README.md

CPE guesser

CPE guesser is a command-line or web service to guess the CPE name based on one or more keyword(s). Then the result can be used against cve-search to do actual searches by CPE names.

Requirements

Redis
Python

Usage

To use CPE guesser, you have to initialise the Redis database with import.py. Then you can use the software with lookup.py to find the most probable CPE matching the keywords provided.

Command line - `lookup.py`

usage: lookup.py [-h] [--word WORD]

Find potential CPE names from a list of keyword(s) and return a JSON of the results

optional arguments:
  -h, --help   show this help message and exit
  --word WORD  One or more keyword(s) to lookup

python3 lookup.py  --word microsoft --word sql --word server | jq .
[
  [
    51076,
    "cpe:2.3:a:microsoft:sql_server_2017_reporting_services"
  ],
  [
    51077,
    "cpe:2.3:a:microsoft:sql_server_2019_reporting_services"
  ],
  [
    57612,
    "cpe:2.3:a:quest:intrust_knowledge_pack_for_microsoft_sql_server"
  ],
  [
    60090,
    "cpe:2.3:o:microsoft:sql_server"
  ],
  [
    60660,
    "cpe:2.3:a:microsoft:sql_server_desktop_engine"
  ],
  [
    64489,
    "cpe:2.3:a:microsoft:sql_server_reporting_services"
  ],
  [
    75465,
    "cpe:2.3:a:microsoft:sql_server_management_studio"
  ],
  [
    77161,
    "cpe:2.3:a:microsoft:sql_server"
  ],
  [
    77793,
    "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.

Redis structure

w:<word> set
s:<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