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CSV processing and mutual conversion of web related data types

Project description

Convey

Swiss knife for mutual conversion of the web related data types, like base64 or outputs of the programs whois, dig, curl. Convenable way to quickly gather all meaningful information or to process large files that might freeze your spreadsheet processor.

Any input is accepted:

  • if a single value input is detected, all meaningful information is fetched
  • multiline base64/quoted_printable string gets decoded
  • log file is converted to CSV
  • CSV file (any delimiter, header or whatever) performs one or more actions
    1. Pick, delete or sort columns (if only some columns are needed)
    2. Add a column (computes one field from another – see below)
    3. Unique filter (no value duplicates)
    4. Value filter (only rows with a specific values are preserved)
    5. Split by a column (produce separate files instead of single file; these can then be sent by generic SMTP or through OTRS)
    6. Change CSV dialect (change delimiter or quoting character)
    7. Aggregate (count grouped by a column, sum...)

Python3.6+ required.

Table of contents

Usage

Usage 1 – Single query

Check what happens if an IP is provided, it returns table with WHOIS-related information and scraped HTTP content.

$ convey 1.1.1.1 # single query input
Input value detected: ip

1.1.1.1 ...au

field             value
----------------  -----------------
prefix            1.1.1.0-1.1.1.255
asn               as13335
abusemail         abuse@apnic.net
country           au
netname           apnic-labs
csirt-contact     -
incident-contact  au
status            200
text              DNSThe free app that makes your (much longer text...)

Usage 2 – CSV processor program

Parses CSV file.

$ convey my-file-with-ips.csv # will trigger file parsing
Source file: /tmp/my-file.csv
Log lines: 200

Sample:
...

Delimiter character found: ','
Quoting character: '"'
Header is present: not used

Could you confirm this? [y]/n
...
...

Usage 3 – Web service

Again, let's provide an IP to the web service, it returns JSON with WHOIS-related information and scraped HTTP content.

# install convey and check where it is installed
$ pip3 show convey
Location: /home/$USER/.local/lib/python3.7/site-packages
# launch __main__.py with uwsgi (note that LACNIC may freeze for 300 s, hence the timeout recommendation)
$ uwsgi --http :26683 --http-timeout 310 --wsgi-file /home/$USER/.local/lib/python3.7/site-packages/convey/__main__.py

# Access: http://localhost:26683/?q=example.com
# {'ip': '93.184.216.34', 'prefix': '93.184.216.0-93.184.216.255', 'asn': '', 'abusemail': 'abuse@verizondigitalmedia.com', 'country': 'unknown', 'netname': 'edgecast-netblk-03', 'csirt-contact': '-', 'incident-contact': 'unknown', 'status': 200, 'text': 'DNSThe free app that makes your (much longer text...)'}

Installation and first run

Launch as a package:

# (optional) setup virtual environment
python3 -m venv venv
. venv/bin/activate
(venv) $ ... # continue below

# install from PyPi
pip3 install convey  # without root use may want to use --user

# (optional) alternatively, you may want to install current master from GitHub
pip3 install git+https://github.com/CZ-NIC/convey.git

# (optional) install bash completion script
# 1. apt-get install bash-completion jq
# 2. pip3 show convey # → shows location /home/$USER/.local/lib/python3.7/site-packages
# 3. copy /home/$USER/.local/lib/python3.7/site-packages/convey/extra/convey-autocompletion.bash /etc/bash_completion.d/convey-autocompletion.bash

# launch
convey [filename or input text] # or try `python3 -m convey` if you're not having `.local/bin` in your executable path

Parameter [filename or input text] may be the path of the CSV source file or any text that should be parsed. Note that if the text consist of a single value, program prints out all the computable information and exits; I.E. inputting a base64 string will decode it.

OR launch from a directory

# download from GitHub
git clone git@github.com:CZ-NIC/convey.git
cd convey
pip3 install -r requirements.txt  --user

# launch
./convey.py

Dependencies and troubleshooting

  • You'll be asked to install dialog library at the first run if not already present in the system.
  • If something is missing on your system, you may find help yourself with this command: sudo apt install python3-pip python3-tk git gcc dialog whois dnsutils nmap curl && pip3 install setuptools wheel && pip3 install --upgrade ipython

Customisation

  • Convey tries to open the file in the default GUI editor or in the terminal editor if GUI is not an option.
  • If config.ini is present at working directory, that one is used over the one in the user config folder.
  • Configuration is updated automatically on upgrade.

Computing fields

Computable fields

Some of the field types we are able to compute:

  • abusemail – got abuse e-mail contact from whois
  • asn – got from whois
  • base64 – encode/decode
  • country – country code from whois
  • csirt-contact – e-mail address corresponding with country code, taken from your personal contacts_foreign CSV in the format country,abusemail. Path to this file has to be specified in config.ini » contacts_foreign
  • external – you specify method in a custom .py file that receives the field and generates the value for you, see below
  • hostname – domain from url
  • incident-contact – if the IP comes from local country (specified in config.ini » local_country) the field gets abusemail, otherwise we get country. When splitting by this field, convey is subsequently able to send the splitted files to local abuse and foreign csirt contacts
  • ip – translated from url
  • netname – got from whois
  • prefix – got from whois

Detectable fields

Some of the field types we are able to auto-detect:

  • ip – standard IPv4 / IPv6 addresses
  • cidr – CIDR notation, ex: 127.0.0.1/32
  • port_ip – IPv4 in the form 1.2.3.4.port
  • any_ip – IPv4 garbled in the form any text 1.2.3.4 any text
  • hostname – or FQDN; 2nd or 3rd domain name
  • url – URL starting with http/https
  • asn – AS Number
  • base64 – text encoded with base64
  • wrong_url – URL that has been deactivated by replacing certain chars, ex: "hxxp://example[.]com"

Overview of all methods:

Current field computing capacity can be get from --show-uml flag. Generate yours by ex: convey --show-uml | dot -Tsvg -o /tmp/convey-methods.svg

  • Dashed node: field type is auto-detectable
  • Dashed edge: field types are identical
  • Edge label: generating options asked at runtime
  • Rectangle: field category border

Methods overview

External field how-to

Simple custom method

If you wish to compute an external field, prepare a file whose contents can be as simple as this:

def any_method(value):
    # do something
    return "modified :)"
Launch an external method
  • When CSV processing, hit 'Add column' and choose 'new external... from a method in your. py file'
  • Or in the terminal append --field external to your convey command. A dialog for a path of the Python file and desired method will appear.
$ convey [string_or_filepath] --field external 
  • You may as well directly specify the path and the callable. Since the --field has following syntax:

FIELD[[CUSTOM]],[COLUMN],[SOURCE_TYPE],[CUSTOM],[CUSTOM]

You may omit both COLUMN and SOURCE_TYPE writing it this way:

FIELD,COLUMN,SOURCE_TYPE,CUSTOM,CUSTOM
external,/tmp/myfile.py,any_method

$ convey [string_or_filepath] --field external,/tmp/myfile.py,any_method
Input value seems to be plaintext.
field     value
--------  -----------------------
external  modified :)
Register an external method
  • You may as well hard code custom fields in the config.ini by providing paths to the entry point Python files delimited by a comma: external_fields = /tmp/myfile.py, /tmp/anotherfile.py. All the public methods in the defined files will become custom fields!
[EXTERNAL]
external_fields = /tmp/myfile.py
  • If this is not needed, you may register one by one by adding new items to the EXTERNAL section. Delimit the method name by a colon.
[EXTERNAL]
any_method = /tmp/myfile.py:any_method

List of results possible

If you need a single call to generate multiple rows, return list, the row accepting a list will be duplicated.

def any_method(value):
    # do something
    return ["foo", "bar"]

When convey receives multiple lists, it generates a row for each combination. Ex: If a method returns 2 items and another 3 items, you will receive 6 similar rows.

PickMethod decorator

Should there be multiple ways of using your generator, place them as methods of a class decorated with PickMethod and let the user decide at the runtime. PickMethod has optional default:str parameter that specifies the default method.

from convey import PickMethod

@PickMethod("all")
class any_method(PickMethod):
    def all(x):
        ''' All of them.  '''
        return x
    
    def filtered(cls, x):
        ''' Filter some of them '''
        if x in country_code_set:
            return x
$ convey file.csv --field any_method  # user will be asked whether to use `all` or `filtered`
$ convey file.csv --field any_method[filtered]  # `filtered` sub-method will be used
$ convey file.csv --field any_method --yes  # the default `all` sub-method will be used

PickInput decorator

If you need a direct user entry before each processing, import PickInput and make your method accept two parameters. The latter will be set by the user and may have a default value.

from convey import PickInput

@PickInput
def time_format(val, format="%H:%M"):
    ''' This text will be displayed to the user.
        If running in headless mode, the default format will be "%H:%M" (hours:minutes).   '''
    return dateutil.parser.parse(val).strftime(format)
$ convey file.csv --field time_format  # user will be asked for a format parameter
$ convey file.csv --field time_format[%M]  # `format` will have the value `M%`
$ convey file.csv --field time_time --yes  # the default `format` `%H:%M` will be used

Examples

In the examples, we will use these parameters to add a field and to shorten the result.

# -f, --field adding field syntax: FIELD[[CUSTOM]],[COLUMN],[SOURCE_TYPE],[CUSTOM],[CUSTOM]
# -H, --headless: just quietly print out single value, no dialog

URL parsing

Output formats

Put any IP or URL as the argument.

$ convey example.com
Input value detected: hostname

Whois 93.184.216.34... abuse@verizondigitalmedia.com
Scrapping http://example.com...
field             value
----------------  ------------------------------------------------------------------------------
cidr              93.184.216.0/24
ip                93.184.216.34
tld               com
url               http://example.com
abusemail         abuse@verizondigitalmedia.com
csirt_contact     -
incident_contact  abuse@verizondigitalmedia.com
netname           edgecast-netblk-03
prefix            93.184.216.0-93.184.216.255
a                 93.184.216.34
aaaa              2606:2800:220:1:248:1893:25c8:1946
mx                0 .
ns                ['a.iana-servers.net.', 'b.iana-servers.net.']
spf               v=spf1 -all
http_status       200
text              Example Domain
                  This domain is for use in illustrative examples in documents. You may use this
                   domain in literature without prior coordination or asking for permission.
                  More informatio
                  n...

Should you need just the country the domain/IP is hosted in, use --field, -f argument

$ convey wikipedia.com -f country
Input value detected: hostname

Whois 208.80.154.232... us
field    value
-------  -------
country  us

Use --headless, -H or --quiet, -q flag to shorten the output (and cut down all dialogues).

$ convey wikipedia.com -f country -H
us

Flag --json modifies the output.

$ convey wikipedia.com -f country -H --json
{"country": "us"}

Computing TLD from another column

To compute a TLD from the abusemail that is being used for the IP domain is hosted in, add a field abusemail and then another field tld. Specifically say that the latter should source from the second column (which is abusemail) – either type '2' or 'abusemail'.

$ convey example.com -f abusemail -f tld,2
$ convey example.com -f abusemail -f tld,abusemail
Input value detected: hostname

Whois 93.184.216.34... abuse@verizondigitalmedia.com
field      value
---------  -----------------------------
abusemail  abuse@verizondigitalmedia.com
tld        com

To prevent abusemail from being output, use --field-excluded, -fe instead of --field, -f:

$ convey example.com -fe abusemail -f tld,2 -H
Input value detected: hostname

Whois 93.184.216.34... abuse@verizondigitalmedia.com
field    value
-------  -------
tld      com

We did not say earlier, user is asked each time whether they wish to get any tld, gTLD (ex: com) or ccTLD (ex: cz). You may specify it from CLI by one of those equivalent commands.

$ convey test.csv --fresh --field tld[gTLD]
$ convey test.csv --fresh --field tld,,,gTLD

# flag --yes or --headless will choose the default option which is *all*
$ convey test.csv --fresh --field tld --yes

CSV processing

Should you have a list of the object that you want to enrich of a CIDR they are hosted at, load the file test.csv they are located in.

# file text.csv
domain list
wikipedia.com
example.com

And see the menu just by adding --field cidr argument.

$ convey test.csv -f cidr
Source file: /tmp/ram/test.csv
Identified columns: 
Log lines: 3

Sample:
domain list
wikipedia.com
example.com

Delimiter character found: ','
Quoting character: '"'
Header is present: yes

Could you confirm this? [y]/n: (HIT ENTER)

Source file: /tmp/ram/test.csv, delimiter: ',', quoting: '"', header: used
Identified columns: domain list (hostname)
Computed columns: cidr (from domain list)
Log lines: 3

Sample:
domain list
wikipedia.com
example.com

Whois 208.80.154.232... us
Whois 93.184.216.34... abuse@verizondigitalmedia.com
Preview:
domain list      cidr from:
   (hostname)    domain list
---------------  ---------------
wikipedia.com    208.80.152.0/22
example.com      93.184.216.0/24

Main menu - how the file should be processed?
1) Pick or delete columns
2) Add a column
3) Unique filter
4) Value filter
5) Split by a column
6) Change CSV dialect
p) process ←←←←←
~) send (split first)
~) show all details (process first)
r) Refresh...
c) Config...
x) exit
?  

File splitting

We will create an ASN field and split the file.csv by this field, without adding it into the output.

# file.csv
wikipedia.com,443,2016-02-09T01:12:26-05:00,16019,US
seznam.cz,25,2016-02-27T22:20:21-05:00,16019,CZ
google.com,25,2016-02-28T02:27:21-05:00,16019,US
$ convey file.csv --field-excluded asn --split asn
(...)
** Processing completed: 3 result files in /tmp/ram/file.csv_convey1573236314
(...)
# file as14907
wikipedia.com,443,2016-02-09T01:12:26-05:00,16019,US
# file as43037
seznam.cz,25,2016-02-27T22:20:21-05:00,16019,CZ
# file as15169
google.com,25,2016-02-28T02:27:21-05:00,16019,US

CSIRT Usecase

A CSIRT may use the tool to automate incident handling tasks. The input is any CSV we receive from partners; there is at least one column with IP addresses or URLs. We fetch whois information and produce a set of CSV grouped by country AND/OR abusemail related to IPs. These CSVs are then sent by through OTRS from within the tool.
A most of the work is done by this command.

convey --field-excluded incident_contact,source_ip --split incident_contact --yes [FILENAME]

Custom code field

Adding a column from custom Python code:

$ convey example.com -f code,"x=x[1:5]"
xamp

Base64 and Regular expressions

Code there and back:

$ convey hello -f base64  -H  # --headless conversion to base64
aGVsbG8=
$ convey aGVsbG8= -H  # automatically identifies input as base64 and produces plaintext
hello

Use a reg column for regular expressions.

# start adding a new reg column wizzard that will take decoded "hello" as input 
$ convey aGVsbG8= -f reg
$ convey aGVsbG8= -f reg_s,"ll","LL" -H   # substitute 'll' with 'LL'
heLLo

Specify source

# start adding a new reg column wizzard that will take plaintext "aGVsbG8=" as input 
$ convey aGVsbG8= -f reg,plaintext
# specifying plaintext as a source type will prevent implicit convertion from base64
$ convey aGVsbG8= -f reg_s,plaintext,"[A-Z]","!" -H  # substitute uppercase letters with '!'
a!!sb!8=

Converting units

We are connected to the pint unit converter!

$ convey "3 kg" 
Input value detected: unit

field      value
---------  --------------------------------------------------------------------------------------------
plaintext  ['1.806642538265029e+27 atomic_mass_unit', '105.82188584874123 ounce', '96.45223970588393 ap
           othecary_ounce', '0.0703602964419822 bag', '0.05905239165666364 long_hunderweight', '0.06613
           867865546327 US_hundredweight', '0.002952619582833182 UK_ton', '0.002952619582833182 long_to
           n', '1929.0447941176785 pennyweight', '46297.07505882429 grain', '1.7935913792661326e+27 pro
           ton_mass', '771.6179176470714 apothecary_dram', '3000.0 gram', ...]


$ convey "3 kg" -f unit # launches wizzard that let's you decide what unit to convert to 
$ convey "3 kg" -f unit[g] -H
3000.0 gram

$ convey "kg" -f unit --csv-processing --headless
kg|6.022141794216764e+26 atomic_mass_unit
kg|0.001 metric_ton
kg|0.0009842065276110606 UK_ton
kg|771.6179176470714 scruple
kg|257.2059725490238 apothecary_dram
kg|1000.0 gram


# You may try to specify the units with no space and quotation.
# In the following example, convey expand all time-units it is able to compute
# – time units will be printed out and each is base64 encoded. 
$ convey 3hours
Input value detected: timestamp, unit

field                value
-------------------  ------------------------------------------------------------------
(...)
base64               ['MC4wMDQxMDY4NjM4OTc0NTAwNzcgbW9udGg=', 'MTA4MDAuMCBzZWNvbmQ=', 'MC4wMTc4NTcxNDI4NTcxNDI4NSB3ZWVr'] 
plaintext            ['0.004106863897450077 month', '10800.0 second', '0.01785714285714285 week', (...)]
time                 03:00:00
(...)

# What if
$ convey 3hours -f urlencode
Input value detected: timestamp, unit

Input unit_expand variable unit: *you type here sec or seconds to see the wizzard*                                                                                                                                                                                                                                           
Preview                                                                                                                                                                                                            
| original   | result         |                                                                                                                                                                                    
|------------|----------------|                                                                                                                                                                                    
| 3hours     | 10800.0 second |                                                                                                                                                                                    

field      value
---------  ----------------
urlencode  10800.0%20second

# What if we wanted to urlencode text "3hours" without converting it to unit first? 
# Just specify the SOURCE_TYPE to be plaintext:
$ convey "3hours" -f urlencode,plaintext
Input value detected: timestamp, unit

field      value
---------  -------
urlencode  3hours

Country names

When specifying country code, you get country name.

$ convey --type country sc
Seychelles

Lots of countries can be recognized.

bash
$ convey --type country_name Futuna
wf

You may get the country code from various telephone number formats.

$ convey +2481234567
Seychelles

$ convey "1-541-754-3010"
['ca', 'us']

$ convey 

Aggregate

Syntax is [COLUMN, FUNCTION], ..., [group-by-COLUMN].
Possible functions are:

  • avg
  • sum
  • count
  • min
  • max
  • list
  • set

Let's have a file.

# file.csv
category,price,consumption
bulb,100,30
bulb,150,10
kettle,250,70
kettle,352,80
bulb,120,15

Sum the price column.

$ convey file.csv --aggregate price,sum
  sum(price)
------------
         972

Group the price sum by category.

$ convey file.csv --aggregate price,sum,category
category     sum(price)
---------  ------------
total               972
bulb                370
kettle              602

Group the price sum and the consumption average value by category.

$ convey file.csv --aggregate price,sum,consumption,avg,category
category      sum(price)    avg(consumption)
----------  ------------  ------------------
total                972               41
bulb                 370               18.33
kettle               602               75

Group the price sum by category and list its values.

$ convey file.csv --aggregate price,sum,price,list,category
category      sum(price)  list(price)
----------  ------------  ---------------------
total                972  (all)
bulb                 370  ['100', '150', '120']
kettle               602  ['250', '352']

You can even split while aggregating. Each file will count its own results.

$ convey file.csv --agg price,sum --split category

Split location: bulb
  sum(price)
------------
         370

Split location: kettle
  sum(price)
------------
         602

Credits

Brought by CSIRT.cz.

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