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Home / Tips and Tricks / How to find OSINT data on license plate numbers with Skiptracer «Null Byte :: WonderHowTo

How to find OSINT data on license plate numbers with Skiptracer «Null Byte :: WonderHowTo



While performing an OSINT survey, it is important that you be able to retrieve information based on any clue you discover. In particular, license plate information can pop up anywhere from photos to live data to your own street. You could use that data to find the VIN for a vehicle, see if a Tinder date hit someone with their car, and so on. Skiptracer can help you get the ball rolling.

For starters, Python 2 must be installed and updated on your system. Skiptracer's developer, xillwillx, is updating the tool to Python 3 because Python 2 is no longer supported, but it's not quite ready yet, so Python 2 is what we need right now. To see if you have Python 2 installed, use:

  ~ $ python 2 --version

Python 2.7.1
8

Python 2.7.18 is the latest version, so you're good if that's what's coming. If you don't already have it, install or update it with:

  ~ $ sudo apt install python2
[sudo] password for kali:

Read package lists ... Done
Build dependency tree
Read status information ... Done
python2 is already the latest version (2.7.17-2).
python2 set to manually installed.
0 upgraded, 0 newly installed, 0 to uninstall and 122 not upgraded. 

Once you have the license plate and the condition of the vehicle for which you want to perform an OSINT investigation, you can start plugging the data in online. Still, most of them will try to charge you high fees to access all the information. Therefore, Skiptracer is an excellent tool to use as it queries some APIs to see if it can find information from the best available sources for free.

Now, to get started with Skiptracer, after you know that you already have Python 2 installed and up to date, you need to download the tool from xillwillx & # 39; s GitHub. It is quite easy to install because you have to clone the repository with:

  ~ $ git clone https://github.com/xillwillx/skiptracer.git

loning in & # 39; skiptracer & # 39; ...
remote: List objects: 3, done.
remote: Object counting: 100% (3/3), done.
remote control: Compress objects: 100% (3/3), done.
remote: total 1098 (delta 0), reused 0 (delta 0), pack reused 1095
Objects received: 100% (1098/1098), 388.83 KiB | 1.85 MiB / s, ready.
Solve deltas: 100% (654/654), done. 

To see what has been downloaded in the repository, you can cd to skiptracer and then ls . to view the files.

  ~ $ CD skip tracer
~ / skiptracer $ ls

Changelog Dockerfile LICENSE plugins README.md requirements.txt skiptracer.py storage 

If you've ever installed a Python program before, it's pretty clear what to do next. For those of you who don't know or don't know, you need to install the requirements.text file, which is a list of all the different modules that Skiptracer needs to work. Use the command pip install -r to install it.

  ~ / skiptracer $ pip install -r requirements.txt

Collect Python docx
Download Python-docx-0.8.10.tar.gz (5.5 MB)
| ████████████████████████████████ | 5.5 MB 880 kB / s
Requirement already met: urllib3 in / usr / lib / python3 / dist-packages (from -r requirements.txt (line 2)) (1.25.8)
Collect BS4
Download Bs4-0.0.1.tar.gz (1.1 KB)
Requirement already met: lxml in / usr / lib / python3 / dist-packages (from -r requirements.txt (line 4)) (4.5.0)
Requirement already met: Requests in / usr / lib / python3 / dist-packages (from -r requirements.txt (line 5)) (2.23.0)
Collect IPDB
Download IPDB-0.13.2.tar.gz (14 KB)
Collect print
Download pprint-0.1.tar.gz (860 bytes)
Requirement already met: click in / usr / lib / python3 / dist-packages (from -r requirements.txt (line 8)) (7.0)
Collect cfscrape
Download Cfscrape-2.1.1-py3-none-any.whl (12 KB)
Requirement already fulfilled: numpy in / usr / lib / python3 / dist-packages (from -r requirements.txt (line 10)) (1.17.4)
Requirement already fulfilled: simplejson in / usr / lib / python3 / dist-packages (from -r requirements.txt (line 11)) (3.17.0)
Requirement already met: tqdm in / usr / lib / python3 / dist-packages (from -r requirements.txt (line 12)) (4.43.0)
Requirement already fulfilled: beautifulsoup4 in / usr / lib / python3 / dist-packages (from bs4 -> - r requirements.txt (line 3)) (4.9.0)
Requirement already met: setuptools in / usr / lib / python3 / dist-packages (from ipdb -> - r requirements.txt (line 6)) (46.1.3)
Requirement already met: ipython> = 5.1.0 in / usr / lib / python3 / dist-packages (from ipdb -> - r requirements.txt (line 6)) (7.13.0)
Requirement already met: expected in / usr / lib / python3 / dist packages (from ipython> = 5.1.0-> ipdb -> - r requirements.txt (line 6)) (4.6.0)
Build wheels for collected packages: python-docx, bs4, ipdb, pprint
Build wheel for python-docx (setup.py) ... done
Wheel made for python-docx: filename = python_docx-0.8.10-py3-none-any.whl size = 184489 sha256 = 32c641b12abc6ff6aee1d56a517a41bfef0f0141f16b8a56959a17e160b6eae1
Stored in folder: /home/kali/.cache/pip/wheels/97/4c/2e/68066cbf12b9b2e66403da8982aaf4f656d9f5cb5dc3179e82
Build wheel for bs4 (setup.py) ... done
Wheel made for bs4: filename = bs4-0.0.1-py3-none-any.whl size = 1272 sha256 = 38acc084f674266787666f8155ea215bcb5b396e0c10abda215e7eb6c2606b01
Stored in folder: /home/kali/.cache/pip/wheels/75/78/21/68b124549c9bdc94f822c02fb9aa3578a669843f9767776bca
Build wheel for ipdb (setup.py) ... done
Wheel made for ipdb: filename = ipdb-0.13.2-py3-none-any.whl size = 10520 sha256 = 80973c70adb010a911087952c8eb2b65df2c2c39200d55bf5142fcc4bd5809c1
Stored in folder: /home/kali/.cache/pip/wheels/31/f3/58/accdf45cba573136dff3bc0e8aad1848899255f5fc3266a9fc
Build wheel for pprint (setup.py) ... done
Wheel made for pprint: filename = pprint-0.1-py3-none-any.whl size = 1250 sha256 = d925426ad1cb6c7b20b03248fcacffb846477c9b4fa4939417a14b651a65cf2e
Stored in folder: /home/kali/.cache/pip/wheels/db/43/1c/d58ea998a94cba18fba3d83fb3f574dcefe66b825f039cd932
Successfully built python-docx bs4 ipdb pprint
Install collected packages: python-docx, bs4, ipdb, pprint, cfscrape
Installed successfully bs4-0.0.1 cfscrape-2.1.1 ipdb-0.13.2 pprint-0.1 python-docx-0.8.10 

Next we execute the actual skiptracer.py file. When we run it, we see a great banner and a list of several things we can do.

  ~ / skiptracer $ python skiptracer.py

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, .- ~ * ´¨¯¨` * · ~ -.¸- (by) -, .- ~ * ´¨¯¨` * · ~ -.¸

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https://illmob.org

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https://illmob.org

[!] Lookup menu:
[1] Email - Search for targets by email address
[2] Name - Search targets by first name combination
[3] Phone - Search for targets by phone number
[4] ScreenName - Search for targets by known alias
[5] Plate - Search targets by license plate
[6] Domain - Search for targets by domain
[7] Help - Application details and usage scenarios
[88] Report - Generates a docx report of queries
[99] Exit - End the application
[!] Select a number to continue: 

The most obvious choice here is "plate". Many of the other options you see are in other tools, such as Sherlock ("ScreenName"), but we focus only on plate searches. Go ahead and select number 5 to do this.

[!]   Select a number to continue: 5

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, .- ~ * ´¨¯¨` * · ~ -.¸- (by) -, .- ~ * ´¨¯¨` * · ~ -.¸

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https://illmob.org

[!] ScreenName Search Menu: Target Info - None
[1] All: Run all modules associated with the email module group
[2] Plate Search - Perform known vehicle plates against a database
[3] Reset Target - Reset the phone to a new target address
[4] Back: back to the main menu
[!] Please select a number to continue: 

Now let's select number 2 for "Plate Search". After that it will ask you for the license plate, so enter that right now.

  [!] Select a number to continue: 2
[?] What is the number of the target? [ex: (XYZ123|0U812)]: 5FZXXXX 

After entering that, you will be asked for the abbreviation of the number plate.

  [?] FaxVin
[!] Enter a 2 letter abbreviation, for example: (AL = Alabama | CO = Colorado) CA
[X] No results found ... 

If all went well, you should see results. If you see the warning & # 39; No results & # 39; get like I did, press Enter to continue and select number 1 for & # 39; Everything & # 39 ;. It's for all modules associated with the email module group, which doesn't make sense, I know, but it works. Then enter the state ID again.

  [!] ScreenName Search Menu: Target Info - 5FZXXXX
[1] All: Run all modules associated with the email module group
[2] Plate Search - Perform known vehicle plates against a database
[3] Reset Target - Reset the phone to a new target address
[4] Back: back to the main menu
[!] Select a number to continue: 1

[?] FaxVin
[!] Enter a 2 letter abbreviation, for example: (AL = Alabama | CO = Colorado) CA

[+] Plate: 5FZXXXX
[+] State: CA
[+] VIN: WDBUF70JX4A4XXXXX
[+] Brand: Mercedes-Benz
[+] Model: E-Class
[+] Year: 2004
[+] Trimming: E500
[+] Style: SEDAN 4-DR
[+] Engine: 5.0L V8 SOHC 24V
[+] Factory: Sindelfingen, Germany
[+] Age: 16 years

Now press the & # 39; ENTER & # 39; button to continue 

From that we got some information about the vehicle. We started with just the registration number, but now we have the VIN of the car, with which we can request all kinds of other information. That data may include when they are registered and with whom they are registered. If you're an OSINT researcher, you know that the more clues you can get about a specific goal, the easier it will be to connect it to other sources and learn more little by little.

If you are looking for other information, there are other useful modules in Skiptracer. For example, if you have a specific screen name you're looking for, it's easy to use the Screen Name module and run it against "All". It will do the job for you, looking for accounts online that use that screen name. So if you need to do a quick profile on someone, or if you have a license plate to scan, one of these modules will work just fine.

Skiptracer is not a complete solution for an OSINT investigation, but it is a great way to quickly collect clues, provided Python 2 is installed on your system. If you need more help with Skiptracer, click the comments below or ask on Twitter @NullByte .

Don't Miss: How to Detect Social Media Accounts by Usernames Using Sherlock

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