sound-cloudripper

a tool whichs basically finds private soundcloud tracks by bruteforcing shareable links of on.soundcloud.com

Shareable soundcloud links are shrinked links, who look like this :
=> on.soundcloud.com/XXXXX => code 302 :redirect => soundcloud.com/artist/track),
and this can redirect to public tracks as well as private ones too... bruteforce time.

the script catchs the redirect, and uses a regex to find if the full link contains a private token (public ones does not have any)
and if the regex matches, then a private track has been found.

actually, because of the regex-only filter theres some false-positives:
-old private tracks who kept their same shareable link, which are public now, will stiff have a private token on the link;
-sometimes deleted tracks does match.

this is easy to fix tho, i just need to do it :')

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Educationnal purposes only, use it at your own risk.

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Dependencies

use pip install -r requirements.txt to fulfill these

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CLI Arguments

• -h | print out the possible commands

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• -r | base number of requests
• -t | number of simultaneous threads (multiplies the number of requests)

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• -x | exports the positive results in a xml file (output.xml), and updates it if it already exists.
• -j | exports the positive results in a json file (output.json), and updates it if it already exists.
• -e | appends the positive results in a txt file (output.txt)

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• -v | prompts positive results in real time
• -vv | prompts positive and negative results in real time

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• -c | specify the soundcloud client id to ignore public/deleted tracks

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Usage

you can run the script without any arguments, the default values are enough for testing (25 requests, 1 thread, verbose mode).

Features

• Keep a track record of what has been already scanned. It will skip any repeated links (you can delete the checked.sqlite3 to restart scanning from beginning)
• JSON and XML file output containing full links grouped by artist
• CTRL+C in middle of a run saves everything that has been checked
• Retry 5 times if error occurs, then skip is still failing
• rate limit management by sleeping for given ranges of time (30 s, 1 min, 15 min, 30 min and 1 hour)

Example usage with arguments

python3 ripper.py -r 5 -t 5 -x
(run cloudripper for 25(5*5) requests, and export positive results in xml)

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why python ?

why not (i have regrets)