This was an experimental project I did a while back for a client. His goal was to find out whether having many social media followers (specifically Twitter) could make him seem famous. I wrote these scripts to authenticate to users he bought from God knows where, and to make those users interact among themselves and with the client's account. It has everything from bypassing CAPTCHA, to simulating organic growth. Most of the functionality goes against Twitter TOS and even though I never used the script myself, I regret building the tools for someone to break rules, regardless of their intentions. sike. I'm making this public for anyone who wants to learn from this, but please don't abuse Twitter. sike.
When setting up the app on a server, the project root dir MUST be located in /home. Cron jobs will attempt to look for files from that dir.
Add this cron job
`*/10 * * * * python /home/mass-twitter-outh/scripts/schedule_engagement.py`
Create an app with read and write permissions here.
To bypass reCAPTCHA V2, we'll need a recaptcha solve service. Create an account with anticaptcha.com and recharge your account.
1: Take note of your api key.
2: To keep the expenses practical, set your maximum bid to $3 for every 1000 captchas. The codebase has been designed to tolerate lower bid rates by waiting for workers to be idle.
1: Get authentication token and user id by running the command below.
python smartproxy.py gettoken
This requires the presence of the 'PROXY_USERNAME' and 'PROXY_PASSWORD' env variables. Store the results in the 'PROXY_USER_ID' and 'PROXY_TOKEN' env variables.
2: Whitelist your IP address by running the command below, replacing the sample IP address with yours. You may have to overwrite existing IP addresses if you have reached your cap.
python smartproxy.py whitelist '192.168.0.1'
This file contains the account(s) that the authenticated accounts will engage with ie the accounts that will be followed, get their tweets liked, responded to, retweeted etc. Use this sample to configure the file;
{
{
"username": {
"initialFollowers: 77"
"growthInterval": 7,
"growthRate": 0.01,
},
}
In the above example, the user's followers will increase by 1% every 7 days.
After editing the file, you will need to run this command to set up a growth scheduler for the account.
python schedule_following.py --setup-scheduler
The command will set up a cron job for each account in the file, that will run every growthInterval days. If some accounts already have cron jobs, they will be overwritten.
Store the tweets you want the accounts to publish here. A tweet and an account that publishes it will be selected at random.
Store the responses to tweets you want your accounts to send.
Add environment variables, using ".env.sample" as your guide.
In order to simulate realistic growth, twitter following is not ranomized. Instead, it's guided by a mathematical equation.
f(x) = a(1+r)x
Where a is the initial number of followers, r is the percentage in growth expressed as float, and x the growth factor in days. The growth rate will be limited to a very small number, for instance 0.01. In this case, it means that the follower count for the user would increase by 1% every x days.
To keep things even more realistic, a calculated number of unfollowers will be implemented.
This file stores all the accounts, with their login credentials.
This file has no default. It will be created by running prepare_accounts.py. You can also add the accounts manually to the json file following this format;
{
{
"username1": {
"email": "someemail@email.com",
"password": "somepassword",
"followers": "17",
"created": "2012",
"country": "Australia",
"two_factor": 0
},
"username2": {
"email": "someemail@email.com",
"password": "somepassword",
"followers": "0",
"created": "2017",
"country": "Kenya",
"two_factor": 0
}
.
.
.
}
This file has all the accounts whose authentication with the app was completed.
Defaults to empty json.
This file will store the accounts that failed to authenticate with the app, and therefore cannot be accessed.
Defaults to empty json.
To authenticate accounts, run; python mass_oauth.py. This will attempt authentication for accounts defined in all_accounts.json, but not present in authenticated_accounts.json
By default, the script attempts to log in with email. If you want to switch to username login, run;
python mass_oauth.py --username-login
You can pass a command line argument to also re-attempt authentication for the accounts that had previously failed;
python mass_oauth.py --retry-failed
A cron job will run every 10 minutes to check for new activity. The last_tweets.json file stores the last tweets sent by each user in the 'make_me_feel_famous.json' file.
Note: We could use the streaming API to monitor activity in realtime. However, it's not the best approach in this use case for many reasons that won't be discussed in this README.
If there's a new tweet, it is assigned a random number of likes and retweets, between 1 and 1000. Random accounts are then selected and cron jobs added for them to like and retweet the tweet for the next 5 days.
Note: A better algorithm will be written to calculate metrics and engage with tweets, according to the following the specified account has.
All scripts that need to be run at specific times are run from cron jobs.
The format for each cronjob is cron-job # comment. For example, this cron job is for following an account;
python scripts/engagement.py --follow-account cl1973 TaraHer77162822 # cl1973_TaraHer77162822
After running the scheduled tasks, the cron job is deleted.
1: "This version of ChromDriver only supports chrome version xx"
You need to download a chromedriver version that matches your chrome browser and store it in the drivers directory.