Twitter is one of the most popular social media platforms, where millions of users share their opinions, thoughts, and news every day. But not all tweets are genuine. Some of them are generated by bots, which are automated accounts that perform certain tasks on Twitter. Bots can be used for various purposes, such as spreading misinformation, influencing public opinion, promoting products or services, or simply having fun.
In this article, we will show you how to create your own Twitter botnet, a tool that allows you to create a network of autonomous bots that reply to tweets with text generated based on probabilities in Markov chains. A Markov chain is a mathematical model that describes how a system changes from one state to another based on certain rules. For example, if you have a text composed of words, you can use a Markov chain to generate new sentences by choosing the next word based on the previous word.
Flock-Botnet is an open-source project created by arnaucode, which you can find on GitHub. It is written in Go language and uses the Twitter API to stream and post tweets. You can configure your botnet with different keywords, languages, and reply rates. You can also manually tweet from any bot in your flock using a command-line interface.
In this guide, we will explain how to set up Flock-Botnet GitHub on your computer and how to create and run your own Twitter botnet.
Before you start creating your Twitter botnet with Flock-Botnet, you need to have some prerequisites:
- A computer with Windows, Linux or Mac OS
- Go language installed (you can download it from https://golang.org/dl/)
- Git installed (you can download it from https://git-scm.com/downloads)
- A Twitter developer account (you can apply for one at https://developer.twitter.com/en/apply-for-access)
- A set of API keys and tokens for each bot you want to create (you can generate them at https://developer.twitter.com/en/portal/projects-and-apps)
Step 1: Downloading Flock-Botnet
The first step is to download Flock-Botnet from its repository on GitHub. To do this, open a terminal window and type:
git clone https://github.com/arnaucube/flock-botnet.git
This will create a folder called flock-botnet in your current directory. Enter this folder by typing:
Step 2: Configuring Flock-Botnet
The next step is to configure Flock-Botnet according to your preferences and needs. To do this, open the file called flock.go with any text editor and edit the following variables:
flockSize: This is the number of bots you want in your botnet. You need to have as many API keys and tokens as bots.
keywords: This is an array of strings that contains the keywords you want your bots to stream and reply to. You can use any words or phrases related to your topic or niche.
languages: This is an array of strings that contains the languages you want your bots to stream and reply to. You can use any ISO 639-1 codes (for example: “en” for English or “es” for Spanish).
replyRate: This is an integer that represents the percentage of tweets that your bots will reply to. For example: if you set it to 10%, then each bot will reply only 10% of the streamed tweets.
markovOrder: This is an integer that represents the order of the Markov chain used for generating replies. The higher the order, the more coherent but less original the replies will be.
You also need to edit each element in the array called
bots, which contains information about each bot in your flock:
name: This is a string that represents the name or handle of your bot (for example: “@bot123”).
accessTokenSecret: These are strings that represent the API keys and tokens for each bot. You need to
Step 3: Building Flock-Botnet
The next step is to build Flock-Botnet from the source code. To do this, open a terminal window and type:
This will create an executable file called flock-botnet in your current directory.
Step 4: Running Flock-Botnet GitHub
The final step is to run Flock-Botnet GitHub and start your Twitter botnet. To do this, open a terminal window and type:
This will start streaming tweets that match your keywords and languages and reply to them with text generated by Markov chains. You can see the output of each bot on the terminal window.
You can also manually tweet from any bot in your flock using a command-line interface. To do this, open another terminal window and type:
This will prompt you to enter the name of the bot you want to tweet from and the text of the tweet. For example:
Enter name of bot: @bot123 Enter text for tweet: Hello world!
This will post a tweet from @bot123 saying “Hello world!”.
In this article, we have shown you how to create your own Twitter botnet using Flock-Botnet GitHub, a tool that allows you to create a network of autonomous bots that reply to tweets with text generated based on probabilities in Markov chains. We have explained how to download, configure, build and run Flock-Botnet on your computer and how to manually tweet from any bot in your flock.
We hope you have enjoyed this guide and learned something new. If you have any questions or feedback, feel free to leave a comment below.
Q: What are the benefits of creating a Twitter botnet?
A: Creating a Twitter botnet can have various benefits depending on your goals and intentions. For example, you can use it for:
- Experimenting with natural language generation and Markov chains
- Having fun with random replies and interactions
- Testing the limits of Twitter’s policies and detection systems
- Creating fake followers or engagement for yourself or others
- Spreading awareness or information about a topic or cause
Q: What are the risks of creating a Twitter botnet?
A: Creating a Twitter botnet can also have various risks depending on how you use it and what consequences it may have. For example, you may face:
- Legal issues if you violate Twitter’s terms of service or other laws or regulations
- Ethical issues if you deceive or harm other users or entities with your bots
- Technical issues if your bots malfunction or get hacked by others
- Social issues if your bots annoy or offend other users or communities
Q: How can I avoid getting detected or banned by Twitter?
A: There is no definitive answer to this question as Twitter’s algorithms and policies may change over time and vary depending on different factors. However, some general tips that may help you avoid getting detected or banned by Twitter are:
- Use different IP addresses for each bot (you can use proxies or VPNs)
- Use different API keys and tokens for each bot (you can create multiple developer accounts)
- Use realistic names, bios, profile pictures, etc. for each bot (you can use online generators)
- Use different keywords, languages, reply rates etc. for each bot (you can use randomization)
- Limit the number of tweets per day per bot (you can use timers)