1.9 KiB
projectFlock
a twitter botnet with bots replying tweets with text generated by Markov chains
generating text with Markov chains
The algorithm calculates the probabilities of Markov chains, analyzing a considerable amount of text, for the examples, I've done it with the book "The Critique of Pure Reason", by Immanuel Kant (http://www.gutenberg.org/cache/epub/4280/pg4280.txt).
Replying tweets with Markov chains
When the botnet is up working, the bots start streaming all the twitter new tweets containing the configured keywords. Each bot takes a tweet, analyzes the containing words, and generates a reply using the Markov chains previously calculated, and posts the tweet as reply.
In the following examples, the bots ("andreimarkov", "dodecahedron", "projectNSA") are replying some people.
configuration file example (flockConfig.json):
[{
"title": "account1",
"consumer_key": "xxxxxxxxxxxxx",
"consumer_secret": "xxxxxxxxxxxxx",
"access_token_key": "xxxxxxxxxxxxx",
"access_token_secret": "xxxxxxxxxxxxx"
},
{
"title": "account2",
"consumer_key": "xxxxxxxxxxxxx",
"consumer_secret": "xxxxxxxxxxxxx",
"access_token_key": "xxxxxxxxxxxxx",
"access_token_secret": "xxxxxxxxxxxxx"
},
{
"title": "account3",
"consumer_key": "xxxxxxxxxxxxx",
"consumer_secret": "xxxxxxxxxxxxx",
"access_token_key": "xxxxxxxxxxxxx",
"access_token_secret": "xxxxxxxxxxxxx"
}
]