This botnet consists of 99 accounts created between 2010 and 2015 (mostly 2013). All have some variant of "p o r n" as their display name, and all were mostly dormant until mid-April 2021.
This pornbot network tweets prolifically via TweetDeck (223566 tweets from 99 accounts over the span of just two weeks). The majority of the accounts tweet round-the-clock, with some ceasing operation after a few hours or days of activity.
Is this botnet using TweetDeck's scheduling feature to accomplish its 24/7 presence? Almost all scheduled TweetDeck tweets are posted within the first second of the minute for which they are scheduled, which isn't true of this botnet's tweets.
The botnet's tweets do have a timing anomaly, however. It began by posting its tweets shortly before the start of each minute, but it is slowly falling behind: on 4/20, it was tweeting ~10 seconds into each minute, and today (4/25) it is tweeting ~23 seconds into each minute.
What would explain this behavior? A likely explanation is that the botnet operators wrote their own scheduling software that fails to account for some form of latency, and thus slowly falls behind schedule when run for a long period of time.
What does this botnet actually tweet? The tweets are extremely repetitive and consist of single words such as "XXX" or "video" followed by four tags of one of two porn accounts (@/porn_sex_linkkk and @/sex_porn_linkk), followed by a random number.
The two tagged porn accounts in turn have what appear to be blogspot links that actually redirect to endless signup pages for an obscure "dating site" in multiple languages. The site is likely unsafe and we recommend neither visiting it nor providing it any information.
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None of these chefs exist, as they're all AI-generated images. This hasn't stopped them from racking up lots of engagement on Facebook by posting AI-generated images of food (and occasional thoughts and prayers), however.
cc: @ZellaQuixote
These "chefs" are part of a network of 18 Facebook pages with names like "Cook Fastly" and "Emily Recipes" that continually post AI-generated images of food. While many of these pages claim to be US-based, they are have admins in Morocco per Facebook's Page Transparency feature.
Between them, these 18 Facebook "chef" pages have posted AI-generated images of food at least 36,000 times in the last five months. Not all of the images are unique; many have been posted repeatedly, sometimes by more than one of the alleged chefs.
Can simple text generation bots keep sophisticated LLM chatbots like ChatGPT engaged indefinitely? The answer is yes, which has some potentially interesting implications for distinguishing between conversational chatbots and humans.
For this experiment, four simple chatbots were created:
• a bot that asks the same question over and over
• a bot that replies with random fragments of a work of fiction
• a bot that asks randomly generated questions
• a bot that repeatedly asks "what do you mean by <X>?"
The output of these chatbots was used as input to an LLM chatbot based on the 8B version of the Llama 3.1 model. Three of the four bots were successful at engaging the LLM chatbot in a 1000-message exchange; the only one that failed was the repetitive question bot.
The spammers behind the "Barndominium Gallery" Facebook page have branched out into AI-generated video and started a YouTube channel with the catchy name "AY CUSTOM HOME". The results are just about as craptastic as you'd expect.
In this synthetically generated aerial video of a (nonexistent) barndominium under construction, the geometry of the roof changes, a blue building appears, and a tree vanishes, all in the course of just three seconds.
This AI-generated barndominium features a long AI-generated porch with some chairs on it. Exactly how many chairs there are depends on what angle you look at it from, however, as the chair on the left splits into three chairs as the camera pans.
Some observations regarding @Botted_Likes (permanent ID 1459592225952649221)...
First, "viral posts which don't result in follower growth and have very little engagement in the reply section" is not a useful heuristic for detecting botted likes. Why not?
cc: @ZellaQuixote
"Viral posts that do not result in follower growth" is not a valid test for botting, because posts from large accounts often go viral among the large account's existing followers but do not reach other audiences, resulting in high like/repost counts but little/no follower growth.
"Very little engagement in the reply section" doesn't work for multiple reasons (some topics spur debate and some don't, some people restrict replies, etc)
Hilariously, @Botted_Likes seems to be ignoring their own criteria, as many of the posts they feature have tons of replies.
As with the banned @emywinst account, the @kamala_wins47 account farms engagement by reposting other people's videos, accompanied by bogus claims that the videos have been deleted from Twitter. These video posts frequently garner massive view counts.
@Emywinst @kamala_wins47 The operator of the @kamala_wins47 account generally follows up these viral video posts with one or more replies advertising T-shirts sold on bestusatee(dot)com. This strategy is identical to that used by the banned @emywinst account.
What's up with all these similarly-worded enthusiastic posts about a Pierre Poilievre rally in Kirkland Lake, and are they all from accounts that are less than a month old? (Spoiler: yes, they are.) #Spamtastic
cc: @ZellaQuixote
An X search for "Pierre Poilievre", "Kirkland Lake", and "refreshing" performed on August 4th, 2024 turned up 151 posts from 151 accounts. All are new accounts, with the oldest having been created less than a month ago, on July 7th, 2024. (Some have since been suspended by X.)
The most intense period of activity for this group of accounts was on August 3rd, 2024, when the repetitive posts about the Poilievre rally were posted. Each account also has at least one earlier post on a random topic; some of these older posts seem to cut off abruptly.