Ever since the commercialization of the Internet, spammers, and cyber crooks use various techniques, including pornbots, to disseminate spam messages and commit fraud. Pornbots are computer programs which send automatic messages purported to come from users shown on pornographic photos. For example, an automatic message sent by a pornbot may read as follows: “Hi, if you would like to see more photos of me, please click on this link.” The purpose of such messages is to engage in a conversation with a potential victim and persuade him/her to click on malicious links.
Most current pornbots perform rather simple operations and can rarely mislead an Internet user into believing that the messages are sent by the person on the pornographic photos. However, with the developments in the field of artificial intelligence, we can expect that pornbots will soon be able to engage in realistic conversations with their chat partners. In this regard, Matthew Brophy writes in his book “Porn – Philosophy for Everyone: How to Think with Kink” “Pornbots” are the sexual Barbies of the future – virtual reality prostitutes run by artificial intelligence (not that they will need much intelligence).”
This article describes how pornbots work (Section 2). Next, it discusses pornbots utilizing three software applications, namely, Kick, Tinder, and Snapchat (Section 3). Afterward, we warn about the threats of pornbots (Section 4) and provide recommendations on how to avoid pornbots (Section 5). Finally, a conclusion is drawn (Section 6).
How do pornbots work?
Pornbots usually take the form of accounts in instant messaging applications. Pornbots can be divided into two categories, namely, active pornbots and passive pornbots. Active pornbots automatically contact other users and send them messages. Passive pornbots start sending messages only when a user initiates a conversation. Active pornbots quickly raise users’ suspicions because of their overly aggressive communication style. In contrast, passive pornbots may be programmed in such a way as to respond slowly to messages and provide answers which may mislead their interlocutors into believing that they are chatting with a real person.
Below, we present a typical conversation between a user of a social network and an active pornbot.
Hello, Nice to meet you, I’m Janet.
The main strategy used by pornbots to mislead their chat partners is basing their responses on certain keywords. As it can be seen from the example above, Janet replies
“Oh, I love it when you say “no”” to a message starting with the word “no.” Furthermore, it replies “It’s me Janet” to a message containing the words “are you.”
While presently most pornbots try to trick humans into falsely believing that they are communicating with real persons rather than computer systems, the advancements in the field of artificial intelligence may lead to the creation of pornbots which openly admit being bots, but aim to satisfy the communication needs of their chat partners. By way of illustration, inventions similar to the artificial intelligence software “Max” can be deployed in online communication platforms and serve as pornbots. Max, software developed by the University of Bielefeld, can process and respond to visual and acoustic input. By the input information, Max can show mimics and gestures, including mimicking eye-movement behavior. Taking into account technological developments like Max, we may soon witness virtual reality pornbots. This does not mean that the current versions of pornbots will not be used in the future.
Simple pornbots can be used by hackers for hacking social network accounts. For example, the hacking group “Anonymous” used pornbots to hack twitter accounts of a terrorist organization. More specifically, hundreds of pornbots followed the twitter accounts with the aim to discredit the terrorist organization. The pornbots did not send any messages and, therefore, were not deleted as spam bots. The pornbot attack was a direct response to the recent terrorist attacks in Brussels, Belgium.
Pornbots in Kik, Tinder, and Snapchat
Pornbots are mostly used for illegitimate purposes, such as committing identity theft and stealing credit card numbers. Due to their widespread character, pornbots generate a vast amount of traffic in messaging, dating, and social networking applications. Below, we examine pornbots utilizing Kik (Section 3.1), Tinder (Section 3.2), and Snapchat (Section 3.3).
Pornbots in Kik
Kik (www.kik.com), an instant messenger app for mobile devices, attracts a large number of pornbots. Research studies show that pornbots make up around 1% of all messages exchanged through the app. Usually, pornbots ask Kik’s users to visit websites to see pornographic photos. As soon as the users visit the websites, they are asked to insert credit card numbers to verify their age. The collected credit card data is transferred to fraudsters who may further process it for malicious purposes.
Pornbots in Tinder
The pornbots in Tinder (www.gotinder.com), a location-based dating and social service application, reached a high level of sophistication. They mimic a regular conversation on a dating site with the aim to get the phone numbers of the deceived individuals. Having realized that the use of Playboy-style profile pictures immediately raises identity concerns, the developers of pornbots in Tinder usually use girl-next-door-style pictures that contain subtle erotic content. Moreover, some of the pornbots deployed in Tinder reply slowly because an immediate response is usually associated with Internet bots. In this regard, Satnam Narang, a senior security response manager at Symantec, stated: “Clearly these actors are finding new ways to modify their scripts, changing how quickly they respond to messages. It won’t happen for about 50 minutes, 45 minutes, then [you’ll] get the message.”
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Pornbots in Snapchat
The pornbot scammers also target Snapchat (www.snapchat.com), a rapidly growing image messaging and mobile multimedia application. On Snapchat, pornbots are programmed not to send a graphic porn image immediately to their users. Instead, pornbots send friend requests and, if the users accept them, the pornbots will ask the users to download a mobile application which may be malicious software. In 2013, Snapchat was targeted by a pornbot called Honey Crush 9. It automatically contacted Snapchat users and requested them to add it on Skype. Once added in Skype, Honey Crush 9 sent malicious links, spam, or made automated phone calls spreading fake anti-virus warnings.
The threats of pornbots
Pornbots may have a serious impact on individuals and organizations. Some of the negative consequences associated with pornbots are listed below.
(i) Pornbots may send automatic short messages to premium phone numbers. The victim will not realize the fraud until he/she receives the phone bill.
(ii) Pornbots may install malicious software which collects information about the victim. According to Richard Henderson, a security expert, “These bots can send the entire phone book, the contents of your text messages, and anything you type in.”
(iii) Pornbots may replace legitimate ads with phishing ads. When the user clicks on the phishing ads, he/she will be requested to insert his/her personal data. The scammers usually use the collected information for illegitimate purposes.
(iv) Pornbots send spam messages. As known, spam consumes Internet resources, reduces the effectiveness of legitimate advertising, increases the costs of the access to the Internet, exposes children to adult material, and wastes the time of Internet users.
Recommendations on how to avoid pornbots
To avoid a pornbot, one needs to identify it as such. This can be done by using the Turing test, a test measuring machine’s ability to exhibit intelligent behavior. The test was developed by Alan Turing in 1950. Turing stated that, if a machine convinces a human that he/she chats with a machine 70% of the time after five minutes of conversation, the machine has intelligence similar to the human intelligence. In the context of pornbots, the evaluator needs to chat with a pornbot for 5 minutes to understand whether he/she communicates with a machine. Chatting for a period of 20-30 seconds may not be sufficient time for identifying a pornbot.
After the pornbot is identified, the next step should be the deletion of the pornbot from the list of contacts and contacting the administrator of the website in which the pornbot lures its victims. Most websites have strict policies prohibiting the use of bots. For instance, Section 3(2) of Facebook’s Statement of Rights and Responsibility states: “You will not collect users’ content or information, or otherwise access Facebook, using automated means (such as harvesting bots, robots, spiders, or scrapers) without our prior permission.”
Under masks of attractive ladies, pornbots generate a large portion of online traffic and lure daily thousands of individuals and organizations. Pornbot’s victims can be users of dating websites, instant messaging platforms, social networks, and other popular software applications. The failure to identify a pornbot may result in identity theft and other types of fraud. A simple test created by Alan Turing in 1950 may be all that is necessary to identify and ignore a pornbot. The test is not complex. All that is needed is a five minutes conversation with the suspected pornbot.
Allhoff, F., Ponante, G., ‘Porn-Philosophy for Everyone: How to Think With Kink‘, Wiley-Blackwell, Vol. 30, 2011.
Butterfill, S. et. al., ‘Collective Agency and Cooperation in Natural and Artificial Systems’, International Conference at the University of Stuttgart, 2013.
Facebook’s Statement of Rights and Responsibilities, 30 January 2015. Available at https://www.facebook.com/legal/terms .
Geer, D. ‘Bad bots on the rise: A look at mobile, social, porn, and spam bots’, CSO Online, 30 April 2014. Available at http://www.csoonline.com/article/2149570/mobile-security/bad-bots-on-the-rise–a-look-at-mobile–social–porn–and-spam-bots.html .
‘Hackers enlisting ‘pornbots’ to fight ISIS and their supporters on Twitter’, FoxNews, 7 June 2016. Available at http://www.foxnews.com/world/2016/06/07/hackers-enlisting-pornbots-to-fight-isis-and-their-supporters-on-twitter.html .
Kopp, S. ‘Max and the Articulated Communicator Engine’, Bielefeld University, 20 August 2008. Available at https://www.techfak.uni-bielefeld.de/~skopp/max.html .
Melendez, S., ‘Tinder Bots Have Evolved to Mimic the Girl Next Door’, Motherboard, 10 February 2015. Available at http://motherboard.vice.com/read/tinder-bots-next-door .
‘Mobile Web Intelligence Report: Q1 2016’, Device Atlas, 12 May 2016. Available at https://deviceatlas.com/blog/download-new-mobile-web-intelligence-report-q1-2016 .
Narang, S. ‘Hacked Twitter accounts are posting links to adult dating and sex personals’, Symantec, 23 May 2016. Available at http://www.symantec.com/connect/blogs/hacked-twitter-accounts-are-posting-links-adult-dating-and-sex-personals .
Narang, S. ‘Spamchat: Snapchat Users Subjected to Porn and Secret Admirer Spam’, Symantec, 3 December 2013. Available at http://www.symantec.com/connect/blogs/spamchat-snapchat-users-subjected-porn-and-secret-admirer-spam .
Newton, J., ‘Hackers bombard ISIS Twitter accounts with thousands of graphic sexual images using ‘pornbots’, Daily Mail, 7 June 2016. Available at http://www.ibtimes.co.uk/hackers-attack-isis-supporters-thousands-graphic-pornbots-sex-images-1564187 .
Olson, P., ‘Who’s Behind The Porn Bots On Kik?’, Forbes, 20 August 2014. Available at http://www.forbes.com/sites/parmyolson/2014/08/20/kik-porn-bot-spammers/ .
Segall, L. ‘Snapchat’s porn bot problem’, CNN Money, 16 January 2014. Available at http://money.cnn.com/2014/01/16/technology/social/snapchat-spam-porn/index.html .
‘Snapchat sexting spam – how to stop messages from Honey Crush 9 and her friends’, Naked Security, 18 April 2013. Available at https://nakedsecurity.sophos.com/2013/04/18/snapchat-sexting-spam-honey-crush/ .
Watkinson, ‘Hackers target Isis supporters with thousands of graphic ‘Pornbots’ sex images’, International Business Times, 7 June 2016. Available at http://www.ibtimes.co.uk/hackers-attack-isis-supporters-thousands-graphic-pornbots-sex-images-1564187 .
Rasa Juzenaite works as a project manager in an IT legal consultancy firm in Belgium. She has a Master degree in cultural studies with a focus on digital humanities, social media, and digitization. She is interested in the cultural aspects of the current digital environment.