Massive Bot Reporting is becoming a concern for social platforms such as Twitter, Facebook, Instagram, Tinder, LinkedIn…. Also known as bots at the service of hacktivism or Massive Bot Reporting, Weaponized Social Media Bots, Hackti-banning, or computational propaganda, these are essentially social bots that report social media accounts en masse.

It is usually detected when a message arrives at your account without prior notice, such as: “Caution: This account is temporarily restricted. You are seeing this warning because unusual activity was detected on this account. Do you still want to view it?“

The Bad Bot Report by Imperva Research Labs analyzes the latest data on the use and impact of malicious bots in the digital environment.

Below are some of the most representative data points:

• 24.1% of website traffic was generated by malicious bots during 2019.
• 46% of malicious bots originate from the United States.
• 21% of blocks by these attacks are located in Russia, followed by China and Romania.
• 55% of global traffic takes place on Google Chrome.
• The industries most affected by malicious bots are, in this order: the financial sector (with 47.7% of its users being malicious bots), education, services and telecommunications, marketplaces, and government agencies, followed by many others.

Last week we discussed this topic with Daniel Chalmeta, our Entertainment Partner Manager at Facebook. We are very grateful for the support he provides us. His role is key in leading entertainment efforts for Facebook and Instagram in Spain and Portugal. We discussed the growing concern for our clients, as many of the public figures we represent and protect through our CELEBRANDSEC service are being affected by Massive Bot Reporting. we anticipate this situation will continue to grow, and we are concerned about how social platforms will react to this hacktivism practice.

What is Massive Bot Reporting or bots at the service of hacktivism?

A social bot, socialbot, or socbot is a social robot that communicates automatically on social media platforms to interfere with service, block communication between users, or shift the focus of other users. They are not the same as chatbots, but they are related; both waste the time of organizations, social media teams, and others.

Both uses automatically distribute actions on social networks; both are programmed by humans and are sometimes driven by activist groups. Previously, they were used primarily to defend or support campaigns, generating automated activities to grow the user community and increase followers.

We saw the use of this technology when it was at its peak. In the 2016 United States elections, it was estimated that between 9% and 15% of Twitter accounts could be social bots. 15% of the total Twitter population involved in the U.S. presidential election discussion were bots. Approximately 400,000 were responsible for about 3.8 million tweets, roughly 19% of the total volume.

Some well-known robots include Twitterbots, but autonomous users are also detected on Facebook, Tinder, LinkedIn, and other networks like Instagram. Today, their accounts have generated behaviors that are technologically so similar to those of human accounts that they are able to go unnoticed by social platforms.

Is it legal?

No, and it is clearly stated in the terms of service of social platforms like Twitter, Instagram, Facebook, LinkedIn, or Tinder. When automation is mixed and social media APIs can be accessed, the task becomes more complicated.

How does it work?

There are two main ways to do it: 1) Semi-manual or semi-automated Massive Bot Reporting and 2) Automated Massive Bot Reporting via prior programming.

1. Semi-manual or semi-automated

• The activist group organizes remotely via a Telegram channel or a closed group on any platform, such as the old Titanpad or Google Groups, to choose their target and schedule the sequence of block reports.

• How they do it:
  • Each person has a list of social accounts from fake profiles to log in and report in a semi-automated manner.
  • This takes much more time and is less efficient, unless it is done in a highly organized way by a group of people so large that the platform concludes the target account must indeed be banned after being reported by so many social profiles.

2. Automated via prior programming, Massive Bot Reporting

The benefit is that it saves much more time and allows the attack to be mass-produced.

• How they do it:
  • The bot automatically sets up accounts on a social media platform.
  • The bot account may also look like that of a real person (both technically and to the social platform; sometimes they are previously hacked accounts stolen from real users), with personal data and even family photos.
  • The bot crawls site content, looking for the target account and comments of interest to be banned or reported.
  • The bot reports the account or content to trigger a blocking reaction from the platform.
  • Botnets act in concert to promote the blocking of a profile or message.

What are they used for?

One might wonder why this is done; well, it can be done for hacktivism, to muddy the debate taking place on that platform, or to disrupt support for an opponent (we see this often in political campaigns).

1. Generating fame for a user, an idea, a product, a service, or a country: having a certain number of bots as fake followers helps simulate real success, and this number of followers encourages the belief that the person may be of interest, generating trust and social impact.
2. Silencing, Reporting, Blocking, Reporting for hacktivism: Mass reporting an opponent to discredit them in the eyes of their community and thus prevent their message from reaching its potential audience.
3. Biasing public opinion: generating such an influence on opinion trends.
4. Limiting freedom of expression: if many messages are generated on a certain topic from hundreds, thousands, or millions of profiles, the opponent’s messages can disappear from the timeline view under an avalanche of automated messages.

How to avoid it?

It cannot be avoided by human means alone. It can only be prevented through the detection of this behavior by the artificial intelligence applications of the social platforms themselves. However, they are constantly refining how they do it. In Latin America and the United States, it began to trend in 2016, but it quickly spread to Europe, Russia, and the Middle East.

For now, the bad guys are winning, but we know that the Red Teams of the various platforms are working hard on it.

One more reason to protect your social media account

As we mentioned in the interview with Selva Orejón conducted by Cayetana Guillén Cuervo, where do our compromised or hacked accounts end up? Well, we have just explained one of their uses.

Selva explained the price of different hacked accounts; the higher the number of followers or if it is a verified account, the greater the impact it generates on the ban, report, or block within the social network.

So the next time someone wonders why they want my account, why my account has been hacked, or what is done with compromised accounts on Twitter, Facebook, Instagram, Tinder, or LinkedIn, here is one more reason.

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