Building a bot army to target audiences in the US or UK costs just pennies per account, whilst prices on encrypted messaging apps surge globally ahead of national elections.
A new real-time tracking tool launched by the University of Cambridge has exposed the “online manipulation economy” for the first time, revealing that verifying fake accounts in major Western democracies is almost as inexpensive as in Russia.
The Cambridge Online Trust and Safety Index (COTSI) monitors daily fluctuations in SMS verification costs across more than 500 online platforms in every country.
While the average price of verifying a fake account was $4.93 in Japan and $3.24 in Australia, due to strict regulations, the cost plummeted to $0.26 in the US and $0.10 in the UK — comparable to the $0.08 average in Russia.
The index highlights a “thriving underground market” where vendors bulk-purchase SIM cards — both real and virtual — to bypass the SMS security checks used by platforms like TikTok, Amazon, and Spotify.
Bad actors
Researchers found that this “grey market” infrastructure allows bad actors to mass-produce fake profiles for everything from vanity metric boosting to coordinated political influence campaigns.
“All this activity requires fake accounts, and each one starts with a phone number and the SIM hardware to support it,” said Dr Jon Roozenbeek, the study’s co-lead author. “That dependency creates a choke point we can target to gauge the hidden economics of online manipulation.”
The study identified a distinct pattern of price surges tied to political instability. In the 30 days preceding the 61 national elections analysed, the cost of fake accounts on Telegram and WhatsApp increased by 12 per cent and 15 per cent, respectively.
Researchers explain that because these apps link accounts to visible phone numbers, influence operators must register fake accounts in the target country, thereby increasing local demand.
In contrast, platforms like Facebook and Instagram showed no such price correlation with elections.
“A fake Facebook account registered in Russia can post about the US elections and most users will be none the wiser,” said Roozenbeek. “This isn’t true of apps like Telegram and WhatsApp.”
Consequently, fake accounts on these encrypted platforms remain consistently expensive, averaging $1.02 for WhatsApp and $0.89 for Telegram globally.
The study reveals that some of the world’s largest platforms have the lowest verification costs, likely due to the large supply of SIMs targeting them.
- Cheapest: Meta, Grindr and Shopify (global average ~$0.08)
- Mid-range: X and Instagram (~$0.10), TikTok and LinkedIn (~$0.11)
- Slightly higher: Amazon (~$0.12)
Vendors often recoup their hardware costs by selling high-demand verifications for major apps, then profit from the “long tail” of hundreds of other services, including dating apps, gaming platforms like Steam and even ride-hailing services like Uber.
To test the market, the researchers attempted to verify the authenticity of accounts themselves. They found that success rates varied wildly depending on the quality of the SIM farm. Trying to verify fake US Facebook accounts worked only 21 per cent of the time with one major provider, but jumped to over 90 per cent with another.
“High-quality verifications involve a physical SIM, requiring huge banks of phones,” said co-lead author Anton Dek from the Cambridge Centre for Alternative Finance. “Nations in which SIM cards are more expensive have higher prices for fake accounts. This is likely to suppress rates of malicious online activity.”
The researchers tracked 17 major vendors, noting that the market’s largest players have significant customer bases in China and the Russian Federation, with payment systems and site design often indicating Russian authorship.
While direct state involvement is hard to trace, Dek suspects that even state-level actors outsource some operations to this “manipulation market”, where just €10 can buy 90,000 fake views.
“Understanding the cost of online manipulation is the first step to dismantling the business model behind misinformation,” said co-author Professor Sander van der Linden.
