- Barracuda research reveals the extent of data scratch robots
- Not all robots are bad, but many extract huge amounts of data without authorization
- These “gray bots” can be very aggressive, warns the report
New research by Barracuda has identified “gray robots”, alongside good and bad robots that explore the web and extract the data – and although “good robots”, such as SEO and customer service robots, “bad bots” are designed for harmful activities such as fraud, data and violation accounts.
In space between the two, there are “gray robots”, which Baraccuda explains that the Genai foys robots designed to extract serious amounts of websites of websites, probably to form models of AI, or to collect web content such as news, criticisms and travel offers.
These robots “blurring the limits of legitimate activity”, maintains the report. Although they are not downright malicious, their approach can be “questionable” and some are even “very aggressive”.
Increased activity
The Baraccuda detection software found millions of requests received by web applications from Genai Bots between December 2024 and February 2025, with a web application followed receiving 9.7 million scratch robot requests in just 30 days.
These bots collect data and can delete it without authorization, and can also submerge web applications with traffic, disrupt operations and take data protected by copyright to form AI models, which can be in violation of the owner’s rights.
There has been a lot of perspective against practices like these, with creative industries in the United Kingdom by launching a campaign “ Make It Fair ” to protest against the fact that their work is used by AI models to create photos, videos, stories or other content without authorization or credit.
The risks of data confidentiality are also delivered with this level of scratching, because some sites carry sensitive customer data – for example that of health services or financial services.
Boots can also mask websites, which makes organizations very difficult to assess and monitor authentic traffic or user behavior, which makes commercial decisions more difficult.
