CloudFlare: like all traffic to customers through Tor is malicious




CloudFlare, a company that protects, among other sites, says that 94 percent of all the Tor traffic that it perceives with its customers, is evil. Anonymous network would be used among other things to gather email addresses for spam campaigns.

Tor fpa In a blog post explains CloudFlare CEO Matthew Prince that the term “evil” has nothing to do with the content that is visited, but that it refers to the activity being performed. Thus the Tor network besides collecting e-mail addresses are used to operate comment spam, like the search for vulnerabilities, fraud ads and content scraping.

As a result, CloudFlare indicates a high threat score to the IP addresses of Tor exit nodes, which is an indication of the risk that a connection from that IP address entails. Thereby however also hit legitimate users of the Tor network. They are often faced with captcha programs that need to verify that indeed a human user makes a request.

As Ars Technica reports , CloudFlare has recently introduced a policy, allowing customers to choose what they want to do with incoming Tor requests. They can permit or block and may also choose to perform a test with a captcha or javascript challenge. So it is also possible that a Tor user can not access all the way to a certain page. Also, Tor example, users are unable to change Wikipedia pages and sixty to seventy percent of the Tor traffic blocked by Akamai and Amazon Web Services, knows Ars Technica.

According CloudFlare is difficult to distinguish between malicious and legitimate users of the anonymous network. Normally, the threat score is ignored if namely the reputation of the user’s browser is good. Due to the design of the Tor-browser would be the identification of individual users will be more difficult, however. The identification on the basis of, for example, a browser is possible with device fingerprinting . There is only a limited number of exit nodes in the Tor network, so that a relatively small group of malicious users can lead to a high risk estimation.


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