A criminal organization recently busted by law enforcement distributed malware on Facebook using two separate botnets built from tools that are easily found in the hacker underground, a security expert said.
The FBI announced on Tuesday that 10 people had been arrested for allegedly targeting Facebook users with malware designed to steal credit card and bank account numbers.
The arrests were made across seven countries, Bosnia-Herzegovina, Croatia, Macedonia, New Zealand, Peru, the U.K. and the U.S. The police effort was a joint operation between the FBI and international law enforcement agencies.
The suspects allegedly ran a network of more than 11 million compromised computer systems linked to the theft of more than $850 million, the FBI said. Over the last two years, the botnet has distributed malware through Facebook accounts.
Atif Mushtaq, senior staff scientist for security vendor FireEye, said Wednesday the operation involved two separate botnets, each comprised of computers compromised by different malware. One network used unnamed software built with the Butterfly toolkit and the other the Yahos malware, which is a variant of open-source SBDot.
Based on the tools used, the operators were not first class hackers, Mushtaq said. "It looks like these guys aren't very good developers," he said. "They took two ready-to-cook malware."
The operation exemplifies how deep technical knowledge is not needed to run a lucrative botnet. Many underground marketplaces exist for criminals to buy the toolkits they need from developers.
[In depth: The botnet hunters]
For example, the Butterfly toolkit was used to build the Mariposa malware that drove a major botnet by the same name before it was taken down starting in late 2009, Mushtaq said. At its height, the botnet was one of the world's largest and included compromised machines in half of Fortune 100 companies and hundreds of government agencies.
In the latest botnet takedown, Facebook assisted law enforcement in building a case against the suspects. The social network, which recently topped 1 billion users, provided investigators with information on the malware architecture and evidence linking the suspects.
Facebook has been investigating the botnet since 2010. Its automated systems have been configured to identify affected accounts based on suspicious activity, and to block malicious content, the company said. Facebook has not seen any activity from the botnet since October.
Security experts agree that taking down botnets and arresting the operators is necessary to increase the risk and expense. As investigators get better at identifying operators, they will have to spend more money on sophisticated technology to hide their tracks.
However, the potential profit is sure to continue attracting criminals. Tony Perez, chief operating officer for Sucuri, compared it to fighting the drug trade or terrorism. Both remain major problems, despite numerous arrests.
"Cybercrime is a highly lucrative business right now, these arrests, which seem big, are really small and its impact will be marginal," Perez said. "That being said, I don't want to take away from their [law enforcement] accomplishment. Being able to take down the Yahos malware team is a big accomplishment and I commend them for it."
Facebook has taken a number of steps to prevent users from being duped by cybercriminals. Since 2008, Facebook has had a security system that checks URLs against a blacklist. Links pointing to URLs suspected of sending users to malicious websites prompt a warning.
Facebook also provides an antivirus marketplace with malware-detection software from a variety of vendors. In November, Facebook started encrypting all communications with its North American users to prevent crooks from capturing information when people use public Wi-Fi networks.
The security risk on Facebook was highlighted over the summer when the company disclosed in a Securities and Exchange Commission (SEC) filing that it had found 14 million "undesirable" accounts, meaning they were likely spewing spam or other malicious links and content.
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