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By | John Leyden 7th July 2008 09:55

Trojan trawls recruitment sites in ID harvesting scam

All your CV are belong to us

Hackers have turned the harvesting of personal information from and other large US jobsites into a lucrative black market business

A Russian gang called Phreak has created an online tool that extracts personal details from CVs posted onto sites including, AOL Jobs,,,,,,, and As a result the personal information (names, email addresses, home addresses and current employers) on hundreds of thousands of jobseakers has been placed at risk, according to net security firm PrevX.

Phreak has begun selling its "identity harvesting services" to fraudsters, charging $600 for data that might be applied to targeted phishing attacks, ID fraud or other nefarious purposes. Would-be clients are able to contact the gang on ICQ. For a fee the gang will filter its database for entries that refer to a particular country or particular employer.

Jacques Erasmus, director of research at PrevX, explained that he came across adverts for the tool in an underground forum. The PHP-based utility uses built-in recruiter IDs to trawl jobsites and return results in a handy web form, he explained.

"This is way beyond email harvesting tools. The utility is quite sophisticated and attempts to make sense of the data format found in CVs, extracting only useful information," Erasmus told The Register. "Phreak is selling its services to people running higher-end [targeted] spear phishing attacks."

Jobsites have been a target for data sniffing attack for some time. PrevX said the latest attack is distinct from one carried out by a Trojan horse program last year.

This time around the attack affects far more sites than alone. Also the attack involves a harvesting engine, rather than the use of malware.

Job sites might be able to guard against the latest assault on user data by limiting the number of searches a "recruiter" can carry out or by applying CAPTCHAs, Erasmus explained.

A CAPTCHA is a type of challenge-response test designed to distinguish between requests from an automated program and a human. The approach typically asks a user to identify the letter in an image before allowing a request, such as an attempt to sign up to a web-mail service. ®

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