Gurugram, Apr 15 (PTI) The Cyber Cell of Gurugram police has arrested a total of 22 people, including nine women, running a fake call centre involved in duping hundreds of job seekers of over Rs 1.25 crore in the last six months, an official said on Friday.

Also Read | Sunken Russian Cruiser, Moskva Could Have Nuclear Warheads, Says Report.

The police also seized 21 computers, 27 mobile phones, one laptop and Rs 38,000 in cash during their raid on the call centre operating from Udyog Vihar, Phase 5, in the millennium city, he said.

Following the arrests, the police let out 19 of them on bail and produced three key accused before the court which remanded them in police custody for further interrogation, Assistant Commissioner of Police (Crime) Preet Pal Singh Sangwan said.

Also Read | Ramzan 2022 Time Table: Sehri and Iftar Timings for 14th Roza of Ramadan on April 16 in Mumbai, Lucknow, and Delhi.

Detailing the modus operandi of duping people by the fake call centre, Sangwan said the accused ran a fake website called placement.com and secured details of job seekers from some genuine employment guidance websites.

After securing job seekers' details, the website people would call them up, offering them various non-existent jobs for which they would first seek a sum of Rs 6,500 for registration and then another sum of Rs 28,000 for the verification of their documents and other credentials, the ACP said.

They would subsequently demand another sum of Rs 89,000 as commission for the job, the offer letter for which was to be delivered on the payment of the sum, ACP Sangwan said.

The ACP said during the questioning of the accused persons, they have confessed that they duped people of over Rs 1.25 crore in the last six months alone.

(The above story is verified and authored by Press Trust of India (PTI) staff. PTI, India’s premier news agency, employs more than 400 journalists and 500 stringers to cover almost every district and small town in India.. The views appearing in the above post do not reflect the opinions of LatestLY)