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WhatsApp blocks 9,400 scam accounts in India

Meta-owned platform cracks down on ‘digital arrest’ fraud networks after concerns raised by Indian authorities

WhatsApp has blocked 9,400 accounts linked to “digital arrest” scams in India since January 2026, according to information shared by the Central government with the Supreme Court. The disclosure came during ongoing proceedings related to the growing threat of cyber fraud in the country.

Digital arrest scams have emerged as one of the most common forms of online fraud in recent months. In these cases, scammers contact victims through calls or messages while pretending to be police officers, CBI officials, customs officers or other government authorities. They often accuse people of crimes such as money laundering or illegal parcels and then threaten arrest unless money is transferred immediately.

According to the government’s status report, WhatsApp launched a focused investigation earlier this year after concerns were raised by Indian enforcement agencies. Instead of removing only accounts reported by users, the platform reportedly used internal systems to detect suspicious activity, identify linked numbers and track organised scam networks. This wider crackdown led to the blocking of 9,400 accounts.

Officials also told the court that earlier takedown requests had identified around 3,800 suspicious accounts, but only a small number were directly linked to digital arrest frauds. However, deeper investigation later revealed a much larger network operating through multiple accounts.

The Centre informed the court that several agencies are now working together to curb such crimes. Telecom companies, financial institutions, regulators and digital platforms have been asked to coordinate more closely to detect fraud quickly and prevent money transfers. Authorities are also focusing on faster blocking of suspicious SIM cards and stronger identity verification measures.

WhatsApp is said to be developing additional tools to detect misuse of police or government logos in profile photos and identify impersonation attempts more effectively.

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