Over 1,000 Fake IPL Websites Target Fans With Ticket Frauds and Malware Attacks: Report

New Delhi: Cybersecurity researchers have uncovered more than 1,000 fake IPL-related websites being used to scam cricket fans and spread malware during the ongoing Indian Premier League season.

According to a report by CloudSEK, over 600 fraudulent domains were found selling fake IPL tickets, while more than 400 fake streaming websites were identified as platforms distributing malware and conducting phishing attacks.

The report said cybercriminals are taking advantage of the excitement and urgency surrounding IPL matches, especially among fans searching for last-minute tickets or free live streaming options online.

Sourajeet Majumder from CloudSEK said these scams have become highly organised, with fraudsters operating sophisticated fake ticketing systems that track user activity, manage payments, alter prices dynamically and collect personal information for future misuse or resale.

Researchers found that many fake ticket booking sites closely resembled genuine platforms by copying official logos, website layouts and booking procedures. Users were asked to choose seats, provide personal information and complete payments through UPI, QR codes, cards and online payment gateways.

In several cases, victims received fake PDF tickets carrying booking IDs and QR codes after making payments, only to discover the fraud upon reaching stadium entry gates.

The report also revealed that scammers were using Meta Pixel tools to monitor clicks, form submissions and payment activity, helping them refine and expand their fraudulent campaigns in the same way legitimate e-commerce businesses optimise customer engagement.

Apart from ticket scams, the report warned about fake IPL streaming websites designed to appear in searches related to “free IPL live streaming” and match-specific broadcasts.

Many of these websites reportedly redirected users to suspicious pages, triggered malware downloads or attempted to steal login credentials and personal information.

With inputs from IANS