A viral AI trend that transforms ordinary photographs and videos into an 1980s-style retro look is reportedly being exploited by cybercriminals in Amroha, Uttar Pradesh. Three people have reported being targeted after receiving links from unknown numbers, with ₹16,000 allegedly withdrawn from one victim's bank account.
The incidents highlight how cybercriminals are increasingly using popular online trends as bait. Similar warnings about unverified photo-editing applications and links connected to the retro-photo trend have also been issued by cybersecurity authorities in other parts of India.
How the 1980s AI Photo Trend Is Being Misused
The current social-media trend allows users to give photographs and videos an old-fashioned 1980s appearance using AI-powered tools.
According to the reported Amroha cases, fraudsters allegedly sent WhatsApp links from unknown numbers claiming that users could create similar retro-style photographs or videos by opening the link.
The danger lies not in the AI trend itself, but in unsolicited links claiming to provide access to it. Cybersecurity officials elsewhere have similarly warned that unverified applications promoted through such trends may request excessive device permissions or expose users to financial and personal-data risks.
One Victim Reportedly Lost ₹16,000
According to the report, Amroha resident Mohammad Danish received a WhatsApp message from an unknown number offering access to the AI photo and video effect.
After he opened the link, his phone was allegedly compromised. About ₹16,000 was subsequently withdrawn from his bank account linked to the device.
Danish disconnected the phone from the internet after noticing the incident and reported the matter through the cybercrime helpline.
Two More People Were Targeted
Two other Amroha residents, Manoj Kumar and Arshad, reportedly received similar links and were also targeted.
In their cases, however, their bank accounts were not linked to the affected mobile numbers, and their money remained safe, according to the report.
All three individuals reportedly contacted the 1930 cybercrime helpline.
The cases demonstrate how a familiar and popular internet trend can make an unsolicited message appear more believable. Cybercriminals can use that familiarity to encourage users to open links they might otherwise ignore.
Why Trending Links Can Become Fraud Traps
Viral content often creates curiosity, and cybercriminals can exploit that attention by presenting malicious links as shortcuts to popular effects, applications or online services.
Cybersecurity warnings issued in Telangana this month similarly advised users against downloading unverified applications promoted as tools for creating retro-style photographs. Officials warned that malicious applications can request access to sensitive information and device functions.
This means users should distinguish between a genuine trend and an unknown link claiming to provide access to that trend.
What Users Should Do
Users should avoid opening unsolicited links simply because they promise access to a viral AI feature. Instead, they should independently locate the relevant service through its trusted website or official application.
If a suspicious link has already been opened, users should avoid further interaction with it and report suspected financial cyber fraud promptly through 1930. India's CyberDost awareness platform also advises cyber-fraud victims to contact 1930 or use the government's cybercrime reporting system.
For businesses, maintaining reliable transaction records and financial controls can also help identify and review suspicious activity. bookkeeping services in india can support organised financial documentation and transaction monitoring.
Conclusion
The Amroha incidents show how quickly cybercriminals can adapt popular online trends into potential fraud bait. The 1980s AI-photo trend itself is not the issue; the risk comes from unsolicited links, unverified applications and requests presented as shortcuts to popular digital features.
Users should verify the source independently and avoid treating a viral trend as proof that every link associated with it is genuine.