Scammers have now resorted to a new method of looting people, and this time, it is the steganography technology.
As confirmed by latest reports, scammers used steganography technology to steal more than ₹2 lakh from a guy called Pradeep Jain through a malicious picture posted on WhatsApp.
Here’s what went down.
Over 2 Lakh Stolen By Simply Sharing a Picture Over Whatsapp
Soon after downloading a picture that was sent to him via WhatsApp, Pradeep Jain lost over Rs 2 lakh.
After receiving a call from an unidentified number, 28-year-old Jain saw a picture of an older guy with the words, “Do you know this person?”
At first, Jain chose to ignore the calls, but when the con artists persisted, he eventually downloaded the picture.
Jain lost ₹2.01 lakh, which was taken out of an ATM in Hyderabad, just minutes after uploading the picture.
The fraudsters successfully evaded verification by impersonating Jain using a vocal mimicking method when Canara Bank attempted to confirm the transaction over the phone.
What is Least Significant Bit Steganography?
Least Significant Bit (LSB) steganography, which modifies the least significant bits of data units to conceal harmful material within media files, was employed in the assault.
An expert explained, “The word ‘steganography’ has Greek origins. It means ‘hidden writing’. In cybercrime, this technique is exploited to embed malware or secret instructions inside harmless-looking media files. These hidden payloads often evade traditional detection systems and are triggered only by specific scripts.”
Another expert added historical context: “This isn’t a new concept. In 2017, hackers embedded harmful executable code inside GIF files shared on WhatsApp. When downloaded, the hidden code ran in the background, bypassing security settings and accessing the user’s data. Though the vulnerability was patched, this technique made a comeback in 2019 with more refined methods and broader targets.”
Traditional antivirus software is not sufficient to detect such threats. Detecting steganographic attacks requires forensic tools, behavioural analytics, and steganalysis platforms to identify anomalies in file structures.
One expert emphasized the role of AI: “AI and machine learning offer a better shot by detecting behavioural irregularities within files and improving early threat detection.”
