AI-Generated Fake Train Tickets Lead to Arrests on Mumbai Local
Multiple passengers were arrested for using AI-generated forged UTS train passes on Mumbai local trains after ticket inspectors detected the fraudulent digital tickets. An engineer had used AI tools to create the fake season passes, which were identified by their inability to function in the official app and through verification of duplicate ticket numbers.
What happened
An engineer named Omkar Sharma used AI tools and his coding skills to generate forged UTS AC local train season passes and shared them with his wife Gudiya Sharma. On November 26, Gudiya Sharma was caught by Travelling Ticket Inspector Vishal Navle on a Kalyan-Dadar AC local train when she presented a non-functional forged pass; verification with CR control room revealed the ticket number belonged to an expired pass issued in February and registered under her husband's name.
On November 28, three other passengers—Niraj Talreja, Atharv Baag and Aditi Manglurkar—were detected by TTI Prashant Kamble on an 18:45 Parel-Kalyan AC local train with AI-generated fake UTS season passes. All three digital passes carried the same ticket number XOOJHN4569, and verification confirmed no season tickets had been issued to them.
Reported impact
Railway officials stated that quick detection of the forged passes helped prevent revenue loss. Police said the couple may be linked to a wider network involved in fake digital passes.
Index analysis
The fake tickets were identified by trained ticket inspectors who noticed that forged passes could not be opened in the official UTS mobile app and carried non-functional QR codes or duplicate ticket numbers that differed from how genuine UTS-generated tickets function.
Governance controls
Central Railway urged commuters to buy tickets only through authorised counters, ATVMs, or the official UTS app. The railway warned that travelling on forged tickets is punishable with imprisonment of up to seven years, a fine, or both.
Classification
Sources and evidence
This record was researched and written by the Index, based on the following original reporting.