Blab AI
Indore Law Student Arrested for Selling AI-Generated NEET Question Sets on Instagram
A 19‑year‑old first‑year law student from Indore, Madhya Pradesh, was taken into custody on 23 June 2026 after authorities uncovered an Instagram scam that targeted NEET aspirants. The accused, Akshay Malviya, is alleged to have sold PDF documents that he promoted as leaked National Eligibility cum Entrance Test (NEET) papers. The files were reportedly produced with generative artificial‑intelligence tools—including ChatGPT—alongside older NEET papers and publicly available study material.
The Indore Crime Branch said the arrest followed intelligence inputs from authorities in Kota, Rajasthan. During the operation, police seized Malviya’s mobile phone and other electronic devices, recovering social‑media conversations, PDF files and records of online transactions. According to the branch, the investigation found no evidence that Malviya had accessed any genuine NEET examination paper.
The scam reportedly involved 20 to 35 students who paid between ₹50 and ₹200 through UPI and other digital payment modes to obtain the PDFs. Malviya’s Instagram account advertised the material as “exclusive” and “leaked” papers, urging students to pay for access. Police say the low price point was intended to make the offer appear credible to students anxious about securing admission to medical colleges.
The case comes amid heightened concerns over exam security and misinformation surrounding NEET‑UG. In 2026, the National Testing Agency faced a large‑scale paper‑leak controversy that led to the cancellation of the exam on 3 May 2026. The incident prompted authorities to warn candidates against trusting social‑media accounts, Telegram channels, WhatsApp groups and other unofficial sources that claim to possess confidential examination material.
Under provisions of the Information Technology Act and other relevant legal sections, the case has been registered. The investigation is ongoing, with digital‑forensic analysis underway to determine the full extent of the operation. The police have kept the investigation confidential until after the exam to avoid causing panic among candidates.
The incident highlights the potential for generative AI to be misused for academic fraud. While AI tools can aid learning and revision, they can also produce convincing‑looking content that is not based on authentic exam material. The case raises questions about digital literacy and the ability of young users to distinguish legitimate study resources from fabricated content designed to exploit their fears and ambitions.
Law enforcement agencies across India have repeatedly warned candidates against trusting unofficial claims of leaked papers. The Indore case underscores the need for stronger safeguards against emerging forms of academic fraud, as well as the importance of clear communication from exam authorities about what constitutes legitimate study material.
At present, the accused remains in custody. No further charges or court proceedings have been announced. The investigation is still underway, and it is unclear whether Malviya acted independently or was part of a larger network. The case serves as a reminder that examination‑related misinformation can spread as quickly as genuine information, especially during periods of uncertainty surrounding high‑stakes tests.
The Indore Crime Branch said the arrest followed intelligence inputs from authorities in Kota, Rajasthan. During the operation, police seized Malviya’s mobile phone and other electronic devices, recovering social‑media conversations, PDF files and records of online transactions. According to the branch, the investigation found no evidence that Malviya had accessed any genuine NEET examination paper.
The scam reportedly involved 20 to 35 students who paid between ₹50 and ₹200 through UPI and other digital payment modes to obtain the PDFs. Malviya’s Instagram account advertised the material as “exclusive” and “leaked” papers, urging students to pay for access. Police say the low price point was intended to make the offer appear credible to students anxious about securing admission to medical colleges.
The case comes amid heightened concerns over exam security and misinformation surrounding NEET‑UG. In 2026, the National Testing Agency faced a large‑scale paper‑leak controversy that led to the cancellation of the exam on 3 May 2026. The incident prompted authorities to warn candidates against trusting social‑media accounts, Telegram channels, WhatsApp groups and other unofficial sources that claim to possess confidential examination material.
Under provisions of the Information Technology Act and other relevant legal sections, the case has been registered. The investigation is ongoing, with digital‑forensic analysis underway to determine the full extent of the operation. The police have kept the investigation confidential until after the exam to avoid causing panic among candidates.
The incident highlights the potential for generative AI to be misused for academic fraud. While AI tools can aid learning and revision, they can also produce convincing‑looking content that is not based on authentic exam material. The case raises questions about digital literacy and the ability of young users to distinguish legitimate study resources from fabricated content designed to exploit their fears and ambitions.
Law enforcement agencies across India have repeatedly warned candidates against trusting unofficial claims of leaked papers. The Indore case underscores the need for stronger safeguards against emerging forms of academic fraud, as well as the importance of clear communication from exam authorities about what constitutes legitimate study material.
At present, the accused remains in custody. No further charges or court proceedings have been announced. The investigation is still underway, and it is unclear whether Malviya acted independently or was part of a larger network. The case serves as a reminder that examination‑related misinformation can spread as quickly as genuine information, especially during periods of uncertainty surrounding high‑stakes tests.
