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Google Nano Banana Creates Fake PAN, Aadhaar Cards – Identity Fraud Risk

Key Takeaways

  • Google’s Nano Banana AI can generate highly realistic fake PAN and Aadhaar cards
  • A Bengaluru techie demonstrated this capability, raising serious identity fraud concerns
  • Experts warn current verification systems may not detect these sophisticated fakes

Google’s new AI image generator Nano Banana is raising serious security alarms as security researchers demonstrate its ability to create convincing fake PAN and Aadhaar cards. The technology’s precision in replicating official documents poses significant identity fraud risks in a country heavily dependent on these IDs for verification.

Bengaluru Techie Exposes Security Flaw

Harveen Singh Chadha, a Bengaluru-based technologist, recently showcased Nano Banana’s dangerous capability on X (formerly Twitter). His post included AI-generated PAN and Aadhaar cards that appeared remarkably authentic at first glance.

“Nano Banana is good but that is also a problem. It can create fake identity cards with extremely high precision.”

The demonstration revealed how easily scammers could misuse this technology to create fraudulent identification documents.

Growing Concerns About Verification Systems

While some users noted minor font inconsistencies in the generated IDs, security experts warned that these flaws could be easily corrected. One X user highlighted the core issue:

“It can become a serious issue for identity verification, since we are heavily relying on Aadhar and PAN. Issues in Identity Card generation that we spot can go overseen by people verifying it.”

The widespread use of PAN and Aadhaar across financial, government, and private services makes this vulnerability particularly concerning. Without robust verification mechanisms, these AI-generated fakes could enable large-scale identity fraud.

Training Data Questions Add to Concerns

Another user raised critical questions about the AI’s training data, asking “How did they get the training data for all these?” This points to broader concerns about how AI models are trained on potentially sensitive document templates.

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