What is it about?
Fingerprints are widely used for security, but they can't be changed if stolen, unlike passwords. Most systems store abstract "templates" instead of actual fingerprint images, assuming they’re safe. Our research shows this assumption is no longer valid. Using AI, we were able to turn stolen fingerprint templates into realistic fake fingerprints. We then used low-cost tools to make physical copies of these fake prints with silicone and a 3D printer. These replicas were able to fool real commercial fingerprint scanners. This shows that attackers can now bypass fingerprint security using only the stored template data. We share our tools openly to help others study this threat and develop better defenses.
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Photo by George Prentzas on Unsplash
Why is it important?
Fingerprint templates were long believed to be safe because they don’t store actual fingerprint images. Our work proves this assumption is outdated. We show that attackers can now turn stolen templates into real fake fingerprints that work on commercial scanners. What’s new here is that we don’t just simulate an attack, we fully execute it in the physical world, using cheap, accessible tools. This is the first study to do so. By releasing our tools, we help others test their own systems and build better defenses against this growing AI-driven threat.
Perspectives
It felt important to verify whether the deepfake fingerprint threat was actually possible, beyond just theory. Building and testing the full pipeline gave us a clear answer. It was rewarding to work with the equipment and see each stage come together, from model training to 3D printing and casting the replicas. In the end, everything worked as hoped, and it was satisfying to see the results come out clearly and convincingly.
Yaniv Hacmon
Ben-Gurion University of the Negev
Read the Original
This page is a summary of: The Threat of Deepfake Fingerprints, August 2025, ACM (Association for Computing Machinery),
DOI: 10.1145/3709022.3736542.
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