Detecting and Preventing Harmful Generative Image Outputs Using Digital Signatures
Summary
The USPTO published patent application US20260111549A1 filed by inventors Meenaz Aliraza Merchant, Sudharsan Prabu, Kun Wu, and Surendra Ulabala on December 19, 2025. The application covers an image model protection system that uses digital signatures of identified harmful images to determine whether a particular harmful image was generated by a specific large generative image model. The system matches harmful images to generated outputs and identifies prompts used to create them, enabling security measures against similar harmful images in the future.
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USPTO classification G06N covers computer systems based on specific computational models: neural networks, knowledge representation, fuzzy logic, expert systems, evolutionary algorithms. With the AI patent boom, this is one of the most-filed application classes in the office. Every newly published application in G06N lands in this feed, around 230 a month. Patent applications publish 18 months after filing, so this feed reveals what AI labs and companies were working on in the prior year and a half. Watch this if you compete in machine learning, file freedom-to-operate analyses, scout acquisition targets in AI infrastructure, or track which research groups are converting publications to patents. GovPing pulls each application with the filing number, title, applicant, and abstract.
What changed
The USPTO published patent application US20260111549A1 for a system and method of detecting and preventing harmful generative image outputs using digital signatures. The image model protection system utilizes digital signatures of identified harmful images to determine whether a harmful image was generated by a specific large generative image model, matches the harmful image to model outputs, and identifies the prompt used to generate it. The system then uses the harmful prompt to implement new security measures. This publication represents a patent application, not a granted patent, and creates no compliance obligations for any party.
Archived snapshot
Apr 24, 2026GovPing captured this document from the original source. If the source has since changed or been removed, this is the text as it existed at that time.
DETECTING AND PREVENTING HARMFUL GENERATIVE IMAGE OUTPUTSUSING DIGITALSIGNATURES
Application US20260111549A1 Kind: A1 Apr 23, 2026
Inventors
Meenaz Aliraza MERCHANT, Sudharsan PRABU, Kun WU, Surendra ULABALA
Abstract
This disclosure describes utilizing an image model protection system to improve the defensive robustness of a large generative image model against the generation of harmful digital images. For example, the image model protection system uses digital signatures of identified harmful images to determine whether a particular harmful image was generated by a specific large generative image model. Using digital signatures, the image model protection system matches the harmful image to images generated by the large generative image model. The image model protection system then identifies the prompt used to generate the image at the large generative image model. Furthermore, the image model protection system uses the harmful prompt to implement new security measures to safeguard the large generative image model against the generation of similar harmful images in the future.
CPC Classifications
G06F 21/566 G06F 21/554 G06N 3/0475 G06F 2221/034
Filing Date
2025-12-19
Application No.
19427582
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