NSFW JS — Client-side image moderation library

NSFW JS is an open-source image moderation library for web developers and platform owners

NSFW JS is a client-side machine learning library that identifies indecent content in images directly within the browser environment. This tool is built for web developers and platform owners who need to moderate user-generated content without transmitting sensitive image data to external servers. By utilizing TensorFlow.js, the library classifies images into specific categories such as neutral, porn, and hentai to ensure platform safety. The library provides business owners with a way to reduce server-side processing costs while significantly increasing user privacy. NSFW JS processes data locally on the user's device, which allows for real-time moderation before an image is saved to your cloud storage or database. This local execution model helps maintain strict platform integrity while keeping your infrastructure requirements to a minimum. As you scale digital communities or online marketplaces in 2026, automated moderation becomes critical for protecting brand reputation and following safety regulations. Business owners can explore additional security integrations and safety benchmarks on surfai.app to further harden their applications against inappropriate content. The tool includes multiple model sizes, enabling your team to optimize for either mobile performance or maximum classification accuracy. NSFW JS is an open-source project provided under the MIT license and is entirely free to use. This makes it an ideal choice for startups and enterprises that want to implement content guardrails without the recurring costs of external API subscriptions.

• Pricing: free

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