FakeSec - AI Deepfake Detector - Sell Project

FakeSec.com - The AI-Generated Image & Deepfake Detection Platform The Story The explosion of AI-generated content - from Midjourney portraits to deepfake videos - has created an urgent, global problem: you can no longer trust what you see online. Journalists need to verify sources. Marketers need to protect brand integrity. Dating platforms need to catch catfish. Legal teams need forensic evidence. Schools need to detect AI submissions. FakeSec was built to solve this. It's a fully functional, production-ready SaaS that analyzes photos and videos for signs of AI generation using a proprietary 12-method ensemble engine - something no competitor offers. While most detectors rely on a single neural network and return a simple "real or fake" answer, FakeSec runs 3 AI models + 9 forensic analysis techniques simultaneously, giving users a transparent, detailed breakdown of exactly why an image is likely real or AI-generated. The platform is live, monetized, and serving users across 3 channels: a modern web app, a Telegram bot, and a developer API - all from a single efficient codebase. Zero Marketing - Already Getting Users This project has never been advertised. Not a single dollar has been spent on marketing. Despite that, the platform is already attracting real users organically: Total registered users: 26 (9 web + 17 Telegram bot) Total analyses performed: 397 (85 web + 312 bot) Google OAuth sign-ups: 7 Marketing budget spent: $0 Advertising campaigns run: None Live since: February 2026 Users still registering: Yes - latest registration today All 26 users found the platform on their own - through organic search, social media content published by the automated pipeline, or direct discovery. New users are still signing up every week with zero promotion. The entire development focus has been on building a complete, production-grade product - not on marketing. All monetization infrastructure (LemonSqueezy payments, Telegram Stars, API subscriptions) is fully wired and tested, ready to convert the moment traffic arrives. What this means for the new owner: the hardest part - building the product - is done. The platform works, users are finding it organically, and the payment system is ready. All that's missing is a marketing budget. Run Google Ads on "AI image detector", "deepfake checker", "is this photo real" - these are high-intent, low-competition keywords - and the revenue will follow. The product-market fit is already validated by real users choosing to register and use the tool without any prompting. Development Investment This is not a weekend project or a ChatGPT wrapper. Here are the real numbers: Total lines of code: 44,505 Total project files: 994 Python backend code: 14,417 lines across 88 files Frontend code (HTML/CSS/JS): 11,510 lines across 37 files Localization content: 12,599 lines (25 languages) SEO & metadata: 5,989 lines Media assets: 766 files (images, videos, fonts) Estimated development hours: 1,100 - 1,500+ hours Estimated development cost: $70,000 - $100,000+ Breakdown of development cost by component: AI engine (12 analyzers, scorer, ensemble logic) - 200+ hrs - $16,000 - $24,000 Proprietary model training (data collection, fine-tuning) - 150+ hrs - $15,000 - $22,500 Web application (auth, handlers, payments, admin, middleware) - 140+ hrs - $8,400 - $11,200 Telegram bot (handlers, Stars payments, inline mode, cards) - 60+ hrs - $3,000 - $4,200 REST API (endpoints, rate limiting, key system, docs) - 30+ hrs - $1,800 - $2,400 Content automation (video parser, reels generator, 4-platform publisher) - 120+ hrs - $6,000 - $8,400 Frontend (landing page, dashboard, check UI, admin panel, API docs) - 160+ hrs - $6,400 - $9,600 Localization (25 languages, 242 keys each, URL routing, RTL) - 80+ hrs - $3,200 - $4,000 Database architecture (schema, async ORM, migrations) - 25+ hrs - $1,500 - $2,000 SEO (125-URL sitemap, JSON-LD, hreflang, llms.txt, ai.json) - 30+ hrs - $1,200 - $1,800 DevOps (Nginx, SSL, deployment, process management) - 20+ hrs - $1,200 - $1,600 UI/UX design (landing, result cards, PIL image generation) - 40+ hrs - $2,000 - $2,800 Testing & debugging - 60+ hrs - $3,000 You're not paying for development time - you're skipping it entirely and getting a finished product at a fraction of what it cost to build. How It Works (The Technology) Every uploaded image goes through 12 independent analyses: 3 Neural Network Models: 1 proprietary custom-trained model (included in the sale - 1.5GB trained weights, significant R&D investment) 2 third-party high-accuracy models 9 Forensic Analysis Methods: FFT (frequency domain analysis) ELA (error level / compression artifacts) Noise pattern detection EXIF metadata inspection Texture analysis Color distribution analysis Benford's Law statistical check Edge detection analysis Pixel-level analysis The engine uses weighted ensemble scoring with intelligent model consensus - if multiple models strongly agree, their verdict is boosted. The final result...