
AI AdBlocker (for Android) per eye3
AI AdBlocker for Firefox Android. Build using background scripts (no service worker) Blocks obvious ad containers + simple heuristics; no remote calls. Bundles ONNX Runtime Web locally(WASM only); no CDN, No data collection, no telemetry.
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Metadatos del extension
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A proposito de iste extension
No user data is collected, stored, or transmitted. No remote endpoints. All ML/WASM runs entirely locally.
This add-on is a starter AI Ad Block extension.
• The uploaded .zip is the Firefox-compatible build (no rules/ directory, uses background.scripts instead of service_worker).
• The uploaded source .zip contains the full, human-readable source code (TypeScript, scripts, manifests, build files) without dist/ or node_modules/.
• No remote code execution, dynamic code generation, or obfuscated code is used.
• Can detect hidden ads, sponsored labels, promoted posts, native ads that rule-based systems miss.
• Can adapt better if you re-train the model with new data.
Example AI Features You Can Add DOM / Heuristic Classifier:
Train a lightweight ML model on HTML snippets (features: tag type, attributes, text like “Sponsored”).
Content script grabs candidate nodes → runs model → hide if classified as ad.
Vision-based Ad Detection:
Use a small CNN (e.g., MobileNet/ONNX quantized) to check if an <img> looks like a banner ad.
Useful for “image-only” ads where markup doesn’t give them away.
Hybrid (most practical):
Use heuristics to filter likely candidates (divs with fixed size, suspicious classes, “sponsored” text).
Use ML to confirm → avoid false positives.
Future-proofing: when advertisers obfuscate HTML/CSS, rules break → but your ML model still generalizes.
Privacy-preserving: everything runs locally in the browser; no need to send page data to servers.
Research value: positions your extension as “next-gen” ad blocker, different from commodity ones.
This add-on is a starter AI Ad Block extension.
• The uploaded .zip is the Firefox-compatible build (no rules/ directory, uses background.scripts instead of service_worker).
• The uploaded source .zip contains the full, human-readable source code (TypeScript, scripts, manifests, build files) without dist/ or node_modules/.
• No remote code execution, dynamic code generation, or obfuscated code is used.
• Can detect hidden ads, sponsored labels, promoted posts, native ads that rule-based systems miss.
• Can adapt better if you re-train the model with new data.
Example AI Features You Can Add DOM / Heuristic Classifier:
Train a lightweight ML model on HTML snippets (features: tag type, attributes, text like “Sponsored”).
Content script grabs candidate nodes → runs model → hide if classified as ad.
Vision-based Ad Detection:
Use a small CNN (e.g., MobileNet/ONNX quantized) to check if an <img> looks like a banner ad.
Useful for “image-only” ads where markup doesn’t give them away.
Hybrid (most practical):
Use heuristics to filter likely candidates (divs with fixed size, suspicious classes, “sponsored” text).
Use ML to confirm → avoid false positives.
Future-proofing: when advertisers obfuscate HTML/CSS, rules break → but your ML model still generalizes.
Privacy-preserving: everything runs locally in the browser; no need to send page data to servers.
Research value: positions your extension as “next-gen” ad blocker, different from commodity ones.
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Permissiones e datosSaper plus
Permissiones necessari:
- Acceder a tu datos pro tote le sitos web
Plus de informationes
- Ligamines del additivo
- Version
- 0.1.6
- Dimension
- 107,82 KB
- Ultime actualisation
- pred 2 mesiacmi (19. aug 2025)
- Categorias associate
- Licentia
- Licentia MIT
- Politica de confidentialitate
- Lege le politica de confidentialitate pro iste additivo
- Historia de versiones
- Etiquettas
- Adder al collection
Le disveloppator de iste extension te demanda adjuta pro supportar su continuation del disveloppamento per un micre donation.
It does not collect or transmit user data.
Reviewers can build the extension from source using the included scripts (see README).