Advanced bypass for ad-blocker detection with filter list optimization
目前為
Purpose: This userscript is designed to bypass common anti-adblocker detection mechanisms used across websites. Its goal is to provide a smoother browsing experience for users who employ ad-blocking tools by suppressing disruptive overlays, messages, and tracking systems that interfere with site content.
Key Functions:
Ad-blocker Variable Spoofing: It sets common detection variables to benign values, making the site think no ad blocker is in use.
Function Mocking:
Mocks and safely triggers detection-related functions (like ai_adb_undetected) to prevent disruptions or pop-ups.
Bait Element Handling: Identifies and manipulates “bait” ad elements and ensures they appear normal to scripts checking for hidden ads.
Ad Resource Spoofing:
Intercepts fetch and XMLHttpRequest calls to known ad domains and returns harmless responses, avoiding detection.
DOM Cleaning: Continuously removes or hides anti-adblock overlays, notices, pop-ups, and sponsored content.
Cookie Clearing: Deletes ad-related and tracking cookies commonly used in anti-adblock systems.
Content Restoration: Restores legitimate site content that may be hidden or blocked due to ad-block detection.
IAB Script Neutralization: Counteracts detection scripts following IAB (Interactive Advertising Bureau) guidelines by making their bait elements visible.
Mutation Observation & Interval Checks: Monitors the DOM for new elements and periodically reapplies spoofing and cleanup procedures for dynamic content.
This script is currently in beta mode, meaning it is still under development and may not work perfectly on all websites. Users might encounter bugs or unexpected behavior.
If you experience issues, please report them with as much detail as possible (site URL, what happened, etc.). This feedback is essential for improving the script’s effectiveness and compatibility.
This script is distributed under the MIT License (see https://opensource.org/licenses/MIT for details), allowing free use, modification, and distribution with proper attribution.
