Anti-adblock script 2026: what changed after Manifest V3

Google's Manifest V3 platform for Chrome extensions, which became mandatory for new extensions in 2022 and for existing extensions progressively since then, fundamentally changed how ad blockers can operate. The core change is that extensions can no longer run a persistent background process that intercepts and evaluates every network request in JavaScript. Instead, blocking rules must be declared ahead of time as static JSON rule sets, and the browser applies them via the declarativeNetRequest API without any extension-side script involvement.

For an anti-adblock script 2026, the practical impact is significant. Classic detection relied on observing the side effects of dynamic JavaScript filtering: a bait script would fail to load, a bait DOM element would disappear, or a global object associated with ad serving would be undefined. Those signals are still present for Manifest V2 blockers, but Manifest V3 blockers like uBlock Origin Lite leave a much smaller and different footprint. A detection script written against the old behaviour will miss a growing proportion of active blockers.

The transition is not complete: Firefox still supports Manifest V2 extensions fully, and classic uBlock Origin remains the most widely installed content blocker on Firefox. But Chrome's market dominance means that Manifest V3 patterns are increasingly the norm for the visitors you need to reach. An effective anti-adblock script in 2026 must handle both paradigms reliably.

Under declarativeNetRequest, the browser itself applies a set of rules to network requests before any page JavaScript runs. This means that when a request to a known ad domain is blocked, the blocking happens at the browser level and produces no observable JavaScript exception, no timing anomaly from a cancelled request promise, and no modification to the DOM that a MutationObserver would catch. The extension has, in effect, removed itself from the detectable JavaScript environment.

What you can still detect are the consequences of the blocking: network-level bait requests that fail to complete, ad slot elements that remain empty, and the absence of callbacks that ad scripts would normally fire. These are outcome-based signals rather than process-based signals, and they require careful timeout management. A slow network can produce the same outcome signals as an active blocker if your detection window is too tight, which leads to false positives that frustrate non-blocking visitors.

Some Manifest V3 implementations also support optional cosmetic filtering through CSS injection, which can hide page elements by class or selector even when the underlying network request was not blocked. A complete anti-adblock script must check both whether ad-related requests succeeded and whether ad-related elements are actually visible in the rendered page, not just present in the DOM. These are two distinct checks that require different detection methods.

Network bait tests send a small request to a URL that matches common ad-blocking filter list patterns, such as a path containing slash ads slash or a domain name on the EasyList blocklist. If the request completes successfully, no network-level blocker is active. If it fails or times out, a network-level blocker is likely present. This test is essential for catching declarativeNetRequest blockers that leave no other observable trace.

DOM bait tests inject a hidden element with a class name or ID that matches common cosmetic filter patterns. After a brief render cycle, the script checks whether the element is still present and visible. If it has been hidden or removed, a cosmetic filter is active. This test catches blockers that operate purely through CSS injection without blocking network requests, which is a mode some users configure specifically to avoid being detected by network-only checks.

Environment probe tests examine the browser environment for signatures left by ad-blocking extensions. Some extensions modify global objects, inject attributes into the document, or expose themselves through the browser's extension messaging API. These probes are more brittle than network or DOM tests because they depend on extension implementation details that can change with any release, but they add valuable signal to a multi-vector ensemble. AntiAdBlock Core combines several such signals to achieve approximately 99.7% detection precision across the current blocker landscape.

A detection script runs on every page load for every visitor, the vast majority of whom are not running an ad blocker. The script must complete its checks quickly enough that it does not delay the display of page content for non-blocking visitors. Any overlay shown to a false-positive visitor, someone the script wrongly identified as using an ad blocker, will directly damage user experience and can hurt your site's reputation. Both performance and precision matter.

Loading the detection script early in the page lifecycle, in or near the document head, is necessary so that detection fires before ad slots begin their auction cycle. However, the actual detection checks, particularly network bait requests, are asynchronous and must not block rendering. The script architecture should separate the synchronous early-load phase from the asynchronous signal-gathering phase, resolving a detection verdict only after collecting enough signals to be confident in the result.

Caching detection results at the session level is good practice to avoid re-running expensive checks on every page navigation. A visitor who was positively detected on the first pageview is almost certainly still using the same blocker on the second. Re-running the full ensemble on every pageview adds unnecessary latency and server load. Most production anti-adblock scripts store the detection verdict in a first-party cookie or session storage and refresh it only periodically.

Building your own anti-adblock script gives you full control over the detection logic and no dependency on a third-party service. It is a reasonable choice for very large publishers with dedicated engineering resources who can commit to ongoing maintenance as the blocker ecosystem evolves. The hidden cost is that maintenance is not optional: a detection script that is not updated against new blocker versions and new filter list patterns will degrade silently over months.

Using a managed detection service shifts the maintenance burden to a specialist provider. The provider tracks new blocker releases, updates heuristics, and can roll out changes to all customers simultaneously. For publishers without dedicated ad-tech engineering, this trade-off is usually favourable. The key evaluation criteria are detection precision across the full blocker landscape, the latency the script adds to page load, and whether the service respects your data privacy requirements.

AntiAdBlock Core is designed as a drop-in managed anti-adblock script that installs with a single line of code and handles the full detection stack, overlay delivery, and analytics reporting. It is free for up to 10,000 detections per month, which is a natural entry point for publishers who want to measure their adblock exposure before committing to a paid tier. Evaluating it alongside your own implementation gives you a concrete benchmark for detection precision and latency impact.