Agentic AI Detection

How we detect browser-based AI agents that interact with websites like humans.

What is Agentic AI?

Agentic AI refers to AI systems that can autonomously browse the web, interact with websites, fill forms, click buttons, and complete complex multi-step tasks. Unlike traditional crawlers that simply fetch and index content, agentic AI operates more like a human user.

Traditional Crawlers

• Fetch HTML content
• Follow links systematically
• Identify via User-Agent
• Respect robots.txt

Agentic AI

• Execute JavaScript
• Interact with UI elements
• Often use headless browsers
• May not identify as bots

Known Agentic AI Systems

Major AI providers are launching agentic capabilities:

OpenAI Operator

OpenAI

ChatGPT's agentic feature that can browse the web, interact with websites, and complete tasks on behalf of users. Uses HTTP Message Signatures (RFC 9421) for verification.

Manus

Manus AI

Browser-based AI agent that uses a Chrome extension to control the browser. Can be detected via extension fingerprinting.

Genspark

AI-powered search agent that injects DOM elements (like a floating action bar) into pages for interaction. Detectable via DOM fingerprinting.

Arc Search

The Browser Company

AI-native browser with built-in agentic capabilities. Browses and summarizes content on behalf of users.

Detection Methods

We use multiple techniques to identify agentic AI traffic:

Browser Automation Detection

Most agentic AI uses browser automation frameworks (Puppeteer, Playwright, Selenium). These leave detectable traces:

navigator.webdriver = true

navigator.plugins.length = 0

window.outerWidth = 0 (headless)

window.__playwright__ = defined

DOM Fingerprinting

Some agents inject identifiable DOM elements into pages:

Genspark: #genspark-float-bar

Custom agents: [data-ai-agent]

Extension Detection

Some agents use browser extensions that can be detected by probing for known extension resources:

Manus: chrome-extension://mljmkmod.../content.ts.js

How Client-Side Detection Works

Our tracking pixel includes lightweight JavaScript that checks for automation indicators:

Detection Flow

1Pixel loads and checks for navigator.webdriver and other automation signals
2Scans DOM for known agent-injected elements
3Checks for missing browser APIs (common in headless)
4Assigns confidence score based on indicators found
5Sends detection data with tracking beacon

Privacy Note: Detection runs entirely client-side and only reports aggregated signals. We don't collect personal data or browser history.

Enabling Agentic Detection

Agentic AI detection is enabled by default in the tracking pixel. You can configure it:

JavaScript

// Agentic detection is enabled by default
Superlines.init({
  trackingId: 'YOUR_TRACKING_ID',
  detectAgentic: true,  // default: true
})

// To disable (not recommended)
Superlines.init({
  trackingId: 'YOUR_TRACKING_ID',
  detectAgentic: false,
})

Detection Confidence

Detection results include a confidence level:

Level	Indicators	Example
High	3+ indicators or DOM match	Genspark float bar detected
Medium	2 indicators present	webdriver + no plugins
Low	1 weak indicator	webdriver only

Dashboard Insights

When agentic AI is detected, you'll see:

Agent identification: Which agent was detected (when identifiable)
Confidence level: How certain we are about the detection
Detection indicators: Which signals triggered the detection
Traffic trends: Agentic AI visits over time