Computer-use APIs are model endpoints that look at a screenshot and reply with the next mouse click or keystroke, so a developer's own program can operate a browser or desktop on a user's behalf. Anthropic released computer use in public beta with Claude 3.5 Sonnet on Oct 22, 2024. OpenAI followed on Mar 11, 2025 with its Computer-Using Agent model in the Responses API, and Google released the Gemini 2.5 Computer Use model, tuned for browsers, on Oct 7, 2025.
None of the three vendors publishes usage numbers for these APIs, which makes them hard to size. What we know is that they are paid per token and that the developer supplies and pays for the browser or desktop the model controls. That second part is what matters for detection, because the AI company never touches your site at all.
Developers use them for form filling and data entry, testing user flows, booking and shopping tasks, scraping behind logins and back-office workflows. Any site with a form or a login can see them, and they turn up most on SaaS sign-ups, ecommerce and travel.
How computer-use agents show up on your site
The model only returns actions, and the developer's code carries them out in a browser the developer runs. Anthropic's reference implementation is a Docker container with a virtual Linux desktop and Firefox. OpenAI's samples use Playwright with local Chromium and list Browserbase, Browser Use, Daytona and E2B as hosted partners, while Google's samples use Playwright Chromium at 1440x900. Traffic leaves from the developer's VM, laptop or browser host, not from Anthropic, OpenAI or Google.
| Check | What computer-use agents do |
|---|---|
| User agent | No token. Whatever browser the developer runs |
| Web Bot Auth signature | None from the model vendors. A host such as Browserbase may sign |
| IP ranges | No vendor list. Developer's network or browser host |
| robots.txt | Not documented by any of the three vendors |
Why computer-use agents are easy to catch in default setups
The reference setups are built for clarity, not stealth. Playwright Chromium and a virtual Linux desktop in Docker leave automation markers, VM traits and datacenter IPs. Playwright tends to leave globals such as __playwright__binding__ and __pwInitScripts in the page, and WebDriver harnesses built on ChromeDriver leave cdc_ variables in the document, and the way the model works adds its own rhythm: a fixed, round viewport, long pauses while the model reads each screenshot, then a single click with the cursor jumping straight to its target, and text that arrives pasted or perfectly even.
All of that depends on the host. When a developer runs the same model on a stealth browser service with residential proxies, the automation markers disappear and only the pacing remains, while a host that signs, such as Browserbase, which Cloudflare lists as a signed agent, identifies itself instead. That is why the same Claude, OpenAI or Gemini agent can be trivial to catch in one deployment and hard in the next.
How Verisoul detects computer-use agents
Verisoul names the harness rather than the model. Depending on how the developer built it, the browser shows headless markers, DevTools-protocol automation artifacts or WebDriver flags, and the session moves with scripted navigation and no human input. Verisoul returns those as headless_chrome, cdp_automation or webdriver. Runs on a stealth browser host that hides those markers are flagged through bot score, and Verisoul does not name the model behind them.
"agent": {
"id": "cdp_automation",
"name": "DevTools automation",
"provider": "Open source",
"type": "headless_automation",
"detection_method": "self_declared",
"detection_signals": [
"network",
"device",
"behavioral"
]
}idis the rule key, herecdp_automationfor a Playwright-driven Chromium;headless_chromeandwebdrivercover other harnessestypeisheadless_automation, a scripted browser with no person driving itdetection_methodisself_declared, because the browser exposed its own automation markersdetection_signalslists the evidence,devicefor automation artifacts andbehavioralfor scripted navigation
Agent Atlas covers DevTools automation, Headless Chrome and WebDriver, and the AI agent detection docs explain the response format.
- 01Model returns a click
- 02Developer's Playwright script performs it
- 03Your page loads in a Linux VM
- 04Next screenshot goes back to the model
How to detect computer-use agents step by step
- Add the Verisoul SDK to sign-up, login and payout pages following the Verisoul docs
- Route
headless_chrome,cdp_automationandwebdriverto your automation policy - Set a bot score threshold for unnamed sessions to catch agents running on stealth hosts
- Allowlist your own testing or partner automation so production rules can stay strict
Should you block computer-use agents?
A computer-use agent may be doing legitimate back-office work for a business, but on your site it is usually an unknown developer's script. Block it at sign-up and payouts, and send it to review at checkout, where model vendors' own guardrails on purchases can be switched off by the developer.
If a partner needs to automate a flow on your site, offer an API or a dedicated path. That keeps the browser flow strict for everyone else.