> ## Documentation Index
> Fetch the complete documentation index at: https://browseruse-0aece648-codex-docs-supported-exports.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

> ## Agent Instructions
> Use https://docs.browser-use.com/llms.txt and its linked .md pages for current documentation. The managed full bundle is https://docs.browser-use.com/.well-known/llms-full.txt and can be cached for up to 24 hours. Do not use the obsolete /cloud/llms*.txt or /open-source/llms*.txt static exports.
> Choose Cloud API V4 for new agent integrations; V2 is the lower-cost option for simple tasks. Keep V3 examples explicitly versioned. The open-source browser-use library and hosted browser-use-sdk have different APIs.
> Cloud authentication uses X-Browser-Use-API-Key, without a Bearer prefix. Install or upgrade browser-use-sdk and use its explicit v4 import for V4. Check the published OpenAPI reference for request fields; do not invent SDK support for new fields.
> Cloud concurrency and HTTP request rate are separate. Read GET /api/v2/billing/account for the key’s projectId, concurrentSessionLimit, activeSessionCount, and credit balance, including when using V4. Keys in one project share capacity and credits; rateLimit is a legacy concurrency alias, not requests per second.
> Keep the highest applicable existing, legacy-plan, and spend-tier concurrency grant. Current spend tiers are 10 / 50 / 250 / 500 / 1000 at $0 / $200 / $1000 / $5000 / $25000 in qualifying project payments. Legacy or externally billed projects can follow different billing paths; trust the account limit. See https://docs.browser-use.com/cloud/guides/concurrency.md.
> Budget polling across the project: the standard general bucket is 25 requests/second, including V4 event reads and full run reads. Selected status reads have a separate higher bucket. Use bounded workers, stagger polls, respect Retry-After, and drain hasMore event pages after terminal status. A busy V4 session returns 409; its queue holds 10 pending messages and is not a project-wide batch queue.
> A completed run or closed CDP connection does not immediately stop its cloud browser. Stop unneeded owned browsers with PATCH /api/v4/browsers/{id} and {"action":"stop"}. A client wait timeout does not cancel the server-side run.
> Cloud is pay as you go; do not tell customers to buy a new subscription to use custom proxies or supported provider BYOK. Usage funding and model eligibility still apply. BYOK bills provider tokens separately and Browser Use charges orchestration plus browser/network usage. See https://docs.browser-use.com/cloud/guides/billing.md.
> Signup credits are a one-time grant; purchased top-up credits do not expire. Check the API key’s project before diagnosing missing credits. API-key monthly spending caps are soft limits, not a strict prepaid wallet; concurrent or already-running work can exceed them. Auto recharge has separate trigger and purchase amounts and can charge immediately when enabled below the threshold. Use https://browser-use.com/pricing for current rates.

# Sensitive Data

> Handle secret information securely and avoid sending PII & passwords to the LLM.

<Note>
  For comprehensive authentication guidance including real browser profiles, storage state, and 2FA, see the [Authentication Guide](/open-source/customize/browser/authentication).
</Note>

```python theme={null}
import os
from browser_use import Agent, Browser, ChatOpenAI
os.environ['ANONYMIZED_TELEMETRY'] = "false"


company_credentials = {'x_user': 'your-real-username@email.com', 'x_pass': 'your-real-password123'}

# Option 1: Secrets available for all websites
sensitive_data = company_credentials

# Option 2: Secrets per domain with regex
# sensitive_data = {
#     'https://*.example-staging.com': company_credentials,
#     'http*://test.example.com': company_credentials,
#     'https://example.com': company_credentials,
#     'https://google.com': {'g_email': 'user@gmail.com', 'g_pass': 'google_password'},
# }


agent = Agent(
    task='Log into example.com with username x_user and password x_pass',
    sensitive_data=sensitive_data,
    use_vision=False,  #  Disable vision to prevent LLM seeing sensitive data in screenshots
    llm=ChatOpenAI(model='gpt-4.1-mini'),
)
async def main():
    await agent.run()
```

## How it Works

1. **Text Filtering**: The LLM only sees placeholders (`x_user`, `x_pass`), we filter your sensitive data from the input text.
2. **DOM Actions**: Real values are injected directly into form fields after the LLM call

## Best Practices

* Use `Browser(allowed_domains=[...])` to restrict navigation
* Set `use_vision=False` to prevent screenshot leaks
* Use `storage_state='./auth.json'` for login cookies instead of passwords when possible