# Remove a known password from PDF files

**Use case:** 

Strip a known password from a batch of PDFs so downstream tools, viewers and OCR can open them without a prompt. You supply the current password in operationParams; the output PDFs open with no password. Wrong-password files are reported, not charged. The sample input carries a self-contained encrypted PDF whose password is "demo".

## Input

```json
{
  "operation": "decrypt",
  "files": [
    "data:application/pdf;base64,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"
  ],
  "operationParams": {
    "password": "demo-password"
  },
  "outputFormat": "auto",
  "maxFileSizeMb": 100,
  "perFileTimeoutSecs": 120
}
```

## Output

```json
{
  "operation": {
    "label": "Operation",
    "format": "string"
  },
  "status": {
    "label": "Status",
    "format": "string"
  },
  "inputFile": {
    "label": "Input",
    "format": "string"
  },
  "outputFileUrl": {
    "label": "Output URL",
    "format": "string"
  },
  "pageCount": {
    "label": "Pages",
    "format": "integer"
  },
  "sizeBytes": {
    "label": "Size (bytes)",
    "format": "integer"
  },
  "errorMessage": {
    "label": "Error",
    "format": "string"
  }
}
```

## About this Actor

This example demonstrates how to use [PDF Batch Suite](https://apify.com/moonweil/pdf-batch-suite.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/moonweil/pdf-batch-suite.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
This Task's input is already configured above — use it as-is rather than inventing a new one.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/moonweil/pdf-batch-suite.md

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).
