d3b60fa898
* fix(security): use CodeQL-recognised sanitiser for path-injection sinks Addresses CodeQL alerts #205-213 (py/path-injection, high). All three modules already contained path-containment logic, but relied on ``pathlib.Path.resolve()`` + ``Path.is_relative_to`` / ``startswith``, which CodeQL's dataflow model does not recognise as a sanitiser — so the alerts kept firing on ``.exists()``/``.resolve()`` sinks. Rewrites the sanitisers using ``os.path.realpath`` + ``startswith`` — the pattern documented by CodeQL as the recognised traversal sanitiser — without changing the security guarantees. ``realpath`` canonicalises and follows symlinks, so the containment check is robust against both ``..`` sequences and symlink escapes. Files touched (one sanitiser per file): * ``agentic/services/helpers/flow_loader.py`` — replace ``_validate_path_within_base`` with ``_safe_resolved_path`` that returns the canonicalised path, then have ``resolve_flow_path`` use that canonicalised path for all downstream ``.exists()`` calls. * ``api/v1/files.py`` — rewrite the profile-picture lookup to derive the candidate path from ``realpath`` of base + user components and verify containment before any filesystem access. * ``api/v1/flows_helpers.py`` — collapse the absolute/relative branches of ``_get_safe_flow_path`` into a single ``realpath`` + ``startswith`` containment check. Drops the now- unused ``pathlib.Path as StdlibPath`` import. No behavioural changes: all 92 existing path-validation/flow-loader unit tests and 54 ``files.py`` tests still pass. * fix(security): don't leak resolved base path in flow path error detail The containment-failure branch for absolute paths returned the fully resolved flows base directory (e.g. /var/lib/langflow/flows/<user-uuid>) in the HTTP 400 detail, exposing server filesystem layout and the user's internal path component. Replace with a static message — the specific resolved path adds no diagnostic value for the client and leaks internal detail.
Langflow is a powerful platform for building and deploying AI-powered agents and workflows. It provides developers with both a visual authoring experience and built-in API and MCP servers that turn every workflow into a tool that can be integrated into applications built on any framework or stack. Langflow comes with batteries included and supports all major LLMs, vector databases and a growing library of AI tools.
✨ Highlight features
- Visual builder interface to quickly get started and iterate.
- Source code access lets you customize any component using Python.
- Interactive playground to immediately test and refine your flows with step-by-step control.
- Multi-agent orchestration with conversation management and retrieval.
- Deploy as an API or export as JSON for Python apps.
- Deploy as an MCP server and turn your flows into tools for MCP clients.
- Observability with LangSmith, LangFuse and other integrations.
- Enterprise-ready security and scalability.
🖥️ Langflow Desktop
Langflow Desktop is the easiest way to get started with Langflow. All dependencies are included, so you don't need to manage Python environments or install packages manually. Available for Windows and macOS.
⚡️ Quickstart
Install locally (recommended)
Requires Python 3.10–3.13 and uv (recommended package manager).
Install
From a fresh directory, run:
uv pip install langflow -U
The latest Langflow package is installed. For more information, see Install and run the Langflow OSS Python package.
Run
To start Langflow, run:
uv run langflow run
Langflow starts at http://127.0.0.1:7860.
That's it! You're ready to build with Langflow! 🎉
📦 Other install options
Run from source
If you've cloned this repository and want to contribute, run this command from the repository root:
make run_cli
For more information, see DEVELOPMENT.md.
Docker
Start a Langflow container with default settings:
docker run -p 7860:7860 langflowai/langflow:latest
Langflow is available at http://localhost:7860/. For configuration options, see the Docker deployment guide.
🛡️ Security
For security information, see our Security Policy.
🚀 Deployment
Langflow is completely open source and you can deploy it to all major deployment clouds. To learn how to deploy Langflow, see our Langflow deployment guides.
⭐ Stay up-to-date
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👋 Contribute
We welcome contributions from developers of all levels. If you'd like to contribute, please check our contributing guidelines and help make Langflow more accessible.