Langflow: BaseFileComponent-based nodes arbitrary file read with RCE exploit

Summary

All components based on BaseFileComponent are vulnerable to the following vulnerability:

1. Docling (DoclingInlineComponent)
2. Docling Serve (DoclingRemoteComponent)
3. Read File (FileComponent)
4. NVIDIA Retriever Extraction (NvidiaIngestComponent)
5. Video File (VideoFileComponent)
6. Unstructured API (UnstructuredComponent)

For clarity, from now on I'll only refer to Read File component.

The Read File node processes user-controlled files. Example scenario is a RAG chatbot - a system that allows users of an organization to ask questions about documents saved in the organizations.

By controlling a files that are digested into the RAG, an attacker can direct the node to read any file on the file-system by absolute path.

Using this vulnerability an attacker can acheive RCE:

1. Upload a file that directs the node to read Langflow's secret_key file containing the JWT token secret.
2. This would allow the attacker then to simply task the Chatbot for the JWT secret.
3. Using this secret, the attacker then crafts a JWT token for any user-id, bypassing authentication.
4. Code execution is then trivial - simply create a new flow with "Python Interpreter" node, fill it with arbitrary Python code and execute it.

Tested on commit 2d67402b1dbaefcbce85a244d4a6cd5e4bda1cfe

Details

The vulnerability is in: langflow/src/lfx/src/lfx/base/data/base_file.py Specifically in _unpack_bundle. This function extracts tar files, which can contain a symlink. This symlink can point to any file in the filesystem. Then, in self.process_files(), the file pointed by the symlink will be parsed and saved into the RAG. This can be done with unlimited number of symlinks in the same tar which can also be useful in some scenarios.

Suggestd fix - iterate over the files and make sure all are regular files or directories.

PoC

Reproduction:

1. Create a flow with Read File (or any other affected components), and connect its output to some storage such as Chroma DB.
2. Create a symlink pointing to any file. For the above exploit, point the symlink to langflow's JWT token file.
3. Compress this symlink with tar.
4. Upload it to the Read File component.
5. Check the database, or ask a Chatbot connected to this vector database for the contents of the file.