An SSRF vulnerability exists in the gradio-app/gradio due to insufficient validation of user-supplied URLs in the `/proxy` route. Attackers can exploit this vulnerability by manipulating the `self.replica_urls` set through the `X-Direct-Url` header in requests to the `/` and `/config` routes, allowing the addition of arbitrary URLs for proxying. This flaw enables unauthorized proxying of requests and potential access to internal endpoints within the Hugging Face space. The issue arises from the application's inadequate checking of safe URLs in the `build_proxy_request` function.
A Cross-Site Request Forgery (CSRF) vulnerability in gradio-app/gradio allows attackers to upload multiple large files to a victim's system if they are running Gradio locally. By crafting a malicious HTML page that triggers an unauthorized file upload to the victim's server, an attacker can deplete the system's disk space, potentially leading to a denial of service. This issue affects the file upload functionality as implemented in gradio/routes.py.
Gradio is an open-source Python package that allows you to quickly build a demo or web application for your machine learning model, API, or any arbitary Python function. Versions of `gradio` prior to 4.11.0 contained a vulnerability in the `/file` route which made them susceptible to file traversal attacks in which an attacker could access arbitrary files on a machine running a Gradio app with a public URL (e.g. if the demo was created with `share=True`, or on Hugging Face Spaces) if they knew the path of files to look for. This issue has been patched in version 4.11.0.
Gradio is an open-source Python library that is used to build machine learning and data science. Due to a lack of path filtering Gradio does not properly restrict file access to users. Additionally Gradio does not properly restrict the what URLs are proxied. These issues have been addressed in version 3.34.0. Users are advised to upgrade. There are no known workarounds for this vulnerability.
Gradio is an open-source Python library to build machine learning and data science demos and web applications. Versions prior to 3.13.1 contain Use of Hard-coded Credentials. When using Gradio's share links (i.e. creating a Gradio app and then setting `share=True`), a private SSH key is sent to any user that connects to the Gradio machine, which means that a user could access other users' shared Gradio demos. From there, other exploits are possible depending on the level of access/exposure the Gradio app provides. This issue is patched in version 3.13.1, however, users are recommended to update to 3.19.1 or later where the FRP solution has been properly tested.
`gradio` is an open source framework for building interactive machine learning models and demos. Prior to version 2.8.11, `gradio` suffers from Improper Neutralization of Formula Elements in a CSV File. The `gradio` library has a flagging functionality which saves input/output data into a CSV file on the developer's computer. This can allow a user to save arbitrary text into the CSV file, such as commands. If a program like MS Excel opens such a file, then it automatically runs these commands, which could lead to arbitrary commands running on the user's computer. The problem has been patched as of `2.8.11`, which escapes the saved csv with single quotes. As a workaround, avoid opening csv files generated by `gradio` with Excel or similar spreadsheet programs.
Gradio is an open source framework for building interactive machine learning models and demos. In versions prior to 2.5.0 there is a vulnerability that affects anyone who creates and publicly shares Gradio interfaces. File paths are not restricted and users who receive a Gradio link can access any files on the host computer if they know the file names or file paths. This is limited only by the host operating system. Paths are opened in read only mode. The problem has been patched in gradio 2.5.0.