Gradio is an open-source Python package that allows quick building of demos and web application for machine learning models, API, or any arbitrary Python function. Gradio's Access Control List (ACL) for file paths can be bypassed by altering the letter case of a blocked file or directory path. This vulnerability arises due to the lack of case normalization in the file path validation logic. On case-insensitive file systems, such as those used by Windows and macOS, this flaw enables attackers to circumvent security restrictions and access sensitive files that should be protected. This issue can lead to unauthorized data access, exposing sensitive information and undermining the integrity of Gradio's security model. Given Gradio's popularity for building web applications, particularly in machine learning and AI, this vulnerability may pose a substantial threat if exploited in production environments. This issue has been addressed in release version 5.6.0. Users are advised to upgrade. T…

Gradio is an open-source Python package designed to enable quick builds of a demo or web application. If File or UploadButton components are used as a part of Gradio application to preview file content, an attacker with access to the application might abuse these components to read arbitrary files from the application server. This issue has been addressed in release version 5.5.0 and all users are advised to upgrade. There are no known workarounds for this vulnerability.

An open redirect vulnerability exists in the gradio-app/gradio, affecting the latest version. The vulnerability allows an attacker to redirect users to arbitrary websites, which can be exploited for phishing attacks, Cross-site Scripting (XSS), Server-Side Request Forgery (SSRF), amongst others. This issue is due to improper validation of user-supplied input in the handling of URLs. Attackers can exploit this vulnerability by crafting a malicious URL that, when processed by the application, redirects the user to an attacker-controlled web page.

The 'deploy-website.yml' workflow in the gradio-app/gradio repository, specifically in the 'main' branch, is vulnerable to secrets exfiltration due to improper authorization. The vulnerability arises from the workflow's explicit checkout and execution of code from a fork, which is unsafe as it allows the running of untrusted code in an environment with access to push to the base repository and access secrets. This flaw could lead to the exfiltration of sensitive secrets such as GITHUB_TOKEN, HF_TOKEN, VERCEL_ORG_ID, VERCEL_PROJECT_ID, COMMENT_TOKEN, AWSACCESSKEYID, AWSSECRETKEY, and VERCEL_TOKEN. The vulnerability is present in the workflow file located at https://github.com/gradio-app/gradio/blob/72f4ca88ab569aae47941b3fb0609e57f2e13a27/.github/workflows/deploy-website.yml.

A command injection vulnerability exists in the gradio-app/gradio repository, specifically within the 'test-functional.yml' workflow. The vulnerability arises due to improper neutralization of special elements used in a command, allowing for unauthorized modification of the base repository or secrets exfiltration. The issue affects versions up to and including '@gradio/video@0.6.12'. The flaw is present in the workflow's handling of GitHub context information, where it echoes the full name of the head repository, the head branch, and the workflow reference without adequate sanitization. This could potentially lead to the exfiltration of sensitive secrets such as 'GITHUB_TOKEN', 'COMMENT_TOKEN', and 'CHROMATIC_PROJECT_TOKEN'.

An issue was discovered in gradio-app/gradio, where the `/component_server` endpoint improperly allows the invocation of any method on a `Component` class with attacker-controlled arguments. Specifically, by exploiting the `move_resource_to_block_cache()` method of the `Block` class, an attacker can copy any file on the filesystem to a temporary directory and subsequently retrieve it. This vulnerability enables unauthorized local file read access, posing a significant risk especially when the application is exposed to the internet via `launch(share=True)`, thereby allowing remote attackers to read files on the host machine. Furthermore, gradio apps hosted on `huggingface.co` are also affected, potentially leading to the exposure of sensitive information such as API keys and credentials stored in environment variables.

An SSRF (Server-Side Request Forgery) vulnerability exists in the gradio-app/gradio repository, allowing attackers to scan and identify open ports within an internal network. By manipulating the 'file' parameter in a GET request, an attacker can discern the status of internal ports based on the presence of a 'Location' header or a 'File not allowed' error in the response.

gradio-app/gradio is vulnerable to a local file inclusion vulnerability due to improper validation of user-supplied input in the UploadButton component. Attackers can exploit this vulnerability to read arbitrary files on the filesystem, such as private SSH keys, by manipulating the file path in the request to the `/queue/join` endpoint. This issue could potentially lead to remote code execution. The vulnerability is present in the handling of file upload paths, allowing attackers to redirect file uploads to unintended locations on the server.

A timing attack vulnerability exists in the gradio-app/gradio repository, specifically within the login function in routes.py. The vulnerability arises from the use of a direct comparison operation (`app.auth[username] == password`) to validate user credentials, which can be exploited to guess passwords based on response times. Successful exploitation of this vulnerability could allow an attacker to bypass authentication mechanisms and gain unauthorized access.

A command injection vulnerability exists in the deploy+test-visual.yml workflow of the gradio-app/gradio repository, due to improper neutralization of special elements used in a command. This vulnerability allows attackers to execute unauthorized commands, potentially leading to unauthorized modification of the base repository or secrets exfiltration. The issue arises from the unsafe handling of GitHub context information within a `run` operation, where expressions inside `${{ }}` are evaluated and substituted before script execution. Remediation involves setting untrusted input values to intermediate environment variables to prevent direct influence on script generation.