Gradio Local File Inclusion Scanner

Gradio is a widely used platform for creating and sharing machine learning interfaces. It is popular among developers and data scientists for its ease of use and ability to quickly prototype and demonstrate machine learning models. Integrated with platforms like Hugging Face, Gradio provides a seamless experience for collaborative work on AI projects. Additionally, Gradio supports a variety of data types and allows for customization in user interface design, making it versatile for different applications. Its user-friendly design and comprehensive documentation have made it a go-to choice for rapid deployment of machine learning models. Gradio's open-source nature ensures that it continuously evolves with contributions from a large community of developers.

The Local File Inclusion (LFI) vulnerability allows an attacker to include files on a server through the web browser. This vulnerability may occur due to insufficient input validation mechanisms when referencing files via user input. Attackers exploit this by manipulating variables to load unauthorized local files. Such attacks can lead to unauthorized disclosure of sensitive information, such as configuration files or system-level password files. In a compromised system, LFI can be leveraged to execute system commands or scripts, potentially leading to full system compromise. The Gradio LFI vulnerability specifically pertains to the manner in which arbitrary methods of its Components class are called, allowing unintended local file access.

Technically, the vulnerability in Gradio is exploited by crafting specific HTTP requests that target the application's component methods. Through techniques like the clusterbomb attack, the vulnerability in the endpoint handling component APIs can be triggered to expose or download unauthorized file content. This problem is particularly exposed when user inputs are not adequately sanitized, leading to potential local file reads. The vulnerable endpoint uses input parameters such as "component_id" and "path" within the "component_server" path, susceptible to tampering. As a result, attackers can retrieve sensitive files like /etc/passwd in Unix systems or win.ini in Windows systems, facilitating further exploits.

Exploitation of an LFI vulnerability can have critical impacts, including unauthorized data access, information disclosure, and escalation of privileges. Cyber attackers could use it to expose sensitive information stored on the server, leading to potential data breaches. If the infection proceeds without timely detection, the threat actor might gain further access or execute additional attacks such as remote command execution. It also creates opportunities for further exploitation through inclusion of malformed files or scripts. Ultimately, this can lead to total system compromise, affecting business operations, damaging reputation, and resulting in financial losses for affected organizations.

REFERENCES

• https://github.com/gradio-app/gradio/commit/24a583688046867ca8b8b02959c441818bdb34a2
• https://www.horizon3.ai/attack-research/disclosures/exploiting-file-read-vulnerabilities-in-gradio-to-steal-secrets-from-hugging-face-spaces/