CVE-2023-51449 Scanner

Gradio is a platform used extensively by developers and data scientists for creating user interfaces for machine learning models. It allows for quickly building scalable applications with interactive, web-based UIs, making machine learning accessible to a wider audience. Organizations leverage Gradio for deploying AI experiments, testing model outputs, and showcasing model capabilities in a user-friendly manner. Its integration with platforms like Hugging Face further broadens its usage in the AI community. Gradio is known for its flexibility, supported by a strong community and regular updates. Its ease of use and ability to integrate with Python makes it a preferred choice for many machine learning projects.

The Local File Inclusion (LFI) vulnerability allows attackers to include files on a server through a web browser. In insecure setups, such as Gradio's configurations without authentication, this can lead to unauthorized file access. LFI can expose sensitive data, opening gateways for further exploitation in the application environment. Gradio's versions between 4.0 and 4.10 and those below 3.33 are susceptible to this vulnerability, mainly when security configurations are not enforced. Attackers often exploit LFI to read system files or inject malicious scripts that can run on the server. Consequently, understanding and patching this vulnerability is crucial to prevent unauthorized file access and data breaches.

Exploiting the LFI vulnerability generally involves manipulating input fields that handle file paths, such as those within Gradio when certain endpoints are improperly secured. Attackers might send requests with crafted payloads leading to file path traversals, reaching unintended directories. Commonly targeted files include configuration or sensitive system files, such as '/etc/passwd' on Unix-like systems, which can be accessed by exploiting the vulnerability. In this template, specific payloads attempt to directory-traverse to fetch critical files. Secure configurations and proper input sanitization in Gradio act as defenses against such attacks, thwarting attempts to exploit the LFI vulnerability.

When exploited, the LFI vulnerability can result in unauthorized exposure of confidential files stored on the server. This exposure may include access to credentials, system configurations, or sensitive data within the application. Additionally, the vulnerability could allow attackers to gather intelligence useful for further attacks, such as privilege escalation or injecting malicious code. Compromised systems are at risk for data theft, operational disruption, and reputational damage. It is crucial to ensure that application configurations, especially around file handling and authentication, are secure to prevent such detrimental effects.

REFERENCES

• https://www.horizon3.ai/attack-research/disclosures/exploiting-file-read-vulnerabilities-in-gradio-to-steal-secrets-from-hugging-face-spaces/
• https://github.com/gradio-app/gradio/security/advisories/GHSA-6qm2-wpxq-7qh2
• https://nvd.nist.gov/vuln/detail/CVE-2023-51449