CVE-2024-4325 Scanner

Gradio is a Python library and web application used by developers to quickly create web applications and demos for machine learning models. It's widely adopted in the AI community for sharing, testing, and interacting with models via a user-friendly interface. The platform supports integrations with various machine-learning frameworks and is used by researchers and companies to demonstrate AI capabilities publicly. Gradio provides a simplified interface for non-technical users to interact with machine learning models. The tool is often used in real-time settings, such as hackathons, conferences, and educational workshops. Overall, Gradio is known for its ease of use, flexibility, and ability to serve complex AI models to a broader audience.

A Server-Side Request Forgery (SSRF) vulnerability allows an attacker to make unauthorized requests from the server where an application is hosted. The vulnerability can be exploited if an application fetches remote resources without sufficient input validation. This can lead to sensitive information disclosure, such as internal IP addresses or metadata access. SSRF is particularly concerning because it may allow an attacker to target internal services that are not otherwise reachable from the outside. In the case of Gradio, this vulnerability exists in the `save_url_to_cache` function. Exploiting it could lead to compromise of confidential server resources and data.

The vulnerability in Gradio occurs within the `/queue/join` endpoint where the `path` parameter is processed. This parameter is expected to contain a URL and is trusted without sufficient validation. Attackers can manipulate this endpoint by passing external URLs, tricking the application into making requests to unwanted destinations. As a result, an attacker could redirect these requests to internal or otherwise sensitive resources on the network. Additionally, it's possible to target cloud provider metadata endpoints, which might lead to further exploitation or data exfiltration. This lack of adequate validation of input data sets the stage for potential misuse by malicious actors.

Exploitation of this SSRF vulnerability can have severe consequences, such as gaining unauthorized access to internal systems and data. If attackers access the AWS metadata endpoint, they could retrieve sensitive credentials or configurations that enable further attacks. Internal network scanning can also occur, revealing more about the network's internal structure and potentially opening the door to other attacks. The integrity and confidentiality of the victim's system and data can be severely compromised. This underscores the need for immediate attention to patch and secure systems vulnerable to this exploit.

REFERENCES

• https://github.com/advisories/GHSA-973g-55hp-3frw
• https://nvd.nist.gov/vuln/detail/CVE-2024-4325