CVE-2024-6095 Scanner

The LocalAI platform, developed by Mudler, provides a powerful tool for AI model management and deployment. It is widely used by developers and organizations to streamline their AI workflows. The platform allows users to apply and manage various machine learning models seamlessly. Given its capability to handle sensitive data, security is paramount for its users. Detecting vulnerabilities ensures that users can maintain the integrity and confidentiality of their AI applications.

The Local File Inclusion (LFI) vulnerability in LocalAI allows attackers to access internal files on the server. Specifically, the vulnerability exists in the /models/apply endpoint, which supports both HTTP(S) and file schemes. When exploited, this vulnerability can lead to unauthorized access to sensitive data. The issue has been addressed in version 2.17, emphasizing the importance of updating to maintain security.

The LFI vulnerability is present in the /models/apply endpoint, which processes requests containing URLs. An attacker can exploit this by crafting a request with a file URL, such as file:///etc/passwd. The endpoint responds with an error message, potentially leaking information about the file's content. Although the output is limited, attackers can gain insights into the server's file structure. This can lead to further attacks if sensitive files are accessible.

If exploited, the LFI vulnerability can allow attackers to read sensitive files on the server, compromising user data and internal configurations. This could lead to unauthorized access to system resources or sensitive information. Additionally, it may serve as a stepping stone for further attacks against the LocalAI instance or other connected systems. The resulting data exposure can significantly harm the organization's security posture.

By becoming a member of the S4E platform, you gain access to advanced security scanning tools that identify vulnerabilities like LFI in your systems. Our comprehensive threat exposure management services provide real-time insights into potential risks, helping you stay ahead of attackers. With our expertise, you can enhance your cybersecurity measures and ensure your digital assets are protected. Join us today to safeguard your applications and maintain the trust of your users.

References:

• https://github.com/fkie-cad/nvd-json-data-feeds
• https://github.com/sev-hack/sev-hack
• https://nvd.nist.gov/vuln/detail/CVE-2024-6095