Localai

mudler/localai version 2.17.1 is vulnerable to a Timing Attack. This type of side-channel attack allows an attacker to compromise the cryptosystem by analyzing the time taken to execute cryptographic algorithms. Specifically, in the context of password handling, an attacker can determine valid login credentials based on the server's response time, potentially leading to unauthorized access.

Published: 2024-10-29T12:48:29.287Z
Updated: 2025-10-15T12:50:35.354Z

mudler/localai version 2.17.1 is vulnerable to remote code execution. The vulnerability arises because the localai backend receives inputs not only from the configuration file but also from other inputs, allowing an attacker to upload a binary file and execute malicious code. This can lead to the attacker gaining full control over the system.

Published: 2024-09-27T15:43:51.011Z
Updated: 2024-09-27T17:48:42.450Z

mudler/LocalAI version 2.17.1 allows for arbitrary file write due to improper handling of automatic archive extraction. When model configurations specify additional files as archives (e.g., .tar), these archives are automatically extracted after downloading. This behavior can be exploited to perform a 'tarslip' attack, allowing files to be written to arbitrary locations on the server, bypassing checks that normally restrict files to the models directory. This vulnerability can lead to remote code execution (RCE) by overwriting backend assets used by the server.

Published: 2024-10-29T12:46:54.732Z
Updated: 2025-10-15T12:49:47.751Z

A vulnerability in the /models/apply endpoint of mudler/localai versions 2.15.0 allows for Server-Side Request Forgery (SSRF) and partial Local File Inclusion (LFI). The endpoint supports both http(s):// and file:// schemes, where the latter can lead to LFI. However, the output is limited due to the length of the error message. This vulnerability can be exploited by an attacker with network access to the LocalAI instance, potentially allowing unauthorized access to internal HTTP(s) servers and partial reading of local files. The issue is fixed in version 2.17.

Published: 2024-07-06T17:48:46.735Z
Updated: 2024-08-01T21:33:03.282Z

A Cross-Site Request Forgery (CSRF) vulnerability exists in mudler/LocalAI versions up to and including 2.15.0, which allows attackers to trick victims into deleting installed models. By crafting a malicious HTML page, an attacker can cause the deletion of a model, such as 'gpt-4-vision-preview', without the victim's consent. The vulnerability is due to insufficient CSRF protection mechanisms on the model deletion functionality.

Published: 2024-07-06T08:38:02.339Z
Updated: 2024-08-01T21:18:06.438Z