Total
6 CVE
| CVE | Vendors | Products | Updated | CVSS v2 | CVSS v3 |
|---|---|---|---|---|---|
| CVE-2024-3135 | 1 Mudler | 1 Localai | 2025-06-27 | N/A | 6.5 MEDIUM |
| A Cross-Site Request Forgery (CSRF) vulnerability exists in the mudler/localai application, allowing attackers to craft malicious webpages that, when visited by a victim, perform unauthorized actions on the victim's local LocalAI instance without their consent. This vulnerability enables attackers to exhaust system resources, consume credits, and fill disk space by making numerous resource-intensive API calls, such as generating images or uploading files. The vulnerability stems from the application's acceptance of simple request content-types without requiring CSRF tokens or implementing other CSRF mitigation measures. Successful exploitation does not require network access to the vulnerable LocalAI environment. | |||||
| CVE-2024-9900 | 1 Mudler | 1 Localai | 2025-04-04 | N/A | 6.1 MEDIUM |
| mudler/localai version v2.21.1 contains a Cross-Site Scripting (XSS) vulnerability in its search functionality. The vulnerability arises due to improper sanitization of user input, allowing the injection and execution of arbitrary JavaScript code. This can lead to the execution of malicious scripts in the context of the victim's browser, potentially compromising user sessions, stealing session cookies, redirecting users to malicious websites, or manipulating the DOM. | |||||
| CVE-2024-6095 | 1 Mudler | 1 Localai | 2024-11-21 | N/A | 5.8 MEDIUM |
| 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. | |||||
| CVE-2024-5182 | 1 Mudler | 1 Localai | 2024-11-21 | N/A | 9.1 CRITICAL |
| A path traversal vulnerability exists in mudler/localai version 2.14.0, where an attacker can exploit the `model` parameter during the model deletion process to delete arbitrary files. Specifically, by crafting a request with a manipulated `model` parameter, an attacker can traverse the directory structure and target files outside of the intended directory, leading to the deletion of sensitive data. This vulnerability is due to insufficient input validation and sanitization of the `model` parameter. | |||||
| CVE-2024-7010 | 1 Mudler | 1 Localai | 2024-11-14 | N/A | 5.9 MEDIUM |
| 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. | |||||
| CVE-2024-6868 | 1 Mudler | 1 Localai | 2024-11-13 | N/A | 9.8 CRITICAL |
| 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. | |||||