Preface: Large language models (LLM) are very large deep learning models that are pre-trained on vast amounts of data. The underlying transformer is a set of neural networks that consist of an encoder and a decoder with self-attention capabilities.

The key feature of a multimodal model is its ability to integrate and interpret information from these different data sources, often simultaneously. These can be understood as more advanced versions of large language models (LLMs) that can work not only on text but diverse data types.

Background:

1.Activate the environment

conda activate lollms

2.Install cudatoolkit

conda install -c anaconda cudatoolkit

3.Install lollms

pip install –upgrade lollms

4.Lord of Large Language Models (LoLLMs) are ready

Vulnerability details: CVE-2024-5443: CVE-2024-4320 describes a vulnerability in the parisneo/lollms software, specifically within the ExtensionBuilder().build_extension() function.
The vulnerability arises from the /mount_extension endpoint, where a path traversal issue allows attackers to navigate beyond the intended directory structure. This is facilitated by the data.category and data.folder parameters accepting empty strings (“”), which, due to inadequate input sanitization, can lead to the construction of a package_path that points to the root directory.
Consequently, if an attacker can create a config.yaml file in a controllable path, this path can be appended to the extensions list and trigger the execution of init.py in the current directory, leading to remote code execution. The vulnerability affects versions from 5.9.0, and has been addressed in version 9.5.1.

Official announcement: For detail, please refer to link – https://nvd.nist.gov/vuln/detail/CVE-2024-5443