Unrestricted Upload of File with Dangerous Type

This vulnerability is capable of writing arbitrary files into arbitrary locations on the remote filesystem in the context of the server process.

Path Traversal: '\..\filename'

A malicious user could use this issue to get command execution on the vulnerable machine and get access to data & models information.

Server-Side Request Forgery (SSRF)

A malicious user could use this issue to access internal HTTP(s) servers and in the worst case (ie: aws instance) it could be abuse to get a remote code execution on the victim machine.

Path Traversal: '\..\filename' in mlflow/mlflow

Path Traversal: '\..\filename' in GitHub repository mlflow/mlflow prior to 2.9.2.

Path Traversal: '\..\filename' in mlflow/mlflow

Path Traversal: '\..\filename' in GitHub repository mlflow/mlflow prior to 2.9.2.

Path Traversal in mlflow/mlflow

Path Traversal in GitHub repository mlflow/mlflow prior to 2.9.2.

Improper Neutralization of Special Elements Used in a Template Engine in mlflow/mlflow

Improper Neutralization of Special Elements Used in a Template Engine in GitHub repository mlflow/mlflow prior to 2.9.2.

Reflected XSS via Content-Type Header in mlflow/mlflow

A reflected Cross-Site Scripting (XSS) vulnerability exists in the mlflow/mlflow repository, specifically within the handling of the Content-Type header in POST requests. An attacker can inject malicious JavaScript code into the Content-Type header, which is then improperly reflected back to the user without adequate sanitization or escaping, leading to arbitrary JavaScript execution in the context of the victim's browser. The vulnerability is present in the mlflow/server/auth/__init__.py file, where the user-supplied Content-Type header is directly injected into a Python formatted string and returned to the user, facilitating the XSS attack.

MLflow Arbitrary File Write

An attacker can overwrite any file on the server hosting MLflow without any authentication.

MLflow Arbitrary File Upload

MLflow allowed arbitrary files to be PUT onto the server.

MLflow Authentication Bypass

An attacker is able to arbitrarily create an account in MLflow bypassing any authentication requirment.

OS Command Injection in mlflow/mlflow

OS Command Injection in GitHub repository mlflow/mlflow prior to 2.6.0.

An issue in MLFlow versions 2.8.1 and before allows a remote attacker to obtain sensitive information via a crafted request to REST API.

Absolute Path Traversal in mlflow/mlflow

Absolute Path Traversal in GitHub repository mlflow/mlflow prior to 2.5.0.

Apptainer's ineffective privileges drop when requesting container network

Apptainer is an open source container platform. Version 1.2.0-rc.2 introduced an ineffective privilege drop when requesting container network setup, therefore subsequent functions are called with root privileges, the attack surface is rather limited for users but an attacker could possibly craft a starter config to delete any directory on the host filesystems. A security fix has been included in Apptainer 1.2.1. There is no known workaround outside of upgrading to Apptainer 1.2.1.

Insecure Temporary File in mlflow/mlflow

Insecure Temporary File in GitHub repository mlflow/mlflow prior to 1.23.1.