Lfprojects: >> Mlflow >> 0.9.1 Security Vulnerabilities
Insufficient sanitization in MLflow leads to XSS when running a recipe that uses an untrusted dataset. This issue leads to a client-side RCE when running the recipe in Jupyter Notebook. The vulnerability stems from lack of sanitization over dataset table fields.
CVSS Score
7.5
EPSS Score
0.002
Published
2024-02-23
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.
CVSS Score
8.6
EPSS Score
0.026
Published
2023-12-20
A malicious user could use this issue to get command execution on the vulnerable machine and get access to data & models information.
CVSS Score
9.8
EPSS Score
0.015
Published
2023-12-20
This vulnerability is capable of writing arbitrary files into arbitrary locations on the remote filesystem in the context of the server process.
CVSS Score
8.8
EPSS Score
0.001
Published
2023-12-20
with only one user interaction(download a malicious config), attackers can gain full command execution on the victim system.
CVSS Score
9.0
EPSS Score
0.002
Published
2023-12-19
Path Traversal: '\..\filename' in GitHub repository mlflow/mlflow prior to 2.9.2.
CVSS Score
7.5
EPSS Score
0.857
Published
2023-12-18
Path Traversal: '\..\filename' in GitHub repository mlflow/mlflow prior to 2.9.2.
CVSS Score
8.1
EPSS Score
0.74
Published
2023-12-15
Path Traversal in GitHub repository mlflow/mlflow prior to 2.9.2.
CVSS Score
9.6
EPSS Score
0.024
Published
2023-12-13
Improper Neutralization of Special Elements Used in a Template Engine in GitHub repository mlflow/mlflow prior to 2.9.2.
CVSS Score
10.0
EPSS Score
0.003
Published
2023-12-12
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.
CVSS Score
6.5
EPSS Score
0.334
Published
2023-12-07