CVE-2024-24779 Apache Superset: Improper data authorization when creating a new dataset

Apache Superset with custom roles that include can write on dataset and without all data access permissions, allows for users to create virtual datasets to data they don't have access to. These users could then use those virtual datasets to get access to unauthorized data. This issue affects Apac...

PT-2024-20556

Name of the Vulnerable Software and Affected Versions Apache Superset versions prior to 3.0.4 Apache Superset versions 3.1.0 through 3.1.0 Description The issue allows users with custom roles that include can write on dataset and without all data access permissions to create virtual datasets to...

Cross Site Scripting (XSS)

mlflow is vulnerable to Cross Site Scripting XSS. The vulnerability is due to insufficient sanitization while executing a recipe with an untrusted dataset, which results in client-side RCE in the Jupyter Notebook...

MLFlow Cross-site Scripting vulnerability leads to client-side Remote Code Execution

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...

GHSA-3V79-Q7PH-J75H MLFlow Cross-site Scripting vulnerability leads to client-side Remote Code Execution

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...

PYSEC-2024-241

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...

CVE-2024-27133

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...

PYSEC-2024-241

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...

Design/Logic Flaw

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...

CVE-2024-27133 Insufficient sanitization in MLflow leads to XSS when running a recipe that uses an untrusted dataset.

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...

CVE-2024-27133 Insufficient sanitization in MLflow leads to XSS when running a recipe that uses an untrusted dataset.

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...

CVE-2024-27133

CVE-2024-27133 : Affects MLflow. Insufficient sanitization of dataset table fields in MLflow recipes can cause a client-side XSS, which in turn can lead to a client-side RCE when running the recipe in Jupyter Notebook . Root cause: lack of input sanitization for untrusted datasets in the data tab...

CVE-2024-27133 Insufficient sanitization in MLflow leads to XSS when running a recipe that uses an untrusted dataset.

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...

PT-2024-21666 · Mlflow · Mlflow

The issue is with MLflow, which has a problem with insufficient sanitization, leading to XSS when running a recipe that uses an untrusted dataset. This can further result in a client-side RCE when the recipe is run in Jupyter Notebook. The affected software is MLflow, and the issue arises from a...

Mlflow Cross-Site Scripting Vulnerability

Mlflow is an open source platform for machine learning lifecycle. Mlflow suffers from a cross-site scripting vulnerability that stems from a lack of cleanup of dataset table fields, leading to cross-site scripting...

Allegro AI ClearML path traversal vulnerability

A path traversal vulnerability in versions 1.4.0 to 1.14.1 of the client SDK of Allegro AI’s ClearML platform enables a maliciously uploaded dataset to write local or remote files to an arbitrary location on an end user’s system when interacted with...

GHSA-M95H-P4GG-WFW3 Allegro AI ClearML path traversal vulnerability

A path traversal vulnerability in versions 1.4.0 to 1.14.1 of the client SDK of Allegro AI’s ClearML platform enables a maliciously uploaded dataset to write local or remote files to an arbitrary location on an end user’s system when interacted with...

Path traversal

A path traversal vulnerability in versions 1.4.0 to 1.14.1 of the client SDK of Allegro AI’s ClearML platform enables a maliciously uploaded dataset to write local or remote files to an arbitrary location on an end user’s system when interacted with...

CVE-2024-24591

A path traversal vulnerability in versions 1.4.0 to 1.14.1 of the client SDK of Allegro AI’s ClearML platform enables a maliciously uploaded dataset to write local or remote files to an arbitrary location on an end user’s system when interacted with...

CVE-2024-24591

A path traversal vulnerability in versions 1.4.0 to 1.14.1 of the client SDK of Allegro AI’s ClearML platform enables a maliciously uploaded dataset to write local or remote files to an arbitrary location on an end user’s system when interacted with...