OS Command Injection

github.com/fluid-cloudnative/fluid is vulnerable to OS Command Injection. The vulnerability is due to insufficient input validation within the JuicefsRuntime, allowing an authenticated user with the authority to create or update the K8s CRD Dataset/JuicefsRuntime to execute arbitrary OS commands...

CVE-2023-51699

Summary: CVE-2023-51699 affects Fluid’s JuicefsRuntime within the Fluid project, enabling OS command injection by an authenticated user with authority to create/update the K8s CRD datasets/ JuicefsRuntime. What is affected: Fluid (open source Kubernetes-native Distributed Dataset Orchestrator) an...

Fluid vulnerable to OS Command Injection for Fluid Users with JuicefsRuntime

Impact OS command injection vulnerability within the Fluid project's JuicefsRuntime can potentially allow an authenticated user, who has the authority to create or update the K8s CRD Dataset/JuicefsRuntime, to execute arbitrary OS commands within the juicefs related containers. This could lead to...

GHSA-WX8Q-4GM9-RJ2G Fluid vulnerable to OS Command Injection for Fluid Users with JuicefsRuntime

Impact OS command injection vulnerability within the Fluid project's JuicefsRuntime can potentially allow an authenticated user, who has the authority to create or update the K8s CRD Dataset/JuicefsRuntime, to execute arbitrary OS commands within the juicefs related containers. This could lead to...

MAI-2024-0065

The ImgTrojan attack represents a sophisticated data poisoning strategy targeting Vision-Language Models VLMs. This method enables adversaries to circumvent built-in safety protocols by introducing a minimal number of maliciously designed image-caption pairs into the training dataset. These...

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. 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 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...

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...