Use of Web Browser Cache Containing Sensitive Information vulnerability in Apache Airflow.  Airflow did not return "Cache-Control" header for dynamic content, which in case of some browsers could result in potentially storing sensitive data in local cache of the browser. This issue affects Apache Airflow: before 2.9.2. Users are recommended to upgrade to version 2.9.2, which fixes the issue.

Langflow through 0.6.19 allows remote code execution if untrusted users are able to reach the "POST /api/v1/custom_component" endpoint and provide a Python script.

kubeflow/kubeflow is vulnerable to a Regular Expression Denial of Service (ReDoS) attack due to inefficient regular expression complexity in its email validation mechanism. An attacker can remotely exploit this vulnerability without authentication by providing specially crafted input that causes the application to consume an excessive amount of CPU resources. This vulnerability affects the latest version of kubeflow/kubeflow, specifically within the centraldashboard-angular backend component. The impact of exploiting this vulnerability includes resource exhaustion, and service disruption.

A vulnerability in mlflow/mlflow version 2.11.1 allows attackers to create multiple models with the same name by exploiting URL encoding. This flaw can lead to Denial of Service (DoS) as an authenticated user might not be able to use the intended model, as it will open a different model each time. Additionally, an attacker can exploit this vulnerability to perform data model poisoning by creating a model with the same name, potentially causing an authenticated user to become a victim by using the poisoned model. The issue stems from inadequate validation of model names, allowing for the creation of models with URL-encoded names that are treated as distinct from their URL-decoded counterparts.

OneFlow-Inc. Oneflow v0.9.1 does not display an error or warning when the oneflow.eye parameter is floating.

Improper input validation in OneFlow-Inc. Oneflow v0.9.1 allows attackers to cause a Denial of Service (DoS) via inputting negative values into the oneflow.zeros/ones parameter.

A Local File Inclusion (LFI) vulnerability was identified in mlflow/mlflow, specifically in version 2.9.2, which was fixed in version 2.11.3. This vulnerability arises from the application's failure to properly validate URI fragments for directory traversal sequences such as '../'. An attacker can exploit this flaw by manipulating the fragment part of the URI to read arbitrary files on the local file system, including sensitive files like '/etc/passwd'. The vulnerability is a bypass to a previous patch that only addressed similar manipulation within the URI's query string, highlighting the need for comprehensive validation of all parts of a URI to prevent LFI attacks.

A vulnerability in mlflow/mlflow version 8.2.1 allows for remote code execution due to improper neutralization of special elements used in an OS command ('Command Injection') within the `mlflow.data.http_dataset_source.py` module. Specifically, when loading a dataset from a source URL with an HTTP scheme, the filename extracted from the `Content-Disposition` header or the URL path is used to generate the final file path without proper sanitization. This flaw enables an attacker to control the file path fully by utilizing path traversal or absolute path techniques, such as '../../tmp/poc.txt' or '/tmp/poc.txt', leading to arbitrary file write. Exploiting this vulnerability could allow a malicious user to execute commands on the vulnerable machine, potentially gaining access to data and model information. The issue is fixed in version 2.9.0.

An issue in OneFlow-Inc. Oneflow v0.9.1 allows attackers to cause a Denial of Service (DoS) via inputting a negative value into the oneflow.index_select parameter.

An issue in the oneflow.permute component of OneFlow-Inc. Oneflow v0.9.1 causes an incorrect calculation when the same dimension operation is performed.