Leo Ring

An arbitrary code execution issue exists due to the way the Guardrails AI Guardrails framework validates XML files. If a maliciously crafted XML file containing Python code is loaded, the code will be executed on the user's machine because it is passed to an eval function.

An arbitrary code execution issue exists due to the way multilabel classification tasks handle provided CSV files. If a user creates a multilabel classification task using a maliciously crafted CSV file containing Python code, the code will be passed to an `eval` function which executes it.

Name of the Vulnerable Software and Affected Versions: MindsDB versions 23.10.2.0 and newer Description: The issue concerns the deserialization of untrusted data in the MindsDB platform. This allows a maliciously uploaded 'inhouse' model to run arbitrary code on the server when used for a prediction. Recommendations: For versions 23.10.2.0 and newer, consider disabling the deserialization of untrusted data until a patch is available. Restrict access to the 'inhouse' model upload feature to minimize the risk of exploitation. Avoid using the affected versions for prediction tasks that involve untrusted models. At the moment, there is no information about a newer version that contains a fix for this vulnerability.

Name of the Vulnerable Software and Affected Versions: MindsDB versions 23.10.3.0 and newer Description: The issue is related to the deserialization of untrusted data in the MindsDB platform. This allows a maliciously uploaded 'inhouse' model to run arbitrary code on the server when a 'describe' query is run on it. Recommendations: For MindsDB versions 23.10.3.0 and newer, consider disabling the deserialization of untrusted data as a temporary workaround until a patch is available. Restrict access to the 'describe' query functionality to minimize the risk of exploitation. At the moment, there is no information about a newer version that contains a fix for this vulnerability.

Name of the Vulnerable Software and Affected Versions: MindsDB versions 23.10.2.0 and newer Description: The issue concerns the deserialization of untrusted data in the MindsDB platform. This allows a maliciously uploaded 'inhouse' model to run arbitrary code on the server when using 'finetune' on it. The vulnerability is remotely exploitable. Recommendations: For MindsDB versions 23.10.2.0 and newer, consider disabling the 'finetune' functionality for 'inhouse' models until a patch is available to prevent arbitrary code execution. Restrict the upload of 'inhouse' models to trusted sources to minimize the risk of exploitation. As a temporary workaround, review and enhance the security posture of the MindsDB platform to prevent deserialization of untrusted data.

Name of the Vulnerable Software and Affected Versions: MindsDB (affected versions not specified) Description: A cross-site scripting (XSS) issue exists, enabling the execution of a JavaScript payload whenever a user enumerates an ML Engine, database, project, or dataset containing arbitrary JavaScript code within the web UI. This allows a JavaScript payload to run when a user views certain elements in the web UI. Recommendations: At the moment, there is no information about a newer version that contains a fix for this vulnerability.

An arbitrary code execution issue exists due to the way the Refuel Autolabel library handles provided CSV files in its classification tasks. If a maliciously crafted CSV file containing Python code is used to create a classification task, the code will be executed by an `eval` function.

An arbitrary code execution issue exists when the Microsoft SharePoint integration is installed on the server. For databases created with the SharePoint engine, a specially crafted `INSERT` query containing Python code can be used to execute code on the server. This occurs because the code is passed to an `eval` function. The vulnerability is related to incorrect code generation management in the `eval` function of the MindsDB platform, allowing a remote attacker to execute arbitrary code by injecting a specially crafted `INSERT` query.