Security Advisory

Autolabel

An attacker can craft a CSV file containing Python code in one of the values. This code must be wrapped in brackets to work i.e. []. The maliciously crafted CSV file can then be shared with a victim user as a dataset. When the user creates a classification task, the CSV is loaded and passed through a validation function, where values wrapped in brackets are passed into an eval function, which will execute the Python code contained within.

Autolabel

An attacker can craft a CSV file containing Python code in one of the values. This code must be wrapped in brackets to work i.e. []. The maliciously crafted CSV file can then be shared with a victim user as a dataset. When the user creates a multilabel classification task, the CSV is loaded and passed through a validation function, where values wrapped in brackets are passed into an eval function, which will execute the Python code contained within.

Cleanlab

An attacker can place a malicious file called datalabs.pkl within a directory and send that directory to a victim user. When the victim user loads the directory with Datalabs.load, the datalabs.pkl within it is deserialized and any arbitrary code contained within it is executed.

Guardrails

An attacker can craft an XML file with Python code contained within a ‘validators’ attribute. This code must be wrapped in braces to work, i.e. `{Python_code}`. This can then be passed to a victim user as a Guardrails file, and upon loading it, the Python code contained within the braces is passed into an eval function, which will execute the Python code contained within.

MindsDB

An attacker authenticated to a MindsDB instance with the Weaviate integration installed can execute arbitrary Python code on the server. This can be achieved by creating a database built with the Weaviate engine and running a ‘SELECT WHERE’ clause against it, containing the code to execute. This code is passed to an eval function used for parsing valid Python data types from arbitrary user input, but it will run any arbitrary Python code contained within the value given in the ‘WHERE embeddings =’ part of the clause.

MindsDB

An attacker authenticated to a MindsDB instance with any one of several integrations installed can execute arbitrary Python code on the server. This can be achieved by creating a database built with the specified integration engine and running an ‘UPDATE’ query against it, containing the code to execute. This code is passed to an eval function used for parsing valid Python data types from arbitrary user input but will run any arbitrary Python code contained within the value given in the ‘SET embeddings =’ part of the query.

MindsDB

An attacker authenticated to a MindsDB instance with the ChromaDB integration installed can execute arbitrary Python code on the server. This can be achieved by creating a database built with the ChromaDB engine and running an ‘INSERT’ query against it, where the value given for ‘metadata’ would contain the code to be executed. This code is passed to an eval function used for parsing valid Python data types from arbitrary user input but will run the arbitrary code contained within the query.

MindsDB

An attacker authenticated to a MindsDB instance with the SharePoint integration installed can execute arbitrary Python code on the server. This can be achieved by creating a database built with the SharePoint engine and running an ‘INSERT’ query against it to create a list, where the value given for the ‘list’ parameter would contain the code to be executed. This code is passed to an eval function used for parsing valid Python data types from arbitrary user input but will run the arbitrary code contained within the query.

MindsDB

An attacker authenticated to a MindsDB instance with the SharePoint integration installed can execute arbitrary Python code on the server. This can be achieved by creating a database built with the SharePoint engine and running an ‘INSERT’ query against it to create a site column, where the value given for the ‘text’ parameter would contain the code to be executed. This code is passed to an eval function used for parsing valid Python data types from arbitrary user input but will run the arbitrary code contained within the query.

MindsDB

An attacker authenticated to a MindsDB instance with the SharePoint integration installed can execute arbitrary Python code on the server. This can be achieved by creating a database built with the SharePoint engine and running an ‘INSERT’ query against it to create a list item, where the value given for the ‘fields’ parameter would contain the code to be executed. This code is passed to an eval function used for parsing valid Python data types from arbitrary user input but will run the arbitrary code contained within the query.

MindsDB

An attacker authenticated to a MindsDB instance can inject a malicious pickle object containing arbitrary code into a model during the Bring Your Own Model (BYOM) training and build process. This object will be deserialized when the model is loaded via a ‘predict’ or ‘describe’ query, executing the arbitrary code on the server.

MindsDB

An attacker authenticated to a MindsDB instance can inject a malicious pickle object containing arbitrary code into a model during the ‘inhouse’ Bring Your Own Model (BYOM) training and build process. This object will be deserialized when the model is loaded via the ‘predict’ method, executing the arbitrary code on the server. Note this can only occur if the BYOM engine is changed in the config from the default ‘venv’ to ‘inhouse’.

MindsDB

An attacker authenticated to a MindsDB instance can inject a malicious pickle object containing arbitrary code into a model during the ‘inhouse’ Bring Your Own Model (BYOM) training and build process. This object will be deserialized when the model is loaded via the ‘describe’ method, executing the arbitrary code on the server. Note this can only occur if the BYOM engine is changed in the config from the default ‘venv’ to ‘inhouse.’

MindsDB

An attacker authenticated to a MindsDB instance can inject a malicious pickle object containing arbitrary code into a model during the ‘inhouse’ Bring Your Own Model (BYOM) training and build process. This object will be deserialized when the model is loaded via the ‘finetune’ method, executing the arbitrary code on the server. Note this can only occur if the BYOM engine is changed in the config from the default ‘venv’ to ‘inhouse.’

MindsDB

An attacker authenticated to a MindsDB instance can create an ML Engine, database, project, or upload a dataset within the UI and give it a name (or value in the dataset) containing javascript code that will render when the items are enumerated within the UI.

LlamaIndex

An attacker can create a website with a prompt injection. Once a victim scrapes the website using the Evaporate integration, malicious code will execute on their system.

LlamaIndex

The safe_eval and safe_exec functions are intended to allow the user to run untrusted code in an eval or exec function while disallowing dangerous functions. However, an attacker can use 3rd party library functions to get arbitrary code execution.

Wyze Cam V4

A command injection vulnerability exists in Wyze Cam V4 firmware versions up to and including 4.52.4.9887. An attacker within Bluetooth range of the camera can leverage this command to execute arbitrary commands as root during the camera setup process.

Tensorflow Probability

An attacker can create a maliciously crafted HDF5 file by injecting a pickle object containing arbitrary code into the DistributionLambda layer of the model under the make_distribution_fn key, and share it with a victim. If the victim is using Tensorflow Probability v0.7 or later and loads the malicious model, the object will be deserialized and arbitrary code will execute on their system.

Skops

An attacker can create a malicious crafted model containing an OperatorFuncNode, and share it with a victim. If the victim is using Python 3.11 or later and loads the malicious model arbitrary code will execute on their system.

YData-profiling

An attacker can create a maliciously crafted pandas dataset and share it with a victim. Once a victim loads the dataset in Ydata-profiling, malicious code will execute on their system.

YData-profiling

An attacker can create a maliciously crafted Ydata-profiling html report containing malicious code. Once a victim browses to the report and views it, malicious code will execute in their browser.

YData-profiling

An attacker can create a maliciously crafted Ydata-profiling report containing malicious code and share it with a victim. When the victim loads the report, the code will be executed on their system.

MLflow

An attacker can package an MLflow Project where the main entrypoint command set in the MLproject file contains malicious code (or an operating system appropriate command), and share it with a victim. When the victim runs the project, the command will be executed on their system.

MLflow

An attacker can create an MLProject Recipe containing a malicious pickle file and a Python file that calls BaseCard.load on it and share it with a victim. When the victim runs mlflow run against the Recipe directory, the pickle file will be deserialized on their system, running any arbitrary code it contains.

MLflow

An attacker can inject a malicious pickle object into a Pytorch model file and log it to the MLflow tracking server via the API using the model.pytorch.log_model function. When a victim user calls the mlflow.pytorch.load_model function on the model, the pickle object is deserialized on their system, running any arbitrary code it contains.

MLflow

An attacker can inject a malicious pickle object during the process of creating a Langhchain model and log the model to the MLflow tracking server via the API using the model.langchain.log_model function. When a victim user calls the mlflow.langchain.load_model function on the model, the pickle object is deserialized on their system, running any arbitrary code it contains.

MLflow

An attacker can inject a malicious pickle object into a Tensorflow model file and log it to the MLflow tracking server via the API using the model.tensorflow.log_model function. When a victim user calls the mlflow.tensorflow.load_model function on the model, the pickle object is deserialized on their system, running any arbitrary code it contains.

MLflow

An attacker can inject a malicious pickle object into a LightGBM scikit-learn model file and log it to the MLflow tracking server via the API using the model.lightgbm.log_model function. When a victim user calls the mlflow.lightgbm.load_model function on the model, the pickle object is deserialized on their system, running any arbitrary code it contains.

MLflow

An attacker can inject a malicious pickle object into a pmdarima model file and log it to the MLflow tracking server via the API using the model.pmdarima.log_model function. When a victim user calls the mlflow.pmdarima.load_model function on the model, the pickle object is deserialized on their system, running any arbitrary code it contains.

MLflow

An attacker can inject a malicious pickle object into a model file and log it to the MLflow tracking server via the API using the model.pyfunc.log_model function. When a victim user calls the mlflow.pyfunc.load_model function on the model, the pickle object is deserialized on their system, running any arbitrary code it contains.

MLflow

An attacker can inject a malicious pickle object into a scikit-learn model file and log it to the MLflow tracking server via the API. When a victim user calls the mlflow.sklearn.load_model function on the model, the pickle file is deserialized on their system, running any arbitrary code it contains.

MLflow

An attacker can inject a malicious pickle object into a scikit-learn model file and log it to the MLflow tracking server via the API. When a victim user calls the mlflow.sklearn.load_model function on the model, the pickle file is deserialized on their system, running any arbitrary code it contains.

AWS Sagemaker

A command injection vulnerability exists inside the capture_dependencies function of the AWS Sagemakers util file. If a user used the util function when creating their code, an attacker can leverage the vulnerability to run arbitrary commands on a system running the code by injecting a system command into the string passed to the function.

AWS Sagemaker

An attacker can inject a malicious pickle object into a numpy file and share it with a victim user. When the victim uses the NumpyDeserializer.deserialize function of the base_deserializers python file to load it, the allow_pickle optional argument can be set to ‘false’ and passed to np.load, leading to the safe loading of the file. However, by default the optional parameter was set to true, so if this is not specifically changed by the victim, this will result in the loading and execution of the malicious pickle object.

R

An attacker could leverage the R Data Serialization format to insert arbitrary code into an RDS formatted file, or an R package as an RDX or RDB component, which will be executed when referenced or called with ReadRDS. This is because of the lazy evaluation process used in the unserialize function of the R programming language.

ONNX

An attacker can create a malicious onnx model which fails an assert statement in a way that an error string equal to or greater than 2048 characters is printed out and share it with a victim. When the victim tries to load the onnx model a string is created which leaks program memory.

ONNX

An attacker can create a malicious onnx model containing paths to externally located tensors and share it with a victim. When the victim tries to load the externally located tensors a directory traversal attack can occur leading to an arbitrary read on a victim’s system leading to information disclosure.

ClearML

An attacker could retrieve ClearML user information and credentials using a tool such as mongosh if they have access to the server. This is because the open-source version of the ClearML Server MongoDB instance lacks access control and stores user information and credentials in plaintext.

ClearML

An attacker can provide a URL rather than uploading an image to the Debug Samples tab of an Experiment. If the URL has the extension .html, the web server retrieves the HTML page, which is assumed to contain trusted data. The HTML is marked as safe and rendered on the page, resulting in arbitrary JavaScript running in any user’s browser when they view the samples tab.

ClearML

An attacker can craft a malicious web page that triggers a CSRF when visited. When a user browses to the malicious web page a request is sent which can allow an attacker to fully compromise a user’s account.

ClearML

An attacker can, due to lack of authentication, arbitrarily upload, delete, modify, or download files on the fileserver, even if the files belong to another user.

ClearML

An attacker can upload or modify a dataset containing a link pointing to an arbitrary file and a target file path. When a user interacts with this dataset, such as when using the Dataset.squash method, the file is written to the target path on the user’s system.