CVE-2024-37061

Remote Code Execution can occur in versions of the MLflow platform running version 1.11.0 or newer, enabling a maliciously crafted MLproject to execute arbitrary code on an end user’s system when run.

CVE-2023-1177

Path Traversal: '..\filename' in GitHub repository mlflow/mlflow prior to 2.2.1.

CVE-2022-0736

Insecure Temporary File in GitHub repository mlflow/mlflow prior to 1.23.1.

CVE-2024-3848

A path traversal vulnerability exists in mlflow/mlflow version 2.11.0, identified as a bypass for the previously addressed CVE-2023-6909. The vulnerability arises from the application's handling of artifact URLs, where a '#' character can be used to insert a path into the fragment, effectively skip...

CVE-2023-6909

Path Traversal: '..\filename' in GitHub repository mlflow/mlflow prior to 2.9.2.

CVE-2024-27134

Excessive directory permissions in MLflow leads to local privilege escalation when using spark_udf. This behavior can be exploited by a local attacker to gain elevated permissions by using a ToCToU attack. The issue is only relevant when the spark_udf() MLflow API is called.

CVE-2024-27132

Insufficient sanitization in MLflow leads to XSS when running an untrusted recipe. This issue leads to a client-side RCE when running an untrusted recipe in Jupyter Notebook. The vulnerability stems from lack of sanitization over template variables.

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-2023-1176

Absolute Path Traversal in GitHub repository mlflow/mlflow prior to 2.2.2.

CVE-2023-2356

Relative Path Traversal in GitHub repository mlflow/mlflow prior to 2.3.1.

CVE-2025-1474

In mlflow/mlflow version 2.18, an admin is able to create a new user account without setting a password. This vulnerability could lead to security risks, as accounts without passwords may be susceptible to unauthorized access. Additionally, this issue violates best practices for secure user account...

CVE-2023-6568

A reflected Cross-Site Scripting (XSS) vulnerability exists in the mlflow/mlflow repository, specifically within the handling of the Content-Type header in POST requests. An attacker can inject malicious JavaScript code into the Content-Type header, which is then improperly reflected back to the us...

CVE-2023-2780

Path Traversal: '..\filename' in GitHub repository mlflow/mlflow prior to 2.3.1.

CVE-2024-0520

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 sc...

CVE-2024-1483

A path traversal vulnerability exists in mlflow/mlflow version 2.9.2, allowing attackers to access arbitrary files on the server. By crafting a series of HTTP POST requests with specially crafted 'artifact_location' and 'source' parameters, using a local URI with '#' instead of '?', an attacker can...

CVE-2023-6977

This vulnerability enables malicious users to read sensitive files on the server.

CVE-2023-30172

A directory traversal vulnerability in the /get-artifact API method of the mlflow platform up to v2.0.1 allows attackers to read arbitrary files on the server via the path parameter.

CVE-2024-2928

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 ...

CVE-2023-3765

Absolute Path Traversal in GitHub repository mlflow/mlflow prior to 2.5.0.

CVE-2024-1594

A path traversal vulnerability exists in the mlflow/mlflow repository, specifically within the handling of the artifact_location parameter when creating an experiment. Attackers can exploit this vulnerability by using a fragment component # in the artifact location URI to read arbitrary files on th...

CVE-2024-4263

A broken access control vulnerability exists in mlflow/mlflow versions before 2.10.1, where low privilege users with only EDIT permissions on an experiment can delete any artifacts. This issue arises due to the lack of proper validation for DELETE requests by users with EDIT permissions, allowing t...

CVE-2024-1560

A path traversal vulnerability exists in the mlflow/mlflow repository, specifically within the artifact deletion functionality. Attackers can bypass path validation by exploiting the double decoding process in the _delete_artifact_mlflow_artifacts handler and local_file_uri_to_path function, allowi...

CVE-2024-3573

mlflow/mlflow is vulnerable to Local File Inclusion (LFI) due to improper parsing of URIs, allowing attackers to bypass checks and read arbitrary files on the system. The issue arises from the 'is_local_uri' function's failure to properly handle URIs with empty or 'file' schemes, leading to the mis...

CVE-2023-6014

An attacker is able to arbitrarily create an account in MLflow bypassing any authentication requirment.

CVE-2023-6831

Path Traversal: '..\filename' in GitHub repository mlflow/mlflow prior to 2.9.2.

CVE-2023-6015

MLflow allowed arbitrary files to be PUT onto the server.

CVE-2024-1558

A path traversal vulnerability exists in the _create_model_version() function within server/handlers.py of the mlflow/mlflow repository, due to improper validation of the source parameter. Attackers can exploit this vulnerability by crafting a source parameter that bypasses the _validate_non_local_...

CVE-2024-1593

A path traversal vulnerability exists in the mlflow/mlflow repository due to improper handling of URL parameters. By smuggling path traversal sequences using the ';' character in URLs, attackers can manipulate the 'params' portion of the URL to gain unauthorized access to files or directories. This...

CVE-2025-1473

A Cross-Site Request Forgery (CSRF) vulnerability exists in the Signup feature of mlflow/mlflow versions 2.17.0 to 2.20.1. This vulnerability allows an attacker to create a new account, which may be used to perform unauthorized actions on behalf of the malicious user.

CVE-2023-4033

OS Command Injection in GitHub repository mlflow/mlflow prior to 2.6.0.

CVE-2023-6974

A malicious user could use this issue to access internal HTTP(s) servers and in the worst case (ie: aws instance) it could be abuse to get a remote code execution on the victim machine.

CVE-2023-6940

with only one user interaction(download a malicious config), attackers can gain full command execution on the victim system.

CVE-2023-6753

Path Traversal in GitHub repository mlflow/mlflow prior to 2.9.2.

CVE-2023-43472

An issue in MLFlow versions 2.8.1 and before allows a remote attacker to obtain sensitive information via a crafted request to REST API.

CVE-2023-6975

A malicious user could use this issue to get command execution on the vulnerable machine and get access to data & models information.

CVE-2023-6709

Improper Neutralization of Special Elements Used in a Template Engine in GitHub repository mlflow/mlflow prior to 2.9.2.

CVE-2024-37059

Deserialization of untrusted data can occur in versions of the MLflow platform running version 0.5.0 or newer, enabling a maliciously uploaded PyTorch model to run arbitrary code on an end user’s system when interacted with.

CVE-2024-37054

Deserialization of untrusted data can occur in versions of the MLflow platform running version 0.9.0 or newer, enabling a maliciously uploaded PyFunc model to run arbitrary code on an end user’s system when interacted with.

CVE-2023-6976

This vulnerability is capable of writing arbitrary files into arbitrary locations on the remote filesystem in the context of the server process.

CVE-2024-37056

Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.23.0 or newer, enabling a maliciously uploaded LightGBM scikit-learn model to run arbitrary code on an end user’s system when interacted with.

CVE-2024-37057

Deserialization of untrusted data can occur in versions of the MLflow platform running version 2.0.0rc0 or newer, enabling a maliciously uploaded Tensorflow model to run arbitrary code on an end user’s system when interacted with.

CVE-2024-37060

Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.27.0 or newer, enabling a maliciously crafted Recipe to execute arbitrary code on an end user’s system when run.

CVE-2024-37052

Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.1.0 or newer, enabling a maliciously uploaded scikit-learn model to run arbitrary code on an end user’s system when interacted with.

CVE-2024-37058

Deserialization of untrusted data can occur in versions of the MLflow platform running version 2.5.0 or newer, enabling a maliciously uploaded Langchain AgentExecutor model to run arbitrary code on an end user’s system when interacted with.

CVE-2024-37053

Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.1.0 or newer, enabling a maliciously uploaded scikit-learn model to run arbitrary code on an end user’s system when interacted with.

CVE-2024-37055

Deserialization of untrusted data can occur in versions of the MLflow platform running version 1.24.0 or newer, enabling a maliciously uploaded pmdarima model to run arbitrary code on an end user’s system when interacted with.

CVE-2025-52967

gateway_proxy_handler in MLflow before 3.1.0 lacks gateway_path validation.