Sicherheitslücken in mlflow · Seite 4

Path Traversal Vulnerability in mlflow/mlflow

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 traverse the server's directory structure. The issue occurs due to insufficient validation of user-supplied input in the server's handlers.

• Auf 2.12.1 aktualisieren

Path Traversal Vulnerability in mlflow/mlflow

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, allowing for the deletion of arbitrary directories on the server's filesystem. This vulnerability is due to an extra unquote operation in the `delete_artifacts` function of `local_artifact_repo.py`, which fails to properly sanitize user-supplied paths. The issue is present up to version 2.9.2, despite attempts to fix a similar issue in CVE-2023-6831.

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.

• Auf 2.10.0 aktualisieren

Insufficient sanitization in MLflow leads to XSS when running an untrusted recipe.

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.

• Auf 2.10.0 aktualisieren

Path Traversal: '\..\filename'

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

• Auf 2.9.2 aktualisieren

Unrestricted Upload of File with Dangerous Type

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

• Auf 2.9.2 aktualisieren

Path Traversal: '\..\filename'

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

• Auf 2.9.2 aktualisieren

Server-Side Request Forgery (SSRF)

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.

• Auf 2.9.2 aktualisieren

Command Injection

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

• Auf 2.9.2 aktualisieren

Path Traversal: '\..\filename' in mlflow/mlflow

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

• Auf 2.9.2 aktualisieren

Path Traversal: '\..\filename' in mlflow/mlflow

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

• Auf 2.9.2 aktualisieren

Path Traversal in mlflow/mlflow

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

• Auf 2.9.2 aktualisieren

Improper Neutralization of Special Elements Used in a Template Engine in mlflow/mlflow

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

• Auf 2.9.2 aktualisieren

Reflected XSS via Content-Type Header in mlflow/mlflow

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 user without adequate sanitization or escaping, leading to arbitrary JavaScript execution in the context of the victim's browser. The vulnerability is present in the mlflow/server/auth/__init__.py file, where the user-supplied Content-Type header is directly injected into a Python formatted string and returned to the user, facilitating the XSS attack.

• Auf 2.9.0 aktualisieren
• Auf 2.9.1 aktualisieren

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.

• Auf 2.9.0 aktualisieren

MLflow Authentication Bypass

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

• Auf 2.8.0 aktualisieren

MLflow Arbitrary File Upload

MLflow allowed arbitrary files to be PUT onto the server.

• Auf 2.8.1 aktualisieren

MLflow Arbitrary File Write

An attacker can overwrite any file on the server hosting MLflow without any authentication.

• Auf 2.9.2 aktualisieren

OS Command Injection in mlflow/mlflow

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

• Auf 2.6.0 aktualisieren

Absolute Path Traversal in mlflow/mlflow

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

• Auf 2.5.0 aktualisieren