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 thi...Show moreA 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_source_contains_relative_paths(source)` function's checks, allowing for arbitrary file read access on the server. The issue arises from the handling of unquoted URL characters and the subsequent misuse of the original `source` value for model version creation, leading to the exposure of sensitive files when interacting with the `/model-versions/get-artifact` handler.Show less |
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...Show moreA 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.Show less |
Minder is a software supply chain security platform. Prior to version 0.0.33, a Minder user can use the endpoints `GetRepositoryByName`, `DeleteRepositoryByName`, and `GetArtifactByName` to access any repository in the d...Show moreMinder is a software supply chain security platform. Prior to version 0.0.33, a Minder user can use the endpoints `GetRepositoryByName`, `DeleteRepositoryByName`, and `GetArtifactByName` to access any repository in the database, irrespective of who owns the repo and any permissions present. The database query checks by repo owner, repo name and provider name (which is always `github`). These query values are not distinct for the particular user - as long as the user has valid credentials and a provider, they can set the repo owner/name to any value they want and the server will return information on this repo. Version 0.0.33 contains a patch for this issue.Show less |
Minder is a Software Supply Chain Security Platform. In version 0.0.31 and earlier, it is possible for an attacker to register a repository with a invalid or differing upstream ID, which causes Minder to report the repos...Show moreMinder is a Software Supply Chain Security Platform. In version 0.0.31 and earlier, it is possible for an attacker to register a repository with a invalid or differing upstream ID, which causes Minder to report the repository as registered, but not remediate any future changes which conflict with policy (because the webhooks for the repo do not match any known repository in the database). When attempting to register a repo with a different repo ID, the registered provider must have admin on the named repo, or a 404 error will result. Similarly, if the stored provider token does not have repo access, then the remediations will not apply successfully. Lastly, it appears that reconciliation actions do not execute against repos with this type of mismatch. This appears to primarily be a potential denial-of-service vulnerability. This vulnerability is patched in version 0.20240226.1425+ref.53868a8.Show less |
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...Show moreInsufficient 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.Show less |
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 saniti...Show moreInsufficient 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.
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cdo-local-uuid project provides a specialized UUID-generating function that can, on user request, cause a program to generate deterministic UUIDs. An information leakage vulnerability is present in `cdo-local-uuid` at ve...Show morecdo-local-uuid project provides a specialized UUID-generating function that can, on user request, cause a program to generate deterministic UUIDs. An information leakage vulnerability is present in `cdo-local-uuid` at version `0.4.0`, and in `case-utils` in unpatched versions (matching the pattern `0.x.0`) at and since `0.5.0`, before `0.15.0`. The vulnerability stems from a Python function, `cdo_local_uuid.local_uuid()`, and its original implementation `case_utils.local_uuid()`. Show less |
This vulnerability enables malicious users to read sensitive files on the server. |
This vulnerability is capable of writing arbitrary files into arbitrary locations on the remote filesystem in the context of the server process. |
A malicious user could use this issue to get command execution on the vulnerable machine and get access to data & models information. |
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. |
with only one user interaction(download a malicious config), attackers can gain full command execution on the victim system. |
Path Traversal: '\..\filename' in GitHub repository mlflow/mlflow prior to 2.9.2. |
Path Traversal: '\..\filename' in GitHub repository mlflow/mlflow prior to 2.9.2. |
Path Traversal in GitHub repository mlflow/mlflow prior to 2.9.2. |
Improper Neutralization of Special Elements Used in a Template Engine in GitHub repository mlflow/mlflow prior to 2.9.2. |
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...Show moreA 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.Show less |
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. |
An attacker is able to arbitrarily create an account in MLflow bypassing any authentication requirment. |
An attacker can overwrite any file on the server hosting MLflow without any authentication. |