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Search Results (18 CVEs found)
| CVE | Vendors | Products | Updated | CVSS v3.1 |
|---|---|---|---|---|
| CVE-2026-2614 | 2 Lfprojects, Mlflow | 2 Mlflow, Mlflow/mlflow | 2026-08-28 | 7.5 High |
| A vulnerability in the `_create_model_version()` handler of `mlflow/server/handlers.py` in mlflow/mlflow versions 3.9.0 and earlier allows an unauthenticated remote attacker to read arbitrary files from the server's filesystem. The issue arises when a `CreateModelVersion` request includes the tag `mlflow.prompt.is_prompt`, which bypasses source path validation. This enables an attacker to store an arbitrary local filesystem path as the model version source. The `get_model_version_artifact_handler()` function later uses this source to serve files without verifying the model version's prompt status, leading to a complete confidentiality compromise. This issue is fixed in version 3.10.0. | ||||
| CVE-2025-52967 | 1 Lfprojects | 1 Mlflow | 2026-04-15 | 5.8 Medium |
| gateway_proxy_handler in MLflow before 3.1.0 lacks gateway_path validation. | ||||
| CVE-2024-0520 | 1 Lfprojects | 1 Mlflow | 2025-10-15 | 8.8 High |
| 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 scheme, the filename extracted from the `Content-Disposition` header or the URL path is used to generate the final file path without proper sanitization. This flaw enables an attacker to control the file path fully by utilizing path traversal or absolute path techniques, such as '../../tmp/poc.txt' or '/tmp/poc.txt', leading to arbitrary file write. Exploiting this vulnerability could allow a malicious user to execute commands on the vulnerable machine, potentially gaining access to data and model information. The issue is fixed in version 2.9.0. | ||||
| CVE-2025-1474 | 1 Lfprojects | 1 Mlflow | 2025-03-27 | 5.5 Medium |
| 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 management. The issue is fixed in version 2.19.0. | ||||
| CVE-2023-23619 | 1 Lfprojects | 1 Modelina | 2025-03-10 | 10 Critical |
| Modelina is a library for generating data models based on inputs such as AsyncAPI, OpenAPI, or JSON Schema documents. Versions prior to 1.0.0 are vulnerable to Code injection. This issue affects anyone who is using the default presets and/or does not handle the functionality themself. This issue has been partially mitigated in version 1.0.0, with the maintainer's GitHub Security Advisory (GHSA) noting "It is impossible to fully guard against this, because users have access to the original raw information. However, as of version 1, if you only access the constrained models, you will not encounter this issue. Further similar situations are NOT seen as a security issue, but intended behavior." The suggested workaround from the maintainers is "Fully custom presets that change the entire rendering process which can then escape the user input." | ||||
| CVE-2023-1176 | 1 Lfprojects | 1 Mlflow | 2025-02-19 | 3.3 Low |
| Absolute Path Traversal in GitHub repository mlflow/mlflow prior to 2.2.2. | ||||
| CVE-2024-4263 | 1 Lfprojects | 1 Mlflow | 2025-02-03 | 5.4 Medium |
| 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 them to perform unauthorized deletions of artifacts. The vulnerability specifically affects the handling of artifact deletions within the application, as demonstrated by the ability of a low privilege user to delete a directory inside an artifact using a DELETE request, despite the official documentation stating that users with EDIT permission can only read and update artifacts, not delete them. | ||||
| CVE-2024-27134 | 1 Lfprojects | 1 Mlflow | 2025-02-03 | 7 High |
| 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-2023-2356 | 1 Lfprojects | 1 Mlflow | 2025-01-30 | 7.5 High |
| Relative Path Traversal in GitHub repository mlflow/mlflow prior to 2.3.1. | ||||
| CVE-2023-30172 | 1 Lfprojects | 1 Mlflow | 2025-01-27 | 7.5 High |
| 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-2024-3848 | 1 Lfprojects | 1 Mlflow | 2025-01-24 | 7.5 High |
| 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 skipping validation. This allows an attacker to construct a URL that, when processed, ignores the protocol scheme and uses the provided path for filesystem access. As a result, an attacker can read arbitrary files, including sensitive information such as SSH and cloud keys, by exploiting the way the application converts the URL into a filesystem path. The issue stems from insufficient validation of the fragment portion of the URL, leading to arbitrary file read through path traversal. | ||||
| CVE-2023-2780 | 1 Lfprojects | 1 Mlflow | 2025-01-22 | 9.8 Critical |
| Path Traversal: '\..\filename' in GitHub repository mlflow/mlflow prior to 2.3.1. | ||||
| CVE-2024-27133 | 1 Lfprojects | 1 Mlflow | 2025-01-22 | 7.5 High |
| 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-2023-6753 | 2 Lfprojects, Microsoft | 2 Mlflow, Windows | 2024-11-21 | 8.8 High |
| Path Traversal in GitHub repository mlflow/mlflow prior to 2.9.2. | ||||
| CVE-2023-6709 | 1 Lfprojects | 1 Mlflow | 2024-11-21 | 8.8 High |
| Improper Neutralization of Special Elements Used in a Template Engine in GitHub repository mlflow/mlflow prior to 2.9.2. | ||||
| CVE-2023-6568 | 1 Lfprojects | 1 Mlflow | 2024-11-21 | 6.1 Medium |
| 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. | ||||
| CVE-2023-4033 | 2 Lfprojects, Mlflow | 2 Mlflow, Mlflow | 2024-11-21 | 7.8 High |
| OS Command Injection in GitHub repository mlflow/mlflow prior to 2.6.0. | ||||
| CVE-2023-3765 | 2 Lfprojects, Microsoft | 2 Mlflow, Windows | 2024-11-21 | 10.0 Critical |
| Absolute Path Traversal in GitHub repository mlflow/mlflow prior to 2.5.0. | ||||
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