Filtered by vendor Lfprojects
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Total
52 CVE
| CVE | Vendors | Products | Updated | CVSS v3.1 |
|---|---|---|---|---|
| CVE-2024-37054 | 1 Lfprojects | 1 Mlflow | 2025-02-03 | 8.8 High |
| 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-2024-37053 | 1 Lfprojects | 1 Mlflow | 2025-02-03 | 8.8 High |
| 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-2024-37052 | 1 Lfprojects | 1 Mlflow | 2025-02-03 | 8.8 High |
| 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-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-2024-27132 | 1 Lfprojects | 1 Mlflow | 2025-01-22 | 7.5 High |
| 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 | 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-2024-3099 | 1 Lfprojects | 1 Mlflow | 2024-11-21 | 5.4 Medium |
| A vulnerability in mlflow/mlflow version 2.11.1 allows attackers to create multiple models with the same name by exploiting URL encoding. This flaw can lead to Denial of Service (DoS) as an authenticated user might not be able to use the intended model, as it will open a different model each time. Additionally, an attacker can exploit this vulnerability to perform data model poisoning by creating a model with the same name, potentially causing an authenticated user to become a victim by using the poisoned model. The issue stems from inadequate validation of model names, allowing for the creation of models with URL-encoded names that are treated as distinct from their URL-decoded counterparts. | ||||
| CVE-2024-2928 | 1 Lfprojects | 1 Mlflow | 2024-11-21 | 7.5 High |
| 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 exploit this flaw by manipulating the fragment part of the URI to read arbitrary files on the local file system, including sensitive files like '/etc/passwd'. The vulnerability is a bypass to a previous patch that only addressed similar manipulation within the URI's query string, highlighting the need for comprehensive validation of all parts of a URI to prevent LFI attacks. | ||||
| CVE-2024-22194 | 1 Lfprojects | 2 Case Python Utilities, Cdo Local Uuid Utility | 2024-11-21 | 2.2 Low |
| 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 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()`. | ||||
| CVE-2024-0520 | 1 Lfprojects | 1 Mlflow | 2024-11-21 | 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-2023-6977 | 1 Lfprojects | 1 Mlflow | 2024-11-21 | 7.5 High |
| This vulnerability enables malicious users to read sensitive files on the server. | ||||
| CVE-2023-6976 | 1 Lfprojects | 1 Mlflow | 2024-11-21 | 8.8 High |
| This vulnerability is capable of writing arbitrary files into arbitrary locations on the remote filesystem in the context of the server process. | ||||
| CVE-2023-6975 | 1 Lfprojects | 1 Mlflow | 2024-11-21 | 9.8 Critical |
| A malicious user could use this issue to get command execution on the vulnerable machine and get access to data & models information. | ||||
| CVE-2023-6974 | 1 Lfprojects | 1 Mlflow | 2024-11-21 | 9.8 Critical |
| 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 | 1 Lfprojects | 1 Mlflow | 2024-11-21 | 8.8 High |
| with only one user interaction(download a malicious config), attackers can gain full command execution on the victim system. | ||||
| CVE-2023-6909 | 1 Lfprojects | 1 Mlflow | 2024-11-21 | 7.5 High |
| Path Traversal: '\..\filename' in GitHub repository mlflow/mlflow prior to 2.9.2. | ||||
| CVE-2023-6831 | 1 Lfprojects | 1 Mlflow | 2024-11-21 | 8.1 High |
| Path Traversal: '\..\filename' in GitHub repository mlflow/mlflow prior to 2.9.2. | ||||