CVE search
Every published CVE plus open-source advisories (NVD, OSV, GitHub), with CVSS, EPSS and whether it is being exploited in the wild (CISA KEV). Updated every few hours. Our scans match these against the technologies they detect.
Every published CVE plus open-source advisories (NVD, OSV, GitHub), with CVSS, EPSS and whether it is being exploited in the wild (CISA KEV). Updated every few hours. Our scans match these against the technologies they detect.
| 29/10/2025 |
| CVE-2025-1474 | 보통5.5 | 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 issu | 20/03/2025 |
| CVE-2025-1473 | 높음7.1 | 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. | 20/03/2025 |
| CVE-2025-0453 | 높음7.5 | In mlflow/mlflow version 2.17.2, the `/graphql` endpoint is vulnerable to a denial of service attack. An attacker can create large batches of queries that repeatedly request all runs from a given experiment. This can tie up all the workers allocated by MLFlow, rendering the application unable to respond to other reques | 20/03/2025 |
| CVE-2024-8859 | 높음7.5 | A path traversal vulnerability exists in mlflow/mlflow version 2.15.1. When users configure and use the dbfs service, concatenating the URL directly into the file protocol results in an arbitrary file read vulnerability. This issue occurs because only the path part of the URL is checked, while parts such as query and p | 20/03/2025 |
| CVE-2024-6838 | 보통5.3 | In mlflow/mlflow version v2.13.2, a vulnerability exists that allows the creation or renaming of an experiment with a large number of integers in its name due to the lack of a limit on the experiment name. This can cause the MLflow UI panel to become unresponsive, leading to a potential denial of service. Additionally, | 20/03/2025 |
| CVE-2024-27134 | 높음7.0 | 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. | 25/11/2024 |
| CVE-2024-2928 | 높음7.5 | 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 | 06/06/2024 |
| CVE-2024-0520 | 높음8.8 | 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 | 06/06/2024 |
| CVE-2024-37061 | 높음8.8 | 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. | 04/06/2024 |
| CVE-2024-37060 | 높음8.8 | 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. | 04/06/2024 |
| CVE-2024-37059 | 높음8.8 | 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. | 04/06/2024 |
| CVE-2024-37058 | 높음8.8 | 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. | 04/06/2024 |
| CVE-2024-37057 | 높음8.8 | 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. | 04/06/2024 |
| CVE-2024-37056 | 높음8.8 | 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. | 04/06/2024 |
| CVE-2024-37055 | 높음8.8 | 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. | 04/06/2024 |
| CVE-2024-37054 | 높음8.8 | 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. | 04/06/2024 |
| CVE-2024-37053 | 높음8.8 | 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. | 04/06/2024 |