Lfprojects vulnerabilities
We track 55 vulnerabilities in Lfprojects products across 7 products. 55 are rated high or critical, and none are known to be exploited. The most recent was published on July 15, 2026.
Latest Lfprojects vulnerabilities
- 8.8 High severity
MLflow: Deserialization of Untrusted Data
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.
- 8.8 High severity
MLflow: Deserialization of Untrusted Data
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.
- 8.8 High severity
MLflow: Deserialization of Untrusted Data
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.
- 8.8 High severity
MLflow: Deserialization of Untrusted Data
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.
- 8.8 High severity
MLflow: Deserialization of Untrusted Data
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.
- 7.5 High severity
mlflow/mlflow: Improper Limitation of a Pathname to a Restricted Directory
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 p
- 9.3 Critical severity
mlflow/mlflow: Improper Limitation of a Pathname to a Restricted Directory
mlflow/mlflow is vulnerable to Local File Inclusion (LFI) due to improper parsing of URIs, allowing attackers to bypass checks and read arbitrary files on the system. The issue arises from the 'is_local_uri' function's failure to properly handle URIs with empt
- 7.5 High severity
mlflow/mlflow: Improper Limitation of a Pathname to a Restricted Directory
A path traversal vulnerability exists in the mlflow/mlflow repository, specifically within the handling of the `artifact_location` parameter when creating an experiment. Attackers can exploit this vulnerability by using a fragment component `#` in the artifact
- 7.5 High severity
mlflow/mlflow: Improper Limitation of a Pathname to a Restricted Directory
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 this vulnerability by crafting a `source` p
- 7.5 High severity
mlflow/mlflow: Improper Limitation of a Pathname to a Restricted Directory
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 w
- 9.6 Critical severity
mlflow: Improper Neutralization of Input During Web Page Generation
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 field
- 9.6 Critical severity
mlflow: Improper Neutralization of Input During Web Page Generation
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.
- 9.8 Critical severity
mlflow/mlflow: Server-Side Request Forgery
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.
- 7.5 High severity
Mlflow: Improper Limitation of a Pathname to a Restricted Directory
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.
- 7.5 High severity
Vector Packet Processor: Generation of Predictable IV with CBC Mode
FP.io VPP (Vector Packet Processor) 22.10, 22.06, 22.02, 21.10, 21.06, 21.01, 20.09, 20.05, 20.01, 19.08, and 19.04 Generates a Predictable IV with CBC Mode.