CVE-2024-27133

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...

a2 (>=0.1.0 <=0.3.17), agentos (>=0.0.5 <=0.0.7) +148 more potentially affected by CVE-2024-27133 via mlflow (>=0.8.2 <=2.0.1)

mlflow PYPI version =0.8.2, =0.1.0, =0.0.5, =0.1.2, =1.0.18.2, =0.0.1, =1.0.41, =1.4.0, =0.2.5, =3.0.0, =0.1.0, =0.3.5, =0.8.0, =0.0.4, =0.0.7 and more Source cves: CVE-2024-27133 Source advisory: OSV:PYSEC-2024-241...

CVE-2024-27133 Insufficient sanitization in MLflow leads to XSS when running a recipe that uses an untrusted dataset.

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-2024-27133

CVE-2024-27133 : Affects MLflow. Insufficient sanitization of dataset table fields in MLflow recipes can cause a client-side XSS, which in turn can lead to a client-side RCE when running the recipe in Jupyter Notebook . Root cause: lack of input sanitization for untrusted datasets in the data tab...

CVE-2024-27133 Insufficient sanitization in MLflow leads to XSS when running a recipe that uses an untrusted dataset.

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...