sagemaker-python-sdk is a library for training and deploying machine learning models on Amazon SageMaker. The sagemaker.base_deserializers.NumpyDeserializer module before v2.218.0 allows potentially unsafe deserialization when untrusted data is passed as pickled object arrays. This consequently may allow an unprivileged third party to cause remote code execution, denial of service, affecting both confidentiality and integrity. Users are advised to upgrade to version 2.218.0. Users unable to upgrade should not pass pickled numpy object arrays which originated from an untrusted source, or that could have been tampered with. Only pass pickled numpy object arrays from trusted sources.
| Métrique | Valeur | Interprétation |
|---|---|---|
|
AV (Vecteur d'Attaque)
Attack Vector
|
Local (L)
|
Exploit nécessite un accès local au système |
|
AC (Complexité d'Attaque)
Attack Complexity
|
Low (L)
|
Peu de conditions requises pour exploiter |
|
PR (Privilèges Requis)
Privileges Required
|
None (N)
|
Aucune authentification requise |
|
UI (Interaction Utilisateur)
User Interaction
|
Required (R)
|
NĂ©cessite une action utilisateur (clic lien, ouverture fichier, etc.) |
|
S (Périmètre)
Scope
|
Unchanged (U)
|
Impact reste dans le périmètre du composant compromis |
|
C (Impact Confidentialité)
Confidentiality Impact
|
High (H)
|
Divulgation totale d'informations |
|
I (Impact Intégrité)
Integrity Impact
|
High (H)
|
Modification totale des données possible |
|
A (Impact Disponibilité)
Availability Impact
|
High (H)
|
Interruption totale du service possible |
sagemaker-python-sdk vulnerable to Deserialization of Untrusted Data
Deserialization of Untrusted Data in sagemaker-python-sdk