Provides fully managed notebook instances specifically designed for machine learning development, eliminating the need to manage underlying infrastructure.
Managed Notebook Environments
CCC.MLDE.CP01
Related Threats
| ID | Title | Description |
|---|---|---|
| CCC.MLDE.TH01 | Elevated System Access on Notebook Instances is Abused | Managed notebook instances may be configured to permit root privileges, interactive terminal sessions, or unrestricted access modes for the users of the environment. When such access is available, the underlying instance configuration could be modified, security agents disabled, or arbitrary commands executed outside the notebook interface. This compromises the integrity of the development environment and the confidentiality of any data or credentials accessible from the instance. |
| CCC.MLDE.TH02 | Training Data or Model Artifacts are Exfiltrated | Notebook instances and connected data pipelines may be configured with unrestricted egress paths, such as file downloads, public network interfaces, or writable external destinations. Training datasets, model artifacts, and embedded credentials could be transferred out of the environment through these paths. This results in a loss of confidentiality for proprietary data and models, and may expose regulated or sensitive records used in training. |
| CCC.MLDE.TH04 | Outdated or Unapproved Environment Images are Exploited | Notebook instances may be created from arbitrary virtual machine or container images, or left running without scheduled upgrades, so that pre-installed machine learning libraries and runtimes fall behind current security patches. Known vulnerabilities in these components could be exploited to execute code or escalate privileges within the environment. This compromises the confidentiality, integrity, and availability of the development environment and the data it processes. |