Model

Updated: August 11, 2026

An AI model processes data, identifies patterns, and makes predictions or generates outputs.

  1. In the side menu, go to Workload and select Models.
  2. All discovered AI models are displayed. Each model shows when it was discovered, its provider, its project and its risk score. Models are sorted by risk score by default.
  3. Click on a model to view further details. The model header shows the risk score as a gauge, along with the severity band it falls into.
  4. The Details tab shows:
    • Model: Identifies the AI model.
    • Provider: Identifies the provider (e.g., Anthropic, OpenAI, Amazon).
    • Scanned Via & Source: Specifies how the model was discovered (e.g., AWS Bedrock, AWS).
    • Framework: The specific model version the discovery maps to (e.g., claude-sonnet-4-20250514-v1).
    • Item Type: Whether the model is a Cloud or code-based resource.
    • Created At & Modified At: Tracks when the model was first detected and last updated.
    • Project & Integration: The project and integration the model was discovered through.
    • Metadata: Includes details such as:
      • Account ID: Identifies the cloud account associated with the model.
      • Model ARN: The unique Amazon Resource Name (ARN) for AWS-hosted models.
      • Model ID: A version-specific identifier (e.g., anthropic.claude-sonnet-4-20250514-v1:0).
      • Discovery Method: Specifies how the model was found (e.g., CloudWatch logs).
      • Region Name: The geographical cloud region where the model is deployed (e.g., us-east-1).
      • Data Last Accessed: When the model was last used.
      • Input Modalities & Output Modalities: The data types the model accepts and returns (e.g., TEXT, IMAGE).
      • Inference Types Supported & Customizations Supported: The inference profiles and customizations available for the model.

Alongside Details, each model has the following tabs:

  • Findings: Security findings raised against this model.
  • Prompts: Information about the prompts associated with the model.
  • Logs: Detailed records showing when the model was called, what inputs were used, and what outputs were generated.