databricks-app-python
Pass
Audited by Gen Agent Trust Hub on Mar 2, 2026
Risk Level: SAFE
Full Analysis
- [DATA_EXPOSURE]: The skill mandates security-positive practices by requiring the use of Databricks SDK
Config()for authentication and environment-based configuration viavalueFrom, preventing the exposure of hardcoded tokens or resource IDs. - [EXTERNAL_DOWNLOADS]: Documents links to the Databricks Apps Cookbook and official Databricks documentation for configuration examples and code recipes. These references target the author's own domain and a well-known service provider.
- [COMMAND_EXECUTION]: Describes the use of standard Databricks CLI tools for workspace management, application deployment, and log retrieval.
- [INDIRECT_PROMPT_INJECTION]: The skill facilitates the creation of applications that ingest untrusted data (e.g., user authorization tokens from headers or database records) and perform downstream operations like SQL queries or model inference calls, creating a potential vulnerability surface.
- Ingestion points: User tokens via
x-forwarded-access-tokenheaders and data fetched from SQL warehouses (documented in1-authorization.mdand2-app-resources.md). - Boundary markers: Encourages structured data handling via Pydantic but does not define explicit delimiters for separating user content from system instructions in prompts.
- Capability inventory: Applications can execute SQL queries, interact with PostgreSQL (Lakebase), and call model serving endpoints via REST APIs.
- Sanitization: Recommends Pydantic for input validation and schema enforcement.
Audit Metadata