databricks-spark-structured-streaming
Pass
Audited by Gen Agent Trust Hub on Jun 28, 2026
Risk Level: SAFE
Full Analysis
- [INDIRECT_PROMPT_INJECTION]: The skill provides patterns for processing data from external streaming sources (Kafka), creating a potential attack surface if the stream content is malicious.
- Ingestion points: Data ingestion from Kafka topics is shown in
references/kafka-streaming.md. - Boundary markers: No specific delimiters are included in the provided code templates for the processed data.
- Capability inventory: The skill demonstrates file and table writes using
writeStream.startandsaveAsTableinSKILL.mdandreferences/multi-sink-writes.md. - Sanitization: Patterns use
from_jsonwith a defined schema to validate and structure the incoming data. - [DYNAMIC_EXECUTION]: Code snippets use string interpolation to construct Spark SQL statements and file paths.
- Evidence: Dynamic construction of
MERGEqueries inreferences/merge-operations.mdand table paths inreferences/checkpoint-best-practices.md. - [COMMAND_EXECUTION]: The skill includes instructions for managing the Databricks filesystem using
dbutils.fscommands. - Evidence: Use of
dbutils.fs.rm,dbutils.fs.cp, anddbutils.fs.lsfor checkpoint management and recovery inreferences/checkpoint-best-practices.md.
Audit Metadata