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.start and saveAsTable in SKILL.md and references/multi-sink-writes.md.
  • Sanitization: Patterns use from_json with 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 MERGE queries in references/merge-operations.md and table paths in references/checkpoint-best-practices.md.
  • [COMMAND_EXECUTION]: The skill includes instructions for managing the Databricks filesystem using dbutils.fs commands.
  • Evidence: Use of dbutils.fs.rm, dbutils.fs.cp, and dbutils.fs.ls for checkpoint management and recovery in references/checkpoint-best-practices.md.
Audit Metadata
Risk Level
SAFE
Analyzed
Jun 28, 2026, 05:51 PM
Security Audit — agent-trust-hub — databricks-spark-structured-streaming