databricks-spark-structured-streaming
Pass
Audited by Gen Agent Trust Hub on Feb 24, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill provides purely technical documentation and implementation patterns for Spark Structured Streaming. No malicious code or obfuscation was detected.
- [SAFE]: The code snippets demonstrate secure credential management by using
dbutils.secrets.get()to retrieve Kafka SASL/PLAIN credentials from a secret scope, rather than hardcoding them. - [SAFE]: The skill provides advanced data engineering patterns for schema validation and routing invalid records to a Dead Letter Queue (DLQ). This practice ensures that malformed or potentially malicious data is isolated and does not disrupt downstream processing.
- [SAFE]: All file path references (e.g., Unity Catalog Volumes, S3/ADLS paths) and network configurations (Kafka broker placeholders) are consistent with standard, legitimate Databricks development workflows.
Audit Metadata