data-engineering-data-pipeline
Pass
Audited by Gen Agent Trust Hub on Apr 8, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill serves as a comprehensive reference for data engineering architecture and best practices. No malicious code, prompt injections, or obfuscation techniques were detected.
- [EXTERNAL_DOWNLOADS]: The instructions and examples reference well-known and reputable data engineering frameworks including Apache Airflow, dbt, Apache Spark, Delta Lake, and Great Expectations. These are standard industry tools.
- [CREDENTIALS_UNSAFE]: Example Python code in the monitoring sub-skill uses safe placeholders (e.g., 'postgresql://host:5432/db' and 's3://lake') rather than hardcoded credentials or sensitive environment data.
- [DATA_EXFILTRATION]: No unauthorized network operations or data exfiltration patterns were found. Network interactions mentioned are limited to standard database and cloud storage operations within a data pipeline context.
- [COMMAND_EXECUTION]: The skill does not contain any instructions that would lead to arbitrary or dangerous command execution on the host system.
Audit Metadata