data-engineering-data-pipeline

Pass

Audited by Gen Agent Trust Hub on Apr 1, 2026

Risk Level: SAFE
Full Analysis
  • [DATA_EXPOSURE]: The skill uses safe placeholders for connection strings (e.g., 'postgresql://host:5432/db') and storage paths (e.g., 's3://lake') in its examples, encouraging proper configuration rather than hardcoding credentials.
  • [PROMPT_INJECTION]: The instructions are strictly limited to technical data engineering domains. There are no attempts to override agent behavior, bypass safety filters, or extract system prompts.
  • [REMOTE_CODE_EXECUTION]: The skill does not download or execute remote scripts. It references well-known open-source frameworks such as Apache Airflow, dbt, and Great Expectations which are standard in the industry.
  • [COMMAND_EXECUTION]: The provided Python snippets demonstrate local data processing and storage operations using standard data engineering libraries. No arbitrary shell command execution or privilege escalation patterns were found.
Audit Metadata
Risk Level
SAFE
Analyzed
Apr 1, 2026, 03:42 AM
Security Audit — agent-trust-hub — data-engineering-data-pipeline