airflow-dag-patterns
Pass
Audited by Gen Agent Trust Hub on Jun 20, 2026
Risk Level: SAFECOMMAND_EXECUTIONPROMPT_INJECTION
Full Analysis
- [COMMAND_EXECUTION]: The skill uses
globals()inresources/implementation-playbook.mdto dynamically register DAG objects at runtime based on a configuration list. While this is a standard idiom for generating multiple similar pipelines in Apache Airflow, it involves dynamic manipulation of the global namespace.\n- [PROMPT_INJECTION]: The templates inresources/implementation-playbook.mddescribe data ingestion patterns that could be vulnerable to indirect prompt injection.\n - Ingestion points: Data is read from S3 buckets using
pandas.read_csvin theextracttasks.\n - Boundary markers: The provided code samples do not include delimiters or instructions to ignore embedded commands within the processed data.\n
- Capability inventory: The skill defines tasks executed via
PythonOperatorandBranchPythonOperatorfor data transformation and routing.\n - Sanitization: There is no evidence of input validation or sanitization for the data retrieved from external sources.
Audit Metadata