beam-dataflow-python
Pass
Audited by Gen Agent Trust Hub on Mar 9, 2026
Risk Level: SAFECOMMAND_EXECUTIONEXTERNAL_DOWNLOADS
Full Analysis
- [SAFE]: The skill provides comprehensive guidelines for building data processing pipelines. All examples follow standard security practices, including the use of environment variables for database credentials and the use of Docker for secure, reproducible environments.
- [COMMAND_EXECUTION]: The skill includes documentation for standard CLI tools like
gcloud,mvn,pip, anddocker. These commands are strictly used for the intended purpose of the skill: deploying, configuring, and testing Dataflow jobs. No unauthorized command execution or persistence mechanisms were found. - [EXTERNAL_DOWNLOADS]: The skill references official and trusted external sources, such as Google Cloud documentation and the Apache Beam GitHub repository. The documentation script
scripts/crawl_dataflow_docs.pyfetches data only fromdocs.cloud.google.com, a well-known and trusted domain. - [INDIRECT_PROMPT_INJECTION]: While the skill describes how to ingest data from external sources like Pub/Sub and BigQuery, it mitigates potential risks by documenting resilient patterns such as Dead Letter Queues (DLQ) and proper data validation using Pydantic and Beam Schemas.
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