data-engineering-data-pipeline
Pass
Audited by Gen Agent Trust Hub on Jul 31, 2026
Risk Level: SAFE
Full Analysis
- [PROMPT_INJECTION]: No evidence of prompt injection or instruction override patterns was detected. The instructions follow a standard role-play format for a domain expert without attempting to bypass safety filters.
- [DATA_EXFILTRATION]: No data exfiltration patterns or sensitive file access were found. The example code uses generic placeholder connection strings (e.g., 'postgresql://host:5432/db') and public cloud service paths (e.g., 's3://lake') as templates for the user.
- [CREDENTIALS_UNSAFE]: No hardcoded secrets, API keys, or private tokens were detected in the instructions or example code.
- [REMOTE_CODE_EXECUTION]: The skill does not perform any remote code execution or download scripts from external sources. It references well-known data engineering frameworks (Apache Spark, Airflow, dbt) which are expected in this context.
- [COMMAND_EXECUTION]: No suspicious shell command execution patterns or privilege escalation attempts were identified.
- [OBFUSCATION]: The content is presented in clear, plain text with no evidence of Base64 encoding, zero-width characters, or homoglyph attacks.
- [INDIRECT_PROMPT_INJECTION]: While the skill involves designing systems that ingest external data, it explicitly includes instructions for schema validation, dead letter queues, and data quality frameworks (Great Expectations), which are best practices for mitigating risks from untrusted data inputs.
Audit Metadata