spark-python-data-source
Pass
Audited by Gen Agent Trust Hub on Aug 11, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill serves as a technical manual and code template library for Spark developers. It does not contain malicious instructions, obfuscation, or unauthorized data exfiltration patterns.
- [EXTERNAL_DOWNLOADS]: The skill references several external resources for educational purposes and reference implementations:
- Official documentation from Apache Spark and Databricks.
- Community-maintained repositories on GitHub, including 'alexott/cyber-spark-data-connectors', 'dgomez04/pyspark-hubspot', and 'allisonwang-db/awesome-python-datasources'.
- A repository associated with the vendor: 'databricks-industry-solutions/python-data-sources'.
- [CREDENTIALS_UNSAFE]: The skill provides code snippets for implementing various authentication methods (Azure Identity, OAuth2, Basic Auth). These examples use standard placeholders like 'YOUR_API_KEY_HERE' and explicitly instruct the user to use secure secrets management (e.g., Databricks Utilities or environment variables) rather than hardcoding credentials.
- [COMMAND_EXECUTION]: The documentation includes standard development commands using 'poetry' for project management, testing, and linting. These are standard practices for Python development and do not represent a security risk.
- [DATA_EXFILTRATION]: While the skill provides examples of network operations using the 'requests' library, these are necessary for the primary purpose of the skill (building data connectors). The instructions also include a 'SecureDataSource' pattern that demonstrates how to mask sensitive keys in logs to prevent accidental data exposure.
Audit Metadata