data-quality-frameworks

Pass

Audited by Gen Agent Trust Hub on Apr 12, 2026

Risk Level: SAFEEXTERNAL_DOWNLOADSPROMPT_INJECTIONCREDENTIALS_UNSAFE
Full Analysis
  • [EXTERNAL_DOWNLOADS]: The skill instructs users to install the great_expectations package from the standard Python Package Index (PyPI).
  • [CREDENTIALS_UNSAFE]: The skill demonstrates secure credential handling by utilizing environment variable placeholders (${SLACK_WEBHOOK}) for Slack integrations instead of hardcoding sensitive tokens.
  • [PROMPT_INJECTION]: The skill exhibits a surface for indirect prompt injection (Category 8) within the quality_pipeline.py script.
  • Ingestion points: Data is ingested from external database validation results via the observed_value field in the generate_report method of DataQualityPipeline.
  • Boundary markers: The generated markdown report lacks delimiters or warnings to prevent the agent from interpreting embedded data as instructions.
  • Capability inventory: The skill performs database read operations and generates text-based reports that may be consumed by an agent; it also supports raising exceptions based on validation failures.
  • Sanitization: There is no evidence of escaping or sanitizing the observed data values before they are interpolated into the final markdown report.
Audit Metadata
Risk Level
SAFE
Analyzed
Apr 12, 2026, 09:36 AM
Security Audit — agent-trust-hub — data-quality-frameworks