synthetic-data-generation

Pass

Audited by Gen Agent Trust Hub on Jul 3, 2026

Risk Level: SAFE
Full Analysis
  • [EXTERNAL_DOWNLOADS]: The skill specifies several Python dependencies required for data processing, including lasio, welly, dlisio, segyio, numpy, pandas, and scipy. These are established, domain-specific libraries for handling geoscientific data formats and performing numerical analysis.
  • [INDIRECT_PROMPT_INJECTION]: The skill possesses a data ingestion surface as it accepts user-provided parameters (such as well_name, formation, and field_name) which are then used to populate metadata in generated synthetic files (LAS, SEG-Y, and OSDU manifests).
  • Ingestion points: User inputs for data generation parameters defined in SKILL.md.
  • Boundary markers: None explicitly defined for user-supplied strings.
  • Capability inventory: The skill performs file writing and metadata generation through domain-specific classes (LASGenerator, SEGYGenerator, LASMapper).
  • Sanitization: There is no mention of explicit sanitization for user-provided strings before they are written to file metadata.
  • [SAFE]: No malicious patterns, obfuscated code, unauthorized network operations, or persistence mechanisms were identified. The instructions for handling expensive AI image generation (core photos) prioritize user consent and cost awareness.
Audit Metadata
Risk Level
SAFE
Analyzed
Jul 3, 2026, 12:42 PM
Security Audit — agent-trust-hub — synthetic-data-generation