faker-data
Pass
Audited by Gen Agent Trust Hub on Aug 12, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill provides documentation and examples for using well-known, industry-standard libraries (Faker) for generating synthetic test data. All external links point to official documentation and reputable GitHub repositories.
- [EXTERNAL_DOWNLOADS]: The skill includes standard installation commands for official packages from public registries (
pip install Faker,npm install @faker-js/faker, andgem 'faker'). These are standard development practices and do not involve untrusted sources. - [PROMPT_INJECTION]: No evidence of prompt injection, role-play instructions, or safety bypass attempts was found in the documentation or metadata.
- [COMMAND_EXECUTION]: The shell commands provided (
pip install,npm install) are purely instructional and intended for the user to set up their development environment. There are no hidden or automated execution patterns. - [DATA_EXFILTRATION]: No network operations to unknown domains or sensitive file access patterns were detected. The skill specifically warns against using real domains for test emails.
- [CREDENTIALS_UNSAFE]: No hardcoded credentials or instructions to handle secrets unsafely were identified. The examples use generic, synthetic data.
Audit Metadata