db-seeder
Warn
Audited by Gen Agent Trust Hub on Oct 6, 2026
Risk Level: MEDIUMCREDENTIALS_UNSAFECOMMAND_EXECUTIONINDIRECT_PROMPT_INJECTIONDYNAMIC_EXECUTION
Full Analysis
- [CREDENTIALS_UNSAFE]: The skill provides instructions and scripts designed to automatically scan the project environment for sensitive configuration files, including .env, settings.py, and alembic.ini, specifically to extract database connection strings and credentials.
- Evidence: This behavior is documented in
SKILL.mdunder the 'Detect Database Configuration' section and inreferences/database-configs.md. - [DYNAMIC_EXECUTION]: The skill's configuration template utilizes string-encoded lambda functions for generating data, indicating that the orchestrator performs runtime evaluation (eval/exec) of these configuration strings.
- Evidence: Found in
assets/seed-config-template.yamlwhere fields likeusernameare mapped to values such aslambda fake: fake.user_name(). - [COMMAND_EXECUTION]: The seeding configuration schema includes a hooks section that allows for the definition and execution of arbitrary shell commands after the seeding process completes.
- Evidence:
assets/seed-config-template.yamldefines ahookssection with examples such aspython scripts/update_search_index.py. - [INDIRECT_PROMPT_INJECTION]: The skill features a tool for automated database schema inspection that ingests untrusted metadata (table and column names) to generate Python factory code and JSON fixtures, creating a risk if the metadata contains malicious instructions.
- Ingestion points: Database schema metadata ingested by
scripts/inspect_schema.py(referenced inSKILL.md). - Boundary markers: None described for the schema analysis or code generation steps.
- Capability inventory: The skill can write files (factory generation) and perform database writes (seeding).
- Sanitization: No sanitization of table or column names derived from the external schema is described before they are used to generate code.
Audit Metadata