besser-generators
Pass
Audited by Gen Agent Trust Hub on Sep 22, 2026
Risk Level: SAFEINDIRECT_PROMPT_INJECTIONCOMMAND_EXECUTIONDYNAMIC_EXECUTION
Full Analysis
- [INDIRECT_PROMPT_INJECTION]: The skill describes a system that generates code based on external inputs (B-UML models).
- Ingestion points: Generators ingest
DomainModel,GUIModel, andAgentmodels from files likeSKILL.mdandreferences/api-and-web.md. - Boundary markers: No explicit boundary markers or instructions to ignore embedded commands are documented for the generated code.
- Capability inventory: The skill documents file system writes (creation of
output/directories and source files) and subprocess execution (DjangoGeneratorandSQLGenerator). - Sanitization: The
SKILL.mdinstructions explicitly note that method bodies forBALorCODEimplementation types are inserted verbatim into generated handlers, which could allow malicious code injection if the source model is attacker-controlled. - [COMMAND_EXECUTION]: Several generators utilize shell commands or subprocesses to complete their tasks.
DjangoGeneratorinreferences/api-and-web.mdrunsdjango-admin startprojectandmanage.py startapp.SQLGeneratorinreferences/persistence.mdexecutes a Python subprocess to generate DDL artifacts.- [DYNAMIC_EXECUTION]: The skill facilitates the creation of executable content from model definitions.
- The system allows users to provide raw code strings (
MethodImplementationType.CODE) that are compiled or interpreted in the generated application. PydanticGeneratordynamically translates OCL constraints into Python validator logic.
Audit Metadata