senior-ml-engineer
Pass
Audited by Gen Agent Trust Hub on Mar 19, 2026
Risk Level: SAFEPROMPT_INJECTION
Full Analysis
- [PROMPT_INJECTION]: The skill contains several examples of LLM prompt construction vulnerable to indirect prompt injection.
- Ingestion points: In
references/llm_integration_guide.md, theFEW_SHOT_TEMPLATEacceptsuser_inputdirectly. Inreferences/rag_system_architecture.md, theRAGPipelineingestscontextretrieved from a vector database (potentially containing untrusted data) and user queries. - Boundary markers: There are no robust boundary markers or "ignore instructions" delimiters used in the prompt templates. For example,
FEW_SHOT_TEMPLATEsimply appends the input after a label, andRAGPipeline._build_promptuses basic f-string interpolation. - Capability inventory: The skill includes scripts for model deployment (
scripts/model_deployment_pipeline.py) and infrastructure setup, which could be exploited if an agent following these instructions is influenced by malicious instructions in the data. - Sanitization: No sanitization, escaping, or validation of the interpolated strings is present in the example code.
Audit Metadata