ai-ml-integration
Pass
Audited by Gen Agent Trust Hub on Feb 17, 2026
Risk Level: SAFE
Full Analysis
- [Data Exposure & Exfiltration] (SAFE): The templates prioritize environment variables for sensitive API keys (e.g., OPENAI_API_KEY) and use safe placeholders in documentation. No hardcoded secrets or unauthorized network exfiltration vectors were identified.
- [Indirect Prompt Injection] (LOW): The README.md includes a RAG pipeline integration example that interpolates untrusted user queries and retrieved context into a prompt without explicit boundary markers or sanitization. 1. Ingestion points: user_query and context variables in the RAG example in README.md. 2. Boundary markers: Absent. 3. Capability inventory: complete() method defined in llm-config.ts for provider communication. 4. Sanitization: Absent. This represents a known architectural surface for indirect prompt injection.
- [Unverifiable Dependencies & Remote Code Execution] (SAFE): The code depends on the standard 'numpy' library for vector operations and does not involve remote script execution, dynamic code generation, or unsafe deserialization.
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