skills/jeremylongshore/tons-of-skills-marketplace/langchain-reference-architecture/Gen Agent Trust Hub
langchain-reference-architecture
Pass
Audited by Gen Agent Trust Hub on Sep 9, 2026
Risk Level: SAFEINDIRECT_PROMPT_INJECTION
Full Analysis
- [INDIRECT_PROMPT_INJECTION]: The reference architecture defines multiple ingestion points where untrusted data enters the agent context, creating a potential attack surface for indirect prompt injection.\n
- Ingestion points: Untrusted data enters the system through FastAPI HTTP route handlers (e.g.,
app/routes/support.py) and via retrieval from external vector stores (e.g.,adapters/retriever_factory.py).\n - Boundary markers: The provided code snippets demonstrate structural layering but do not explicitly include the use of prompt delimiters or specific instructions to ignore embedded commands in the processed data.\n
- Capability inventory: The resulting agent systems are configured with capabilities to perform network requests to external LLM providers (Anthropic, OpenAI, Google) and execute database operations for persistence and checkpointing.\n
- Sanitization: The architectural patterns focus on dependency management and layer enforcement; explicit input sanitization or content filtering for prompt interpolation is not included in this high-level reference.
Audit Metadata