LangGraph Security

Security considerations for agentic RAG applications built with LangGraph. LangGraph is an orchestration framework for stateful, multi-step LLM agents — its security properties depend on how retrieval tools are configured and whether identity context is maintained correctly across graph nodes.

RAGSec connector status: Research. LangGraph support is under evaluation. If your LangGraph application uses Pinecone, Qdrant, or Weaviate as a retrieval tool, those connectors apply today at the vector store layer.

LangGraph and RAG security

LangGraph adds state management, cycles, and multi-step orchestration to LangChain-based agents. RAG retrieval in a LangGraph application is typically implemented as a tool node that queries a vector store. The security concern is whether the tenant identity available at the graph entry point is reliably passed to every retrieval tool call — and whether the graph’s state model allows a user to influence the identity context used for retrieval.

Key security considerations

• Identity context loss across nodes: Tenant identity established at the graph input may not be explicitly passed to retrieval tool nodes, leading to queries without a tenant filter if not explicitly threaded through the graph state.
• Mutable graph state: LangGraph state is mutable. An adversarial message that manipulates the identity or tenant field in graph state could cause a subsequent retrieval node to use an attacker-controlled tenant value.
• Tool invocation from LLM decisions: When the LLM decides which retrieval tool to call and with what arguments, the arguments may include a tenant or namespace value derived from conversational context that can be influenced by prompt injection.
• Checkpointer storage: LangGraph’s persistence layer (checkpointer) stores graph state, including retrieved content, across turns. If checkpointer storage is not tenant-scoped, a thread ID leak or collision could expose another tenant’s conversation context.
• Parallel and subgraph execution: Parallel branches and subgraphs may each make independent retrieval calls. Tenant context must be consistently propagated to all branches — not only the primary execution path.

Current coverage path

If your LangGraph application retrieves from Pinecone, Qdrant, or Weaviate, connect those stores directly with RAGSec today. The posture scan and active isolation tests apply at the vector store layer, independently of the orchestration framework.