SEEK: Agentic Knowledge Graph Retrieval for Secure Code Generation
Large Language Models (LLMs) can generate functionally correct code while introducing exploitable security weaknesses, particularly when developers specify functionality without explicit security requirements. Recent state-of-the-art approaches mitigate this problem using external security knowledge, but largely rely on flat similarity-based retrieval over independent artifacts, making it difficult to infer the relevant vulnerability space and retrieve targeted knowledge when direct matches are unavailable. We propose SEEK, an agentic Graph RAG framework for secure code generation that constructs a security knowledge graph using the Common Weakness Enumeration (CWE) taxonomy as its struct...
| Authors | Varun Gadey, Markus Tohn, Lichao Wu et al. |
|---|---|
| Primary category | cs.CR |
| Published | 10 October 2026 |
| Last updated at source | 10 October 2026 |
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