Zetsu

A personal offline RAG system for offensive security knowledge. Ingest your writeups, lab solutions, bug bounty reports, and security blogs, then query them in natural language during engagements. No cloud, no SaaS, your knowledge stays yours. What it does ZETSU turns your accumulated knowledge into a queryable assistant. Instead of grepping through markdown files or remembering which writeup had that certipy command, you ask naturally: It retrieves from your actual notes first, then generates an answer grounded in what you've documented, not generic internet knowledge. Architecture Ingestion pipeline Query pipeline Features FARR extraction: at ingest time, an LLM reads each section of your writeups and extracts structured attack steps (Finding, Action, Reasoning, Result). What you retrieve is a semantic unit, not a random 800-token window. Hybrid retrieval: BM25 for exact token matching (tool names, CVE numbers, CLI flags) + vector search for semantic similarity. RRF fusion combines both. Cross-encoder reranker: reorders retrieved chunks by actual relevance before sending to the LLM. Two response styles: Operator mode leads with exact commands, Concept mode leads with reasoning.