We developed CultRAG, a trust-weighted Retrieval-Augmented Generation system for BLEnD Track 2 (SemEval-2026 Task 7), targeting culturally grounded multiple-choice QA across 30 countries. Built on Llama-3.1-8B-Instruct, the six-phase pipeline integrates entity extraction via spaCy, hybrid BM25+FAISS retrieval with Reciprocal Rank Fusion, country-aware filtering, keyword-based intent detection, tiered prompt routing, anti-leak quality filtering to suppress answer-anchoring artifacts, and trust-weighted document reranking with source-credibility tiers. Ablation analysis across eight cumulative configurations and per-country decomposition identify which components contribute and where retrieval helps versus hurts, informing future directions for confidence-conditioned selective retrieval.