# Blocked Word List: managed and custom terms you never want through

> Blocked Word List pairs a maintained baseline with per-tenant custom terms, so the system catches both universal risks and the ones unique to your business.

**Category:** Prompt Injection
**Author:** NeuralSeek Team · **Published:** June 9, 2026
**Canonical:** https://neuralseek.ai/ai-grounded/blocked-word-list
**Section index:** https://neuralseek.ai/ai-grounded

Blocked Word List is one of NeuralSeek's Prompt Injection guardrails — part of the platform's 118 individually configurable, fully auditable controls. In regulated, high-volume AI, the difference between a system you can trust and one you merely hope works comes down to specific, tunable controls exactly like this one. Here is what Blocked Word List does, why it matters to the business, and how to set it for your own environment.

## What it actually does

This is the managed and customer-supplied list of terms the system watches for. NeuralSeek maintains a baseline, and each tenant extends it with the words specific to its own risk profile.

## Why business teams care

Every organization has vocabulary it must catch — competitor traps, sensitive project names, known attack triggers — that a generic list won't cover. A custom, per-tenant list closes that gap without code.

## How to tune it in practice

Seed it with the managed baseline, then add the terms unique to your domain and review it as new risks appear. Treat it as living policy rather than a one-time setup.

## Common failure modes it prevents

Adversaries probe production AI constantly, hiding instructions in user input, pasted text, and retrieved documents to hijack how the model behaves. Blocked Word List closes that gap directly. By making the behavior an explicit, enforced control rather than something left to chance, it converts a latent risk into a managed, observable event — one that surfaces in the audit trail instead of in a customer complaint or a compliance finding.

## Where it fits in the stack

It runs early in the request pipeline, screening input before it can reach the model or contaminate retrieval. Because it lives in NeuralSeek's governance layer rather than inside any single model, the control holds identically whether a request routes to OpenAI, Anthropic, Gemini, Llama, Mistral, IBM watsonx, or an in-house model.

## Defense that updates with the threat

Attack patterns evolve, so this control is curated from real production attacks and refreshed as new techniques emerge — the protection you ship with keeps pace with the adversaries you actually face.

> Generic filters catch the obvious. Your blocklist catches what's dangerous to you specifically.

## The takeaway

Blocked Word List pairs a maintained baseline with per-tenant custom terms, so the system catches both universal risks and the ones unique to your business.

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From NeuralSeek's AI Grounded — practical, web-verified guidance on building governed, grounded enterprise AI. NeuralSeek is the model-agnostic, governed AI platform you own: any LLM (swap with no rebuild), your data in your own tenant (cloud or on-prem), 118 guardrails enforced before any action, one container that runs anywhere.