# AI Defense Mechanisms

> AI Defense Mechanisms & Guardrails

- Skill: `j4flmao/ai-defense-mechanisms` (Agent Skill)
- Install (CLI): `npx skillmds@latest add j4flmao/ai-defense-mechanisms`
- Raw SKILL.md: https://api.skillmd.com/api/skills/j4flmao/ai-defense-mechanisms/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Security
- Author: j4flmao (https://skillmd.com/u/j4flmao)
- Updated: 2026-09-21
- Page: https://skillmd.com/skills/j4flmao/ai-defense-mechanisms

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# AI Defense Mechanisms & Guardrails

## PoC Architecture Design

This PoC details the implementation of robust defense architectures for LLM systems, leveraging Semantic Routers and Guardrails to mitigate adversarial attacks.

### Core Mechanics
1. **Semantic Routing:** A fast vector search matches incoming prompts against a database of known malicious intents or topics. If a match is found, the request is blocked before reaching the main LLM.
2. **Input/Output Guardrails (NeMo):** A dedicated secondary LLM (e.g., Llama Guard) evaluates the safety of the user input and the generated output, enforcing strict conversational bounds.
3. **Sanitization:** Stripping control characters, limiting context length, and using delimiters (like XML tags `<user_input>`) to segregate instructions from data.

### Architecture Map

```mermaid
%%{init: {"theme": "default", "flowchart": {"useMaxWidth": true}}}%%
flowchart TD
    subgraph InputPhase ["Input Processing"]
        A["Raw User Input"]
        B["Sanitization & Formatting (XML Tags)"]
    end
    
    subgraph SemanticRouter ["Fast Filtering"]
        C["Vector Embedding Model"]
        D["Cosine Similarity Check"]
        E["Block (Malicious Match)"]
    end
    
    subgraph Guardrails ["NeMo / Llama Guard"]
        F["Input Safety Evaluation"]
        G["Primary LLM Generation"]
        H["Output Safety Evaluation"]
    end
    
    A --> B
    B --> C
    C --> D
    D -->|"High Score"| E
    D -->|"Low Score"| F
    F -->|"Safe"| G
    F -->|"Unsafe"| E
    G --> H
    H -->|"Safe"| I["Return Response"]
    H -->|"Unsafe"| E
```