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secure-ai

Implement defense-in-depth security for LLM pipelines and AI integrations.

14|5|Updated Jan 29, 2026
Search Tags:#ai security#prompt injection#zero trust#agent security#llm security#owasp llm
One-click install
npx skills add https://github.com/oakoss/agent-skills --skill secure-ai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: secure-ai
Source: https://github.com/oakoss/agent-skills/tree/main/skills/secure-ai
Command: npx skills add https://github.com/oakoss/agent-skills --skill secure-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill addresses critical security vulnerabilities in AI integrations, protecting against prompt injection, data leakage, and unauthorized access, ensuring the integrity and safety of your AI-powered applications.

Core Features & Use Cases

  • Prompt Injection Defense: Implements multi-layered strategies to prevent malicious inputs from hijacking AI behavior.
  • Data Leakage Prevention: Secures sensitive information through output validation and stream scrubbing.
  • Agentic Security: Enforces zero-trust principles for autonomous agents, including identity management and least privilege.
  • Use Case: When deploying an AI chatbot that handles customer data, use this Skill to ensure that user inputs cannot trick the AI into revealing sensitive information or executing unauthorized commands.

Quick Start

Use the secure-ai skill to implement defense-in-depth for your LLM integrations.

Frequently Asked Questions about secure-ai

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I prevent prompt injection attacks in my LLM pipeline?▼

Prevent prompt injection attacks by applying multi-layered defense-in-depth strategies that validate model outputs and scrub streams to block malicious inputs from hijacking AI behavior or executing unauthorized commands.

What is zero-trust security for autonomous agents?▼

Zero-trust security for autonomous agents enforces identity management and least privilege principles, ensuring agents operate under strict access controls to prevent privilege escalation and data leakage.

How do I secure MCP tool integrations against data leakage?▼

Secure MCP tool integrations by validating model outputs and applying defense-in-depth controls around server actions interacting with AI services, ensuring sensitive information is not exposed through unauthorized access.

Does this approach satisfy the OWASP LLM Top 10 requirements?▼

Yes, this approach satisfies OWASP LLM Top 10 requirements by addressing critical vulnerabilities including prompt injection defense, agentic security, and AI supply chain requirements for LLM integrations.

How do I audit AI system access patterns for privilege escalation?▼

Audit AI system access patterns by implementing zero-trust controls and monitoring server actions interacting with AI services, detecting unauthorized access attempts and preventing privilege escalation across your LLM pipelines.

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