Defense In Depth logo

Defense In Depth

Organization
RedHatProductSecurity
defense-in-depth

Apply defense-in-depth by layering multiple independent security controls. Use when reviewing system architecture, evaluating whether a single control is the only barrier, or assessing blast radius of a component compromise.

Overview

PublisherRedHatProductSecurity
Repositoryprodsec-skills
Skill namedefense-in-depth
Stars
56
Forks
9
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by RedHatProductSecurity on GitHub. Read the source before you install it.

Installation

Install the Defense In Depth AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/RedHatProductSecurity/prodsec-skills/tree/main/module/skills/defense-in-depth
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/RedHatProductSecurity/prodsec-skills.git /tmp/prodsec-skills
mkdir -p .claude/skills
cp -r /tmp/prodsec-skills/module/skills/defense-in-depth .claude/skills/defense-in-depth
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Defense In Depth in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Defense In Depth on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Defense In Depth is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Defense in Depth

Principle: Security should be viewed holistically. Wherever possible, multiple levels of security controls should be used. No single control provides perfect security, but layering different controls makes attacks extremely complex and unlikely to succeed.

Key Aspects

Layered Security Controls

Implement multiple independent layers, each providing a different line of defense:

LayerExamples
NetworkFirewalls, network segmentation, VPN, private subnets
HostOS hardening, host-based IDS, patch management
ApplicationInput validation, authentication, authorization, output encoding
DataEncryption at rest and in transit, access controls, backup
MonitoringIntrusion detection, log aggregation, alerting, SIEM

Redundancy and Diversity

  • If one layer is compromised, other layers still provide protection
  • Use controls from different vendors or implementations to avoid a single vulnerability defeating all layers
  • Avoid relying on a single security mechanism for any critical protection

Compartmentalization

  • Isolate system components to limit lateral movement after a compromise
  • Use network segmentation, separate namespaces, and distinct trust zones
  • Apply the blast radius test: "If this component is compromised, what else is affected?"

Continuous Monitoring and Updating

  • Continuously update and adapt security measures to address emerging threats
  • Monitor all layers for anomalies, not just the perimeter
  • Regularly test controls through penetration testing and red team exercises

Architecture Review Questions

When reviewing a system's security architecture, ask:

  1. What happens if the firewall/WAF is bypassed? Is there application-level input validation?
  2. What happens if authentication is compromised? Are there authorization checks on every resource?
  3. What happens if a service is breached? Can the attacker move laterally to other services?
  4. What happens if a database is accessed? Is the data encrypted at rest?
  5. What happens if an attacker operates undetected? Are there monitoring and alerting mechanisms?

If any answer is "nothing else protects us," that is a defense-in-depth gap.

Implementation Checklist

  • No critical asset is protected by a single security control alone
  • Network segmentation separates components into trust zones
  • Application-level controls (input validation, authz) exist independently of network controls
  • Data is encrypted at rest and in transit
  • Monitoring and alerting cover all layers (network, host, application)
  • Blast radius of a single component compromise is limited by isolation
  • Controls are regularly tested and updated

References

Frequently asked questions

What does the Defense In Depth AI skill do?

Apply defense-in-depth by layering multiple independent security controls. Use when reviewing system architecture, evaluating whether a single control is the only barrier, or assessing blast radius of a component compromise.

Why use Defense In Depth on TypingMind?

Because you install it once and use it with any model. Defense In Depth is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Defense In Depth in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/RedHatProductSecurity/prodsec-skills/tree/main/module/skills/defense-in-depth. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Defense In Depth?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Defense In Depth?

As many as you like. As long as a model supports skills, you can use Defense In Depth with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Defense In Depth AI skill free?

Yes. It is published on GitHub by RedHatProductSecurity under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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