Security Hardening

Organization

adobe

security-hardening

Perform security audits for the Adobe Dispatcher Apache HTTP Server module and Apache HTTPD in AEMaaCS cloud workflows only, with cloud-specific hardening verification.

Overview

Publisher	adobe
Repository	`skills`
Skill name	`security-hardening`
Stars	298
Forks	92
Bundled files	17
License	Apache-2.0
Links	Skill source Repository Homepage

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.
17 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by adobe on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/adobe/skills/tree/main/plugins/aem/cloud-service/skills/dispatcher/security-hardening
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/adobe/skills/tree/main/plugins/aem/cloud-service/skills/dispatcher/security-hardening

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

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/adobe/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/plugins/aem/cloud-service/skills/dispatcher/security-hardening .claude/skills/security-hardening

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Security Hardening 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 Security Hardening 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 Security Hardening 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.

Dispatcher Security Hardening (Cloud)

Deliver evidence-backed security findings and remediations for cloud workflows that use the Adobe Dispatcher Apache HTTP Server module and related HTTPD configuration.

Variant Scope

This skill is cloud-service-only.
Scope is fixed by this skill directory; do not ask the user to choose deployment variant.

MCP Tool Contract

Use only these Dispatcher MCP tools:

validate
lint
sdk
trace_request
inspect_cache
monitor_metrics
tail_logs

Workflow

Define threat model and audit scope.
Apply cloud guardrails (immutable/default include constraints, reserved probe-path behavior, and CDN-vs-Dispatcher ownership).
Gather baseline evidence (validate, lint, sdk).
Verify exposure controls (trace_request).
Verify cache/header protections (inspect_cache, tail_logs, monitor_metrics).
Return risk-rated findings, prioritized remediation, and rollback.

Verification Scope Selection

Use shared references to select security evidence depth:

mode-specific-verification-matrix.md
test-case-catalog.md

Output Contract

Always return:

scope + threat model assumptions
risk-rated findings table
evidence table (tool/input/result)
prioritized remediation plan
selected test IDs and outcomes
rollback plan and residual risk

Guardrails

Do not downgrade severity without evidence.
Do not claim a control is effective without verification evidence.
Keep cloud assumptions explicit for each remediation recommendation.
Separate mandatory remediations from defense-in-depth guidance.
Separate Dispatcher hardening findings from CDN/WAF edge-policy findings.

References

security-baseline-checklist.md
security-scenario-playbooks.md – scenario-driven security workflows adapted from broader MCP prompt surfaces
security-headers-checklist.md
sensitive-paths-catalog.md
owasp-coverage-matrix.md
security-audit-report-template.md
quick-start-execution-path.md – single entry path for broad or first-time audits
repo-layout-workflows.md – map findings to actual dispatcher file families
playbook-command-linkage.md – exact MCP command chains for security playbooks
mode-specific-verification-matrix.md
cloud-service-aemaacs-guardrails.md – cloud-service-only immutable/include/runtime boundary checks from AEMaaCS patterns
test-case-catalog.md
change-risk-and-rollback-template.md
public-docs-index.md
public-doc-citation-rules.md
core-7-tools-reference.md

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Security Hardening AI skill do?

Perform security audits for the Adobe Dispatcher Apache HTTP Server module and Apache HTTPD in AEMaaCS cloud workflows only, with cloud-specific hardening verification.

Why use Security Hardening on TypingMind?

Because you install it once and use it with any model. Security Hardening 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 Security Hardening in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/adobe/skills/tree/main/plugins/aem/cloud-service/skills/dispatcher/security-hardening. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Security Hardening?

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 Security Hardening?

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

Is the Security Hardening AI skill free?

Yes. It is published on GitHub by adobe 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Dispatcher Security Hardening (Cloud)

Variant Scope

MCP Tool Contract

Workflow

Verification Scope Selection

Output Contract

Guardrails

References

Bundled files

Frequently asked questions

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