Omh Application Threat Model logo

Omh Application Threat Model

CommunityPopular
rlaope
omh-application-threat-model

[omh] Application threat model workflow: turn a system's components and data flows into assets, trust boundaries, attack scenarios, controls, and the security test that proves each control holds. Use when the user says: application-threat-model, application threat model, threat model, threat modeling, threat modelling, threat modeling session, threat modeling workshop, security threat model.

Overview

Publisherrlaope
Repositoryoh-my-hermes
Skill nameomh-application-threat-model
Stars
2.7K
Forks
194
Bundled files
1
LicenseMIT
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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Omh Application Threat Model 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.
  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/rlaope/oh-my-hermes.git /tmp/oh-my-hermes
mkdir -p .claude/skills
cp -r /tmp/oh-my-hermes/agent-skills/omh-application-threat-model .claude/skills/omh-application-threat-model
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Omh Application Threat Model 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 Omh Application Threat Model 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 Omh Application Threat Model 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.

Application Threat Model

This is an OMH application-threat-model workflow skill, projected for Agent Skills hosts (Claude Code, Codex, Cursor, opencode, OpenClaw, pi).

Why This Exists

application-threat-model exists because the nearest neighbour does not merely miss this request. security-safety-review maps the agent's own prompt, tool, credential, and dependency surface, so an application threat-model request came back as an agent tool inventory under a near-identical name — a confident wrong artifact rather than a miss, in the one domain where that costs most.

Do Not Use When

  • The subject is the agent's own prompts, tools, files, credentials, dependencies, or destructive actions; use security-safety-review, which maps that runtime surface.
  • The user wants defects found in a diff or a file; use code-review.
  • The user asks whether a release is ready across rollout, rollback, and observability; use production-audit.
  • The user asks which commands prove a merge is safe; use verification-gate.
  • The user asks for a contractual or regulatory obligation rather than an attacker; use legal-compliance-review.

Examples

Good example:

  • Prompt: build a threat model for our payment service architecture
  • Expected behavior: Prepare application_threat_model/v1: ask for the component map and data flows, register card data and settlement records as assets, mark the merchant API edge and the PSP callback as trust boundaries, derive scenarios per boundary, decide a control for each, and name the test that fails when the control is removed.
  • Why: The subject is an application the user operates, and the goal needs assets, boundaries, scenarios, controls, and tests.

Bad example:

  • Prompt: application-threat-model check whether this agent can be prompt-injected through its file tool
  • Expected behavior: Route to security-safety-review: prompts, tools, and credentials are the agent's runtime surface, not an application this workflow models.
  • Why: The two surfaces share vocabulary and nothing else; modeling the agent's runtime here is how the artifacts get confused.

Completion Checklist

  • Every asset carries a data class and one named loss; every boundary names what crosses it and what authenticates the crossing.
  • Every scenario resolves to mitigate, transfer, accept, or eliminate, with an owner.
  • Every mitigating control carries a security test and the observable that fails without it.
  • Controls read deployed, planned, or unverified; none is inferred from the architecture description.
  • Residual risk is listed, and the model is not offered as a scan, a penetration test, or an attestation.

Recovery Notes

  • If the architecture is not described, ask for the component map and the data flows before modeling; never substitute a generic checklist for the real system.
  • If a scenario has no boundary and no asset, drop it with the reason rather than carrying an unreachable threat.
  • If the user asks for exploit code, give the precondition and the detection signal instead, then hand remediation to an executor.
  • If the request turns out to be about the agent's own prompts, tools, or credentials, stop and hand it to security-safety-review.

Use When

Use when Hermes must model the security of an application, service, or deployed system the user operates: which assets are worth taking, where trust changes hands, how an attacker reaches each asset, which control stops them, and which security test fails when that control is removed. The subject is the modeled system, never the agent's own runtime.

Strong routing signals: `application-threat-model`, `application threat model`, `threat model`, `threat modeling`, `threat modelling`, `threat modeling session`, `threat modeling workshop`, `security threat model`, `build a threat model`, `model the threats`, `threat scenarios`, `stride analysis`, `stride model`, `trust boundary`, `trust boundaries`, `attack scenario`, `attack scenarios`, `attack tree`, `attack trees`, `abuse case`, `abuse cases`, `security design review`, `security architecture review`, `architecture security review`, `how would an attacker`, `how could an attacker`, `what could an attacker do`, `attacker perspective`

Catalog Metadata

Category: review Phase: application-threat-model Quality tier: security-safety-gated Reasoning demand: standard

Quality bar:

  • Name every component, data store, and external dependency of the real system before naming one threat; a model of a system nobody described is a checklist.
  • Give each asset a data class and exactly one loss: disclosure, corruption, unavailability, or fraud.
  • For each trust boundary, state what crosses it, what authenticates the crossing, and what the receiver assumes without checking.
  • Run all six STRIDE prompts from omh-application-threat-model/references/threat-model-method.md per boundary; drop an unreachable scenario with its reason instead of carrying it.
  • Resolve every scenario to one decision (mitigate, transfer, accept, eliminate) with an owner, and give every mitigating control a test whose observable fails when the control is removed.

Required inputs:

  • the system under review: components, which component calls which, and where each is deployed
  • data flows and data classes: what every store, queue, and message carries
  • known trust boundaries: authentication points, network edges, tenant separation, third parties
  • controls already deployed, and who owns each
  • scope exclusions and the threat actors in scope

Expert clarification questions:

  • the system under review: components, which component calls which, and where each is deployed
    • English: Which components make up the system, which of them call each other, and where does each one run?
    • Korean: 이 시스템은 어떤 컴포넌트로 구성되고, 서로 어떤 호출 관계이며, 각각 어디에서 실행되나요?
  • scope exclusions and the threat actors in scope
    • English: Which attackers are in scope — external, authenticated tenant, insider, compromised dependency — and what is out of scope?
    • Korean: 어떤 공격자를 범위에 포함하나요 — 외부, 인증된 테넌트, 내부자, 침해된 의존성 — 그리고 제외 범위는 무엇인가요?

Expected outputs:

  • application_threat_model/v1
  • asset register: data class plus the one loss that makes each asset worth defending
  • trust boundaries: what crosses, what authenticates the crossing, what the receiver assumes unchecked
  • attack scenarios: entry point, path, precondition, impact
  • one decision per scenario (mitigate, transfer, accept, eliminate) with an owner
  • per-control security test naming the observable that fails without it, plus residual risk

Artifact expectations:

  • application_threat_model/v1 with asset register, trust boundaries, attack scenarios, control decisions, and per-control tests
  • every control marked deployed, planned, or unverified; a scenario with no boundary and no asset is dropped, never carried

Safety rules:

  • Never write working exploit code, a payload, or a runnable attack script; a scenario names the entry point, the path, and the precondition, not the weapon.
  • Do not record a control as deployed because the architecture describes it; an unobserved control is unverified until configuration or a passing test says otherwise.
  • Do not model the agent's own prompts, tools, credentials, or dependencies here; that surface belongs to security-safety-review.
  • Never print secrets, tokens, keys, connection strings, or live customer records pulled in as examples.
  • A model is not a penetration test, a scan, or a compliance attestation; name which of the three the user still needs.

Runtime Evidence

Use the current host's own tools and subagent/task mechanism when available; otherwise run the same lanes sequentially or name the unavailable capability. A prepared plan, handoff, checklist, or skill installation is not execution, review, CI, merge-readiness, or merge evidence. Report actual tool results or not_observed / not_available; never invent dispatch or host accounting. Treat supplied context as advisory, not proof of hidden memory reads or writes. State scope, constraints, verification, and the stop condition before work. Supporting paths are relative to this skill directory; sibling skill paths are relative to its parent. Resolve them from the host-provided skill base directory ({baseDir} on hosts that provide it), never a hardcoded install location. A named workflow not installed here is unavailable, not permission to emulate its host-specific capabilities. Verify through the real surface before done.

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 Omh Application Threat Model AI skill do?

[omh] Application threat model workflow: turn a system's components and data flows into assets, trust boundaries, attack scenarios, controls, and the security test that proves each control holds. Use when the user says: application-threat-model, application threat model, threat model, threat modeling, threat modelling, threat modeling session, threat modeling workshop, security threat model.

Why use Omh Application Threat Model on TypingMind?

Because you install it once and use it with any model. Omh Application Threat Model 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 Omh Application Threat Model in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/rlaope/oh-my-hermes/tree/main/agent-skills/omh-application-threat-model. 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 Omh Application Threat Model?

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 Omh Application Threat Model?

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

Is the Omh Application Threat Model AI skill free?

Yes. It is published on GitHub by rlaope under the MIT 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇