Openhound Okta logo

Openhound Okta

Organization
SpecterOps
openhound-okta

Use for OpenHound Okta/OktaHound OpenGraph BloodHound work when the user clearly means Okta semantics such as Okta users, groups, apps, role assignments, super-admin or delegated-admin exposure, API clients and client secrets, MFA or password posture, AD agents, identity providers, inbound or outbound hybrid paths, SCIM provisioning, or GitHub/Azure/Jamf/Entra linked identity paths. Do not use for generic BloodHound path triage, connection checks, explicit Cypher authoring/review, or non-Okta OpenGraph domains.

Overview

PublisherSpecterOps
Repositoryskills
Skill nameopenhound-okta
Stars
706
Forks
80
Bundled files
3
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.

  • 3 bundled files

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

  • Open source

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

Installation

Install the Openhound Okta 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/SpecterOps/skills/tree/main/plugins/bloodhound/skills/openhound-okta
  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/SpecterOps/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/plugins/bloodhound/skills/openhound-okta .claude/skills/openhound-okta
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Openhound Okta 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 Openhound Okta 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 Openhound Okta 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.

OpenHound Okta / OktaHound

Use this skill for OpenHound Okta OpenGraph query design and attack-path triage with OktaHound/OpenHound Okta data.

Required context

  • Authorized Okta organizations and linked identity/application platforms.
  • Whether OktaHound/OpenHound Okta extension/schema/data is loaded and whether optional schemas (SCIM, GitHub, Jamf, Azure/AD, Entra, SaaS integrations) are present.
  • Collector authentication method and scope, such as OAuth private key vs SSWS/API token.
  • Target users, groups, applications, role assignments, client secrets, devices, identity providers, or hybrid links.

Workflow

  1. Read ../../references/docs/bloodhound-query-methodology.md, ../../references/docs/openhound-okta-methodology.md, and ../../references/docs/collector-source-index.md.
  2. If provisioning, SSO, GitHub, Jamf, Entra, or SCIM bridge paths are relevant, read ../../references/docs/scim-methodology.md.
  3. Search ../../references/query-indexes/openhound-okta.md and ../../references/examples/example-cypher.md for a saved-search starting point.
  4. Inspect the referenced JSON snapshot before adapting.
  5. Preserve Okta_ and SCIM_ labels/edges and explicitly document bridge edges in hybrid paths.
  6. Separate app/secret metadata risk from proven secret disclosure and identify collector output/coverage limits.

Common pivots

  • Users/groups to super-admin or delegated-admin capability.
  • App assignments and app credentials/client secret access.
  • API service applications and privileged integrations.
  • MFA/password/device posture queries.
  • AD agents, SCIM links, inbound/outbound federation, GitHub/Azure/Jamf hybrid paths, and other collected SaaS links.

Output

Use the shared output contract from $bloodhound-query and include Okta-specific caveats such as optional schema availability, collector auth scope, linked-platform coverage, secret metadata limitations, and hybrid bridge confidence.

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 Openhound Okta AI skill do?

Use for OpenHound Okta/OktaHound OpenGraph BloodHound work when the user clearly means Okta semantics such as Okta users, groups, apps, role assignments, super-admin or delegated-admin exposure, API clients and client secrets, MFA or password posture, AD agents, identity providers, inbound or outbound hybrid paths, SCIM provisioning, or GitHub/Azure/Jamf/Entra linked identity paths. Do not use for generic BloodHound path triage, connection checks, explicit Cypher authoring/review, or non-Okta OpenGraph domains.

Why use Openhound Okta on TypingMind?

Because you install it once and use it with any model. Openhound Okta 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 Openhound Okta in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/SpecterOps/skills/tree/main/plugins/bloodhound/skills/openhound-okta. 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 Openhound Okta?

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 Openhound Okta?

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

Is the Openhound Okta AI skill free?

Yes. It is published on GitHub by SpecterOps 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.

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