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Cloud Recon Secret Harvest

Organization
CDESpace
Cloud Recon Secret Harvest

Triage a cloud control-plane alert where an actor reads broadly across the account — Describe/List sweeps across regions and services, subscription-wide enumeration bursts, mass reads from secret stores such as Secrets Manager, SSM, or Key Vault, and instance-password pulls. Reads the actor and the shape of the reading to tell a known inventory or posture scanner apart from a credential mapping its blast radius or harvesting secrets, and decides escalate or dismiss.

Overview

PublisherCDESpace
RepositoryDetection-Skills
Skill nameCloud Recon Secret Harvest
Stars
57
Forks
5
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 CDESpace on GitHub. Read the source before you install it.

Installation

Install the Cloud Recon Secret Harvest 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/CDESpace/Detection-Skills/tree/main/skills/triage/cloud-recon-secret-harvest
  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/CDESpace/Detection-Skills.git /tmp/Detection-Skills
mkdir -p .claude/skills
cp -r /tmp/Detection-Skills/skills/triage/cloud-recon-secret-harvest .claude/skills/cdespace-cloud-recon-secret-harvest
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cloud Recon Secret Harvest 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 Cloud Recon Secret Harvest 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 Cloud Recon Secret Harvest 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.

Triage Steps

This class fires on read-only API calls — Describe, List, GetSecretValue — and reads are cheap and constant, run all day by posture scanners, inventory tools, and the application service identities that legitimately consume those exact secrets. So the fact that something read is never the signal; a single fetch means almost nothing. The signal is the shape of the reading: how broad it is, how fast, and who is doing it. A credential validating what it can reach sweeps wider and faster than the actor's normal baseline. Triage here is reading that shape and deciding whether it looks like a routine scanner doing its rounds or someone casing the account — escalate or dismiss. This class turns on reading existing secrets and keys — the breadth and speed of the reads — distinct from creating a new credential or grant, which is a different class; a read that immediately precedes or feeds a credential creation by the same actor is corroboration that points at a real threat, not something the reader's identity waves off.

Start from this detection's track record on this actor and scope — a sweep rule that fires whenever the posture scanner runs and is always closed benign starts the call near dismiss — then read the leads below. None is required on its own; they stack, and a single strong one (a human key sweeping every region it has never touched) can carry the call.

Leads that point to a real threat — what to look for in the data:

  • Breadth the actor never shows. Enumeration or secret reads spanning resources, services, or regions this actor never touches — Describe*/List* across every region at once, GetSecretValue walking an entire secret store. A credential mapping its blast radius reads everywhere; a normal consumer reads its own corner.
  • Burst velocity where a human clicks. An automated cadence — hundreds of reads in seconds — from an identity that normally makes a few scoped calls by hand. The machine-speed pattern from a human actor is the tell.
  • A risky or new actor doing the reading. A freshly created identity, a leaked-key candidate, or a human key behaving like a tool — an interactive identity running a region-wide sweep. The identity directory (Graph/Okta users, risky-users, service-principals) tells you how new the identity is and what kind it is; the actor type tilts hard here even before the breadth does.
  • High-value material, or reads next to other moves. The sweep hits root or admin credentials, production database secrets, or signing keys — the data-security context flags what they guard (Cyera datastores, Wiz sensitive-data) — or the burst sits right next to an IAM grant or precedes data movement by the same actor. Casing that lands on the crown jewels, or chains into the next step, is the strongest shape.

Leads that rule it out — benign context you can actually see in the data; if the data doesn't show it, you don't have it:

  • The actor explains it, and the reads fit its documented job. A confirmed posture, inventory, or backup scanner sweeping as it always does, or a named secrets-consuming service identity reading the specific set it is provisioned to consume, on its documented cadence and within its baseline scope. The identity alone is not enough — a secrets consumer walking the whole store, beyond the corner it normally reads, is not ruled out by being automation, and a first-time-seen pattern for this identity is not proof it is benign.
  • It matches the baseline. The same actor, scope, and read volume have appeared here before as normal activity; volume well inside this actor's normal range.
  • Scoped, not a sweep. A single named fetch by an engineer in context, or reads confined to the resources and region this actor owns — not a cross-region, cross-service walk.
  • Broad fleet pattern, not one actor casing. The same read pattern runs on a fixed cadence across the account as scheduled scanning — the shape of inventory tooling, which sweeps by design; a credential casing the account is a single off-baseline actor.
  • Clean history. Prior dispositions for the same actor-and-scope closed benign, with nothing new in the breadth or velocity this time.

To confirm a lead instead of guessing, pull the thread: did the same actor make an IAM grant, share a snapshot, or pull a volume in the same window after the reads? Corroboration turns a suspicious sweep into a confirmed one.

Output

Decision

  • escalate: enumeration or secret reads span resources or regions the actor never touches, show burst velocity where a human normally clicks, or the actor is newly created, a leaked-key candidate, or a human key behaving like a tool — especially when the reads hit high-value material or chain into a grant or data movement.
  • dismiss: a confirmed posture/inventory/backup scanner, or the service identity that legitimately consumes those secrets, reads at a steady baseline within its normal scope and volume. A dismiss is a positive call that the reading is benign, made with that context in hand — a scanner you confirmed, a scope and cadence you actually saw in its baseline; an actor you couldn't resolve or a baseline you couldn't establish is not that context, and absence of a bad sign is not proof it's good. Dismiss is logged and reopenable; when the benign context is missing or you're unsure — or the breadth or velocity is off-baseline and the actor is risky — escalate.

Evidence

The actor and whether it is the owning service, a confirmed scanner, a human, or a new/risky identity; the breadth (regions, services, secrets touched) versus baseline; the read volume and velocity; the sensitivity of what was read; and any adjacent grant or data movement by the same actor.

Reasoning

Name the leads that decided it and how they stacked — a leaked-key candidate sweeping Describe across every region then pulling production database secrets is escalate on its own; a known posture scanner running its usual List sweep within baseline is dismiss.

Frequently asked questions

What does the Cloud Recon Secret Harvest AI skill do?

Triage a cloud control-plane alert where an actor reads broadly across the account — Describe/List sweeps across regions and services, subscription-wide enumeration bursts, mass reads from secret stores such as Secrets Manager, SSM, or Key Vault, and instance-password pulls. Reads the actor and the shape of the reading to tell a known inventory or posture scanner apart from a credential mapping its blast radius or harvesting secrets, and decides escalate or dismiss.

Why use Cloud Recon Secret Harvest on TypingMind?

Because you install it once and use it with any model. Cloud Recon Secret Harvest 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 Cloud Recon Secret Harvest in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/CDESpace/Detection-Skills/tree/main/skills/triage/cloud-recon-secret-harvest. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Cloud Recon Secret Harvest?

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 Cloud Recon Secret Harvest?

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

Is the Cloud Recon Secret Harvest AI skill free?

Yes. It is published on GitHub by CDESpace 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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