deploying-cloud-deception-with-decoy-resources

deploying-cloud-deception-with-decoy-resources is a skill for Claude Code, Codex from andycungkrinx91/konoha. It costs 224 tokens per session (2,627 once invoked), scanned A, original, MIT.

A guide to creating fake users, keys, storage buckets, secrets, and other resources in AWS, Azure, and Google Cloud. These decoys are designed to alert defenders when someone accesses or searches for them.

In plain words
What is it for?
It helps cloud security teams place tripwires around identity permissions, storage, secrets, and build pipelines, then connect activity on those decoys to their detection and response process.
Why use it?
Cloud attackers can explore accounts and steal credentials without immediately touching real systems. Decoys provide an early warning for unauthorized access, reconnaissance, and movement between cloud resources.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: installed under .agents/ (shared by several agents).

Good fit It helps cloud security teams place tripwires around identity permissions, storage, secrets, and build pipelines, then connect activity on those decoys to their detection and response process.

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Install with agentmods
npx agentmods add skills/andycungkrinx91/konoha/deploying-cloud-deception-with-decoy-resources
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add andycungkrinx91/konoha --skill deploying-cloud-deception-with-decoy-resources
Clone the repo
git clone --depth 1 https://github.com/andycungkrinx91/konoha

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

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README.md
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Your own site
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Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

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Your own site · 80×15
<a href="https://agentmods.dev/skills/andycungkrinx91/konoha/deploying-cloud-deception-with-decoy-resources"><img src="https://agentmods.dev/badge/skills/andycungkrinx91/konoha/deploying-cloud-deception-with-decoy-resources.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 224 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,627 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00224 $0.02627
Opus 5.5 $0.00090 $0.01051
Sonnet 5.5 $0.00045 $0.00525
Haiku 4.5 $0.00022 $0.00263

Measured today against content hash 38a696a5b368, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

deploying-cloud-deception-with-decoy-resources scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/process.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.agents/skills/akatsuki-skill/references/anthropic-cybersecurity-skills-assets/skills/deploying-cloud-deception-with-decoy-resources/SKILL.md · 170 lines

How it starts

The opening of the file, as written. The whole thing — 170 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Deploying Cloud Deception with Decoy Resources

When to Use

  • When cloud accounts (AWS/Azure/GCP) hold crown-jewel data or infrastructure and you need a tripwire that fires the moment an attacker who has gained access starts to operate.
  • When the only deception in place is on-prem honeypots, leaving the cloud control plane uninstrumented.
  • When seeding fake credentials to catch credential theft, accidental code-repo leaks, or secrets exposed in build pipelines.
  • When detecting cloud reconnaissance (enumeration of IAM, storage, or secrets) and lateral movement that legitimate users would never perform.
  • When you want detections that survive into incident response with strong fidelity — a touch on a decoy resource almost always means malicious or unauthorized activity.

This is the cloud counterpart to on-prem honeypot/honeytoken/canary-token deployment skills. For program strategy and how these Activities map to adversary engagement goals, use designing-adversary-engagement-with-mitre-engage.

Prerequisites

  • Cloud admin/IAM permissions to create decoy principals, storage, secrets, and detection wiring, ideally in a dedicated deployment role with least privilege.
  • Cloud audit logging already enabled: AWS CloudTrail (multi-region, with management and relevant data events), Azure Activity log + Microsoft Entra audit/sign-in logs, GCP Cloud Audit Logs (Admin Activity always on; Data Access enabled where needed).
  • A SIEM/alert sink: SNS topic, Microsoft Sentinel workspace, or GCP Pub/Sub + Monitoring, with routing to the SOC.
  • A naming and tagging convention that is plausible to an attacker but unambiguous to defenders internally (e.g., realistic names, plus an internal deception=true tag/label kept out of attacker-visible metadata).
  • Decoy principals must be permission-less (explicit deny-all). The value is the alert, never the access. A decoy that grants real privilege is a liability, not a control.

Workflow

1. Decide what to mimic

Pick decoys that match how your attackers operate: leaked AWS keys (credential theft), an "admin" S3 bucket (data discovery), a prod-db-password secret (secrets harvesting), a privileged-looking service account (cloud lateral movement). Place credential decoys where harvesting tools look: env files, CI variables, code comments, an internal wiki.

Read the full file on GitHub · 170 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. today First seen · 170 lines · 224 tokens per session scan A 38a696a5b368

Subscribe to this mod's changes

deploying-cloud-deception-with-decoy-resources is a skill published in the GitHub repository andycungkrinx91/konoha (12 stars, last pushed today), licensed MIT. It adds 224 tokens to every session and 2,627 once invoked, about $0.0009 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-25.