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Cloud Deception Deployment

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Implement decoy resources for cloud security alerts.

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Free · Opens the source repo

What Cloud Deception Deployment does

Deploying Cloud Deception with Decoy Resources is a skill designed for security professionals looking to enhance their cloud security posture across AWS, Azure, and GCP. This skill enables users to create decoy resources, commonly known as honeytokens, which serve as traps for potential attackers. The primary goal is to generate high-fidelity alerts the moment an attacker interacts with these decoys, allowing for rapid incident response. By leveraging canary IAM access keys, permission-less decoy users, and honey object-storage buckets, organizations can detect unauthorized access and lateral movement within their cloud environments.

The skill is particularly useful for organizations that rely solely on on-premises honeypots and lack cloud coverage. It provides a systematic approach to deploying decoys that mimic the behavior of real resources, enticing attackers to engage with them. This proactive measure not only helps in identifying credential theft and code leaks but also in detecting reconnaissance activities that legitimate users would not perform. By integrating with cloud logging services such as AWS CloudTrail, Azure Sentinel, and GCP Cloud Audit Logs, alerts can be routed to a Security Operations Center (SOC) with minimal false positives.

Users will find a comprehensive workflow that guides them through the decision-making process of what decoys to deploy based on their specific threat model. The skill includes detailed scripts for setting up decoy resources in AWS, Azure, and GCP, ensuring that alerts are triggered and sent to the appropriate monitoring systems. Additionally, it emphasizes the importance of maintaining a plausible naming convention for decoys to avoid detection by attackers while remaining clear to defenders.

This skill is ideal for cloud security engineers, incident response teams, and organizations aiming to enhance their security measures against cloud-based threats. It provides a structured methodology for implementing cloud deception tactics effectively, ensuring that security teams are alerted to potential breaches as soon as they occur.

When to use it

Use this skill when you need to monitor cloud accounts for suspicious activity and lack existing cloud deception measures.

When not to use it

This skill may not be suitable if your cloud environments are already well-instrumented with existing deception techniques or if you lack the necessary permissions to create decoy resources.

What you can build with it

Protecting Sensitive Data

Deploy decoy resources to monitor access to sensitive cloud data, triggering alerts on unauthorized attempts.

Credential Theft Detection

Use honeytokens to catch credential theft by seeding fake credentials that alert when accessed.

Cloud Reconnaissance Monitoring

Detect cloud reconnaissance activities by setting up decoys that legitimate users would not interact with.

How to install Cloud Deception Deployment

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1. Install with the skills CLI

npx skills add mukul975/anthropic-cybersecurity-skills/deploying-cloud-deception-with-decoy-resources --agent claude-code

2. Or install it manually

Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.

Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs

Inside SKILL.md

Written by mukul975

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.

2A. AWS — canary access keys on a permission-less user

Create a decoy IAM user with an explicit deny-all policy, then issue an access key to plant:

aws iam create-user --user-name svc-backup-prod --tags Key=deception,Value=true
aws iam put-user-policy --user-name svc-backup-prod \
  --policy-name deny-all \
  --policy-document '{"Version":"2012-10-17","Statement":[{"Effect":"Deny","Action":"*","Resource":"*"}]}'
aws iam create-access-key --user-name svc-backup-prod   # plant the returned AccessKeyId/Secret

Any use of this key appears in CloudTrail (even denied calls, which still log AccessDenied). Wire an EventBridge rule on CloudTrail to alert:

aws events put-rule --name decoy-key-used \
  --event-pattern '{"detail":{"userIdentity":{"userName":["svc-backup-prod"]}}}'
aws events put-targets --rule decoy-key-used \
  --targets "Id"="1","Arn"="arn:aws:sns:us-east-1:111111111111:soc-deception-alerts"

2B. AWS — honey S3 bucket

Create a believable bucket, enable object-level data events, and alert on any read/list:

aws s3api create-bucket --bucket acme-prod-db-backups-2026 --region us-east-1
aws s3api put-bucket-tagging --bucket acme-prod-db-backups-2026 \
  --tagging 'TagSet=[{Key=deception,Value=true}]'
# Ensure CloudTrail captures S3 data events for this bucket, then alert on GetObject/ListBucket
aws events put-rule --name decoy-bucket-access \
  --event-pattern '{"detail":{"eventSource":["s3.amazonaws.com"],"requestParameters":{"bucketName":["acme-prod-db-backups-2026"]}}}'

2C. AWS — decoy secret

aws secretsmanager create-secret --name prod/db/master-password \
  --secret-string '{"username":"dbadmin","password":"DECOY-DO-NOT-USE"}' \
  --tags Key=deception,Value=true
# Alert on GetSecretValue for this secret via EventBridge -> SNS

3A. Azure — honeytoken watchlist + decoy service principal

Microsoft Sentinel natively supports honeytokens via a Watchlist of the HoneyTokens template; tagged decoy accounts/secrets raise analytics alerts on use. Create a permission-less decoy app registration / service principal, then add its identifiers to the HoneyTokens watchlist and enable the related analytics rules. Microsoft Defender for Cloud and Entra ID Protection surface anomalous sign-ins to the decoy identity.

3B. Azure — honey storage + Key Vault decoy secret

Create a decoy Storage account and Key Vault, enable diagnostic logging to the Sentinel workspace, store a decoy secret, and write an analytics rule that fires on any data-plane read of the decoy resources.

4A. GCP — decoy service account + honey GCS bucket

Create a service account with no role bindings (permission-less), generate a key to plant, and alert on its use via Cloud Audit Logs:

gcloud iam service-accounts create svc-billing-export \
  --display-name="billing-export"
gcloud iam service-accounts keys create decoy-key.json \
  --iam-account=svc-billing-export@PROJECT.iam.gserviceaccount.com   # plant this key
gsutil mb -b on gs://acme-finance-exports-2026

Create a log-based metric + alerting policy in Cloud Monitoring that triggers on any audit-log entry where the principal is the decoy service account or the resource is the honey bucket.

5. Centralize and de-duplicate

Route all clouds' decoy alerts to one SOC pipeline. Tag each alert as DECEPTION/high-fidelity so it bypasses normal noise filtering and triggers an IR playbook rather than a triage queue.

6. Validate (red-team the decoys)

Have an authorized tester use each decoy (read the bucket, call with the key, fetch the secret) and confirm an alert lands end-to-end within target latency. A decoy you have not tested is assumed broken.

7. Maintain realism and rotate

Refresh decoy names, secrets, and pocket-litter periodically so they age with the real environment. Track every decoy in an inventory so they are never mistaken for real assets during audits or cleanups.

Key Concepts

ConceptDefinition
Decoy / honey resourceA cloud object created solely to be touched by an attacker; no legitimate user has any reason to use it.
Canary access keyA planted credential whose use generates an audit-log event; carries deny-all permissions.
High-fidelity alertA near-zero-false-positive signal because legitimate workflows never reference the decoy.
Permission-less principalA decoy IAM user/role/service principal/service account with explicit deny-all or no role bindings.
Data eventCloud audit logging of object/data-plane access (e.g., S3 GetObject), required to detect storage decoys.
Pocket litterPlausible supporting artifacts (fake configs, env files, wiki entries) that make a decoy credible.
Decoy inventoryThe authoritative internal record distinguishing decoys from real assets.

Tools & Systems

  • AWS — IAM (decoy users/roles), S3 (honey buckets, data events), Secrets Manager / SSM Parameter Store (decoy secrets), CloudTrail, EventBridge, SNS/Lambda, GuardDuty (correlate anomalous use).
  • Azure — Microsoft Entra ID (decoy app registrations / service principals), Storage / Key Vault decoys, Microsoft Sentinel HoneyTokens watchlist and analytics rules, Microsoft Defender for Cloud, Entra ID Protection.
  • GCP — IAM service accounts (decoys), Cloud Storage (honey buckets), Secret Manager (decoy secrets), Cloud Audit Logs, log-based metrics + Cloud Monitoring alerting, Pub/Sub.
  • Open-source / managed honeytoken systems — Canarytokens (https://canarytokens.org offers AWS API key tokens), Thinkst Canary, SpaceSiren / SpaceCrab (self-hosted AWS honey-token frameworks).
  • SIEM/SOAR — to centralize alerts across clouds and drive an IR playbook on any decoy hit.

Common Scenarios

  • Credential-theft / code-leak detection. Plant a canary AWS key in CI variables, an env file, and a private repo. Any external use (even from a leaked public push) fires within minutes.
  • Crown-jewel data store. Stand up a honey "backups" bucket next to the real one; attackers enumerating storage hit the decoy first and reveal themselves.
  • Cloud lateral movement. A permission-less decoy service principal that "looks" privileged catches adversaries assuming roles during pivoting.
  • Secrets harvesting. Decoy entries in Secrets Manager / Key Vault / Secret Manager detect tools scraping the secrets store.
  • Migrating from on-prem-only deception. Mirror the existing on-prem decoy strategy into the cloud control plane so coverage follows workloads.

Output Format

Produce a Cloud Deception Deployment Record using assets/template.md, containing:

  1. Decoy inventory — per decoy: cloud, type, plausible name, real placement location of any planted credential, internal deception tag/label, owner.
  2. Detection wiring — per decoy: audit-log source → rule/pattern → alert sink → IR playbook reference, with the target alert latency.
  3. Least-privilege proof — evidence each decoy principal is deny-all / no-role-binding.
  4. Validation results — date tested, who tested, end-to-end latency observed, pass/fail.
  5. Maintenance plan — rotation cadence and review owner.

Use scripts/process.py to render the deployment record and a per-decoy detection checklist from a decoy-inventory JSON, and to flag decoys missing detection wiring or validation.

Frequently asked questions about Cloud Deception Deployment

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