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Cloud Audit

Community
briiirussell
cloud-audit

Audit cloud infrastructure (AWS, GCP, Azure) for misconfigurations, excessive permissions, and security gaps. Use when the user mentions 'cloud security,' 'cloud audit,' 'AWS security,' 'GCP security,' 'Azure security,' 'IAM audit,' 'S3 bucket,' 'cloud misconfiguration,' 'cloud hardening,' or needs to review cloud infrastructure security.

Overview

Publisherbriiirussell
Repositorycybersecurity-skills
Skill namecloud-audit
Stars
429
Forks
60
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Cloud Audit 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/briiirussell/cybersecurity-skills/tree/main/skills/cloud-audit
  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/briiirussell/cybersecurity-skills.git /tmp/cybersecurity-skills
mkdir -p .claude/skills
cp -r /tmp/cybersecurity-skills/skills/cloud-audit .claude/skills/cloud-audit
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cloud Audit 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 Audit 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 Audit 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.

Cloud Audit — Cloud Infrastructure Security Review

Audit cloud infrastructure configurations for misconfigurations, excessive permissions, public exposure, and compliance gaps. Covers AWS, GCP, and Azure.

Cross-references: iam-audit for the consultant-style IAM deep-dive (design / audit / migrate across identity providers and federation patterns) — this skill includes an IAM section but stays at the cloud-posture level; for role design, JIT access, workload identity federation, and migration plans, invoke iam-audit. container-audit for Kubernetes-specific posture sitting on top of cloud. secrets-audit for secrets-manager hygiene and rotation.

Findings should use the three-disposition rule (Fixed / Deferred / Accepted Risk) per owasp-audit's Report Format.

Scope the Audit

Identify:

  1. Cloud provider(s) and account(s)
  2. Regions in use
  3. Whether CLI tools are available (aws, gcloud, az) or reviewing IaC files (Terraform, CloudFormation, Pulumi)

Audit Categories

Identity and Access Management

AWS:

bash
aws iam get-account-summary
aws iam list-users
aws iam generate-credential-report && aws iam get-credential-report --output text --query Content | base64 -d

Check for: root account usage without MFA, access keys older than 90 days, unused credentials, wildcard permissions ("Action": "*"), overprivileged roles.

GCP:

bash
gcloud projects get-iam-policy $PROJECT_ID
gcloud iam service-accounts list

Check for: primitive roles (Owner/Editor) on too many principals, unused service accounts, service account keys instead of workload identity.

Azure:

bash
az role assignment list --all
az ad user list

Check for: excessive Owner/Contributor assignments, guest users with high privileges.

IaC review: Grep Terraform/CloudFormation files for "Action": "*", "Resource": "*", hardcoded secrets, overly broad trust policies.

Network Security

Check for:

  • Security groups or firewall rules allowing 0.0.0.0/0 ingress
  • Unrestricted SSH (port 22) or RDP (port 3389) from the internet
  • VPC flow logs disabled
  • Databases in public subnets
  • Missing network segmentation between tiers

Storage

AWS S3:

bash
aws s3api list-buckets
aws s3api get-public-access-block --bucket <name>
aws s3api get-bucket-policy --bucket <name>
aws s3api get-bucket-encryption --bucket <name>

Check for: public buckets, missing encryption, no versioning, no lifecycle policies, overly permissive bucket policies.

GCP/Azure: Equivalent checks for Cloud Storage and Blob Storage — look for allUsers/allAuthenticatedUsers access or anonymous blob access.

Compute

  • IMDSv2 enforced? (AWS: HttpTokens = required)
  • Unencrypted EBS volumes or disks
  • Public IP addresses on instances that don't need them
  • Outdated AMIs or images (check patch age)
  • Privileged containers, missing security contexts in Kubernetes

Logging and Monitoring

  • CloudTrail / Cloud Audit Logs / Activity Log enabled in all regions
  • Log storage: encrypted, immutable, adequate retention
  • GuardDuty / Security Command Center / Defender for Cloud enabled
  • Alerting configured for: root login, IAM changes, security group changes, large data transfers
  • VPC Flow Logs and DNS query logs enabled

Secrets Management

  • Hardcoded secrets in source code, environment variables, or IaC files
  • Secrets Manager / Key Vault usage for sensitive values
  • KMS key rotation configured

Output Format

markdown
# Cloud Security Audit Report
## Account(s): [account ID(s)]
## Provider: [AWS/GCP/Azure]
## Regions: [audited regions]
## Date: [date]

### Summary
- Total findings: X
- Critical: X | High: X | Medium: X | Low: X

### Findings

#### [SEVERITY] [Category]: [Title]
**Resource:** [resource ARN/ID]
**Region:** [region]

**Issue:** [What the misconfiguration is]

**Risk:** [What an attacker could do]

**Evidence:** [CLI output or IaC snippet]

**Remediation:** [Specific fix command or IaC change]

---

### Prioritized Action Plan
1. [Critical — immediate]
2. [High — this week]
3. [Medium — this month]
4. [Low — next quarter]

Boundaries

  • Only audit accounts or projects the user has access to
  • Do not attempt to access other accounts or tenants
  • Provide remediation for every finding
  • Note if a fix might impact availability (e.g., tightening a security group could break connectivity)
  • Flag any evidence of active compromise found during the audit
  • Refuse requests to exploit found misconfigurations on others' infrastructure

References

  • CIS Benchmarks for AWS/GCP/Azure
  • AWS Well-Architected Security Pillar
  • ScoutSuite (multi-cloud auditing tool)

Frequently asked questions

What does the Cloud Audit AI skill do?

Audit cloud infrastructure (AWS, GCP, Azure) for misconfigurations, excessive permissions, and security gaps. Use when the user mentions 'cloud security,' 'cloud audit,' 'AWS security,' 'GCP security,' 'Azure security,' 'IAM audit,' 'S3 bucket,' 'cloud misconfiguration,' 'cloud hardening,' or needs to review cloud infrastructure security.

Why use Cloud Audit on TypingMind?

Because you install it once and use it with any model. Cloud Audit 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 Audit in TypingMind?

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

Which AI models can use Cloud Audit?

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 Audit?

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

Is the Cloud Audit AI skill free?

Yes. It is published on GitHub by briiirussell 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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