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Auditing Terraform Infrastructure For Security

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mukul975
auditing-terraform-infrastructure-for-security

Auditing Terraform infrastructure-as-code for security misconfigurations using Checkov, tfsec, Terrascan, and OPA/Rego policies to detect overly permissive IAM policies, public resource exposure, missing encryption, and insecure defaults before cloud deployment.

Overview

Publishermukul975
RepositoryAnthropic-Cybersecurity-Skills
Skill nameauditing-terraform-infrastructure-for-security
Stars
34.3K
Forks
4.2K
Bundled files
2
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.

  • 2 bundled files

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

  • Open source

    Published by mukul975 on GitHub. Read the source before you install it.

Installation

Install the Auditing Terraform Infrastructure For Security 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/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/auditing-terraform-infrastructure-for-security
  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/mukul975/Anthropic-Cybersecurity-Skills.git /tmp/Anthropic-Cybersecurity-Skills
mkdir -p .claude/skills
cp -r /tmp/Anthropic-Cybersecurity-Skills/skills/auditing-terraform-infrastructure-for-security .claude/skills/auditing-terraform-infrastructure-for-security
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Auditing Terraform Infrastructure For Security 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 Auditing Terraform Infrastructure For Security 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 Auditing Terraform Infrastructure For Security 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.

Auditing Terraform Infrastructure for Security

When to Use

  • When integrating security scanning into CI/CD pipelines for Terraform deployments
  • When reviewing Terraform plans and modules for security best practices before applying
  • When building policy-as-code guardrails for cloud infrastructure provisioning
  • When auditing existing Terraform state files to identify deployed misconfigurations
  • When enforcing organizational security standards across multiple Terraform projects

Do not use for runtime security monitoring (use CSPM tools), for application security testing (use SAST/DAST tools), or for cloud configuration drift detection (use AWS Config or Azure Policy after deployment).

Prerequisites

  • Checkov installed (pip install checkov)
  • tfsec installed (brew install tfsec or binary from GitHub)
  • Terrascan installed (brew install terrascan)
  • Terraform v1.0+ for plan generation
  • OPA (Open Policy Agent) for custom policy enforcement
  • Git repository with Terraform code to audit

Workflow

Step 1: Scan Terraform Code with Checkov

Run Checkov for comprehensive IaC security scanning with built-in and custom policies.

bash
# Scan a Terraform directory
checkov -d ./terraform/ --framework terraform

# Scan with specific check categories
checkov -d ./terraform/ --check CKV_AWS_18,CKV_AWS_19,CKV_AWS_20,CKV_AWS_21

# Scan and output results in JSON
checkov -d ./terraform/ --output json > checkov-results.json

# Scan a Terraform plan file for more accurate analysis
terraform init && terraform plan -out=tfplan
terraform show -json tfplan > tfplan.json
checkov -f tfplan.json --framework terraform_plan

# Skip specific checks with justification
checkov -d ./terraform/ --skip-check CKV_AWS_145 \
  --bc-api-key $BRIDGECREW_API_KEY

# Scan Terraform modules
checkov -d ./modules/ --framework terraform --compact

# List all available checks
checkov --list --framework terraform | grep CKV_AWS

Step 2: Scan with tfsec for Terraform-Specific Issues

Use tfsec for Terraform-native security analysis with detailed remediation guidance.

bash
# Scan a Terraform directory
tfsec ./terraform/

# Scan with minimum severity threshold
tfsec ./terraform/ --minimum-severity HIGH

# Output in JSON for CI/CD processing
tfsec ./terraform/ --format json > tfsec-results.json

# Scan with custom checks
tfsec ./terraform/ --custom-check-dir ./custom-checks/

# Exclude specific rules
tfsec ./terraform/ --exclude-downloaded-modules \
  --exclude aws-s3-enable-bucket-logging

# Scan and fail on specific severity
tfsec ./terraform/ --minimum-severity CRITICAL --soft-fail

# Generate SARIF output for GitHub Security tab
tfsec ./terraform/ --format sarif > tfsec.sarif

Step 3: Run Terrascan for Multi-Framework Compliance

Execute Terrascan for compliance checking against CIS, NIST, and SOC 2 frameworks.

bash
# Scan Terraform against CIS AWS benchmark
terrascan scan -t aws -i terraform -d ./terraform/ \
  --policy-type aws --verbose

# Scan against specific compliance frameworks
terrascan scan -t aws -i terraform -d ./terraform/ \
  --policy-type aws \
  --categories "Compliance Validation"

# Output in JSON
terrascan scan -t aws -i terraform -d ./terraform/ \
  --output json > terrascan-results.json

# Scan a Terraform plan
terrascan scan -t aws -i terraform \
  --iac-file tfplan.json \
  --iac-type tfplan

# List available policies
terrascan scan --list-policies -t aws

Step 4: Create Custom OPA Policies for Organization Standards

Write Rego policies for organization-specific security requirements.

rego
# policy/aws_s3_encryption.rego
package terraform.aws.s3

deny[msg] {
    resource := input.resource.aws_s3_bucket[name]
    not resource.server_side_encryption_configuration
    msg := sprintf("S3 bucket '%s' must have server-side encryption enabled", [name])
}

# policy/aws_iam_no_wildcards.rego
package terraform.aws.iam

deny[msg] {
    resource := input.resource.aws_iam_policy[name]
    statement := resource.policy.Statement[_]
    statement.Action == "*"
    statement.Effect == "Allow"
    msg := sprintf("IAM policy '%s' must not use wildcard (*) actions", [name])
}

deny[msg] {
    resource := input.resource.aws_iam_policy[name]
    statement := resource.policy.Statement[_]
    statement.Resource == "*"
    statement.Effect == "Allow"
    contains(statement.Action[_], "*")
    msg := sprintf("IAM policy '%s' has overly permissive actions on wildcard resources", [name])
}

# policy/aws_no_public_ingress.rego
package terraform.aws.security_group

deny[msg] {
    resource := input.resource.aws_security_group_rule[name]
    resource.type == "ingress"
    resource.cidr_blocks[_] == "0.0.0.0/0"
    resource.from_port <= 22
    resource.to_port >= 22
    msg := sprintf("Security group rule '%s' allows SSH from 0.0.0.0/0", [name])
}
bash
# Evaluate Terraform plan against OPA policies
terraform show -json tfplan | opa eval \
  --data ./policy/ \
  --input /dev/stdin \
  "data.terraform.aws" \
  --format pretty

# Run Conftest for easier OPA policy testing
conftest test tfplan.json --policy ./policy/ --output json

Step 5: Integrate Security Scanning into CI/CD Pipeline

Add IaC security scanning as a mandatory CI/CD gate.

yaml
# GitHub Actions: Terraform security pipeline
name: Terraform Security Scan
on:
  pull_request:
    paths: ['terraform/**']

jobs:
  security-scan:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4

      - name: Setup Terraform
        uses: hashicorp/setup-terraform@v3

      - name: Terraform Init & Plan
        run: |
          cd terraform/
          terraform init
          terraform plan -out=tfplan
          terraform show -json tfplan > tfplan.json

      - name: Checkov Scan
        uses: bridgecrewio/checkov-action@master
        with:
          directory: terraform/
          framework: terraform
          output_format: sarif
          output_file_path: checkov.sarif
          soft_fail: false

      - name: tfsec Scan
        uses: aquasecurity/tfsec-action@v1.0.0
        with:
          working_directory: terraform/
          soft_fail: false

      - name: Upload SARIF
        uses: github/codeql-action/upload-sarif@v2
        with:
          sarif_file: checkov.sarif

      - name: OPA Policy Check
        run: |
          conftest test terraform/tfplan.json \
            --policy ./policy/ \
            --output json

Step 6: Scan Terraform State for Deployed Misconfigurations

Audit the current Terraform state to identify already-deployed security issues.

bash
# Export current state as JSON
terraform show -json > terraform-state.json

# Scan the state with Checkov
checkov -f terraform-state.json --framework terraform_plan

# Query state for specific security issues
terraform state list | while read resource; do
  terraform state show "$resource" 2>/dev/null | grep -i "public\|0.0.0.0\|encrypt.*false\|password"
done

# Find resources without required tags
terraform state list | grep aws_instance | while read resource; do
  tags=$(terraform state show "$resource" | grep -A20 "tags")
  if ! echo "$tags" | grep -q "Environment"; then
    echo "MISSING TAG: $resource lacks 'Environment' tag"
  fi
done

Key Concepts

TermDefinition
Infrastructure as CodePractice of managing cloud infrastructure through declarative configuration files (Terraform, CloudFormation) rather than manual console operations
Policy as CodeExpressing security and compliance policies as executable code (Rego, Python) that can be automatically evaluated against infrastructure definitions
Shift Left SecurityMoving security checks earlier in the development lifecycle by scanning IaC before deployment rather than auditing after provisioning
Terraform PlanPreview of changes Terraform will make, which can be exported as JSON for security scanning before applying changes
CheckovOpen-source static analysis tool for IaC supporting Terraform, CloudFormation, Kubernetes, and Docker with 1000+ built-in policies
OPA/RegoOpen Policy Agent and its policy language Rego for defining custom security rules that evaluate against structured data inputs

Tools & Systems

  • Checkov: Comprehensive IaC scanner with 1000+ policies for Terraform, CloudFormation, Kubernetes, ARM, and Dockerfile
  • tfsec: Terraform-specific static analysis tool with detailed remediation guidance and SARIF output
  • Terrascan: Multi-IaC scanner supporting compliance frameworks (CIS, NIST, SOC 2) with policy-as-code
  • OPA/Conftest: Custom policy engine for defining organization-specific security rules using Rego language
  • Bridgecrew: Commercial platform built on Checkov providing drift detection and supply chain security

Common Scenarios

Scenario: Adding Security Gates to an Existing Terraform CI/CD Pipeline

Context: A DevOps team deploys infrastructure via Terraform in GitHub Actions but has no security scanning. Recent audit findings show multiple S3 buckets without encryption and security groups allowing SSH from the internet.

Approach:

  1. Add Checkov as the first security gate in the GitHub Actions workflow
  2. Run checkov -d ./terraform/ to establish the current baseline of findings
  3. Triage existing findings: fix CRITICAL issues, create tickets for HIGH, suppress accepted risks
  4. Add tfsec as a secondary scanner for Terraform-specific checks
  5. Write custom OPA policies for organization standards (required tags, naming conventions)
  6. Configure the pipeline to block PRs with CRITICAL or HIGH findings
  7. Generate SARIF reports for GitHub Security tab integration

Pitfalls: Adding security scanning to an existing project will initially produce hundreds of findings. Implement gradually by starting with CRITICAL-only blocking, then expanding to HIGH. Use inline suppression comments (#checkov:skip=CKV_AWS_18:Public bucket for static website) for intentional exceptions with documented justification.

Output Format

Terraform Security Audit Report
==================================
Repository: acme-corp/infrastructure
Branch: main
Scan Date: 2026-02-23
Tools: Checkov 3.x, tfsec 1.x, OPA custom policies

SCAN RESULTS:
  Checkov checks passed:    187
  Checkov checks failed:     34
  tfsec checks passed:      156
  tfsec checks failed:       28
  OPA custom policies:       12 passed, 3 failed

CRITICAL FINDINGS:
[TF-001] S3 Bucket Without Encryption
  File: modules/storage/main.tf:24
  Resource: aws_s3_bucket.data_lake
  Check: CKV_AWS_19
  Fix: Add server_side_encryption_configuration block

[TF-002] Security Group Allows SSH from 0.0.0.0/0
  File: modules/network/security.tf:45
  Resource: aws_security_group_rule.ssh_access
  Check: CKV_AWS_24
  Fix: Restrict cidr_blocks to bastion subnet

[TF-003] IAM Policy with Wildcard Actions
  File: modules/iam/policies.tf:12
  Resource: aws_iam_policy.developer_policy
  Check: CKV_AWS_1
  Fix: Scope actions to specific services required

SUMMARY BY SEVERITY:
  Critical:  6 findings
  High:     14 findings
  Medium:   28 findings
  Low:      18 findings
  Info:     12 findings

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 Auditing Terraform Infrastructure For Security AI skill do?

Auditing Terraform infrastructure-as-code for security misconfigurations using Checkov, tfsec, Terrascan, and OPA/Rego policies to detect overly permissive IAM policies, public resource exposure, missing encryption, and insecure defaults before cloud deployment.

Why use Auditing Terraform Infrastructure For Security on TypingMind?

Because you install it once and use it with any model. Auditing Terraform Infrastructure For Security 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 Auditing Terraform Infrastructure For Security in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/auditing-terraform-infrastructure-for-security. 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 Auditing Terraform Infrastructure For Security?

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 Auditing Terraform Infrastructure For Security?

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

Is the Auditing Terraform Infrastructure For Security AI skill free?

Yes. It is published on GitHub by mukul975 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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