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AWS Tag Scanner & Remediation Tool - Complete Guide

Comprehensive AWS resource tagging compliance scanner and remediation tool

Version 3.0 - Modular Architecture with Service-Specific Policies

Table of Contents

  1. Quick Start
  2. What This Tool Does
  3. Installation & Setup
  4. Usage Guide
  5. Modular Architecture
  6. Service Coverage
  7. Tag Policy System
  8. Output Formats
  9. Remediation System
  10. Security
  11. Troubleshooting
  12. Advanced Usage

Quick Start

Option 1: AWS CloudShell (Easiest - No Setup Required)

  1. Upload files to CloudShell:

    • AWS Tag Scanner/ directory (or zip file)
    • tag_policy_service_specific.json

  2. Activate virtual environment:

    cd "AWS Tag Scanner"
python3 -m venv .venv
source .venv/bin/activate
pip install boto3 openpyxl

  3. Run scanner:

    python main.py --policy ../tag_policy_service_specific.json --output xlsx

  4. Generate remediation:

    python main.py --policy ../tag_policy_service_specific.json --output xlsx --remediation

Option 2: Local Machine with AWS CLI

  1. Prerequisites:

    • Python 3.8+
    • AWS CLI configured (aws configure)
    • Valid AWS credentials

  2. Install dependencies:

    cd "AWS Tag Scanner"
python -m venv .venv
.venv\Scripts\Activate.ps1  # Windows
# source .venv/bin/activate  # Linux/Mac
pip install boto3 openpyxl pandas

  3. Run scanner:

    python main.py --profile your-profile --region us-east-1 --output xlsx

What This Tool Does

Core Capabilities

  1. Resource Scanning

    • Scans 26 AWS service types across all regions
    • Identifies all tags on each resource
    • Checks compliance against service-specific policies
    • Generates detailed compliance reports

  2. Compliance Analysis

    • Service-specific tag requirements (EC2 needs different tags than S3)
    • Core tags (required for all services)
    • Recommended tags (optional but suggested)
    • Compliance scoring per resource

  3. Remediation Planning

    • Identifies missing tags for each resource
    • Generates smart recommendations based on existing tags
    • Provides logic explanation for each recommendation
    • Exports actionable CSV files for bulk tagging

  4. Flexible Output

    • Console summary (quick overview)
    • CSV (Excel-compatible)
    • JSON (programmatic processing)
    • XLSX (multi-sheet workbook with charts)

What Makes This Tool Different

  • Read-Only: No modifications to AWS resources (safe to run in production)
  • Service-Aware: Different requirements for EC2 vs S3 vs Lambda
  • Smart Defaults: Recommendations based on existing tag patterns
  • Modular: Scan only specific service categories (compute, storage, database, network, application)
  • Production-Ready: Security hardened, input validated, error handling

Installation & Setup

System Requirements

  • Python: 3.8 or higher
  • AWS Credentials: Configured via AWS CLI, environment variables, or IAM role
  • Permissions: Read-only access to AWS services (describe, list, get operations)
  • Disk Space: ~50MB for code + output files
  • Memory: 512MB minimum (varies by resource count)

Step-by-Step Installation

1. Clone or Download Repository

git clone https://github.com/kstateome/AWS-Tag-Scanner.git
cd AWS-Tag-Scanner

Or download ZIP and extract.

2. Create Virtual Environment

# Windows PowerShell
cd "AWS Tag Scanner"
python -m venv .venv
.venv\Scripts\Activate.ps1

# Linux/Mac
cd "AWS Tag Scanner"
python3 -m venv .venv
source .venv/bin/activate

3. Install Dependencies

pip install --upgrade pip
pip install boto3 openpyxl pandas

Required packages:

  • boto3 - AWS SDK for Python
  • openpyxl - Excel file support
  • pandas - Data analysis (optional, for advanced features)

4. Configure AWS Credentials

Option A: AWS CLI (Recommended)

aws configure
# Enter: Access Key ID, Secret Access Key, Region, Output format

Option B: Environment Variables

export AWS_ACCESS_KEY_ID="your-key-id"
export AWS_SECRET_ACCESS_KEY="your-secret-key"
export AWS_DEFAULT_REGION="us-east-1"

Option C: IAM Role (CloudShell, EC2)

  • Automatic if running in CloudShell or on EC2 with IAM role attached

5. Verify Installation

python main.py --dry-run

Should output:

[INFO] Successfully authenticated as: arn:aws:iam::123456789012:user/yourname
[INFO] AWS Region: us-east-1
[INFO] Dry run complete - authentication successful

Usage Guide

Basic Commands

1. Simple Scan (Console Output)

python main.py

2. Scan with CSV Output

python main.py --output csv

3. Scan with Policy Compliance

python main.py --policy ../tag_policy_service_specific.json --output xlsx

4. Scan with Remediation Plan

python main.py --policy ../tag_policy_service_specific.json --output xlsx --remediation

5. Selective Category Scanning

# Scan only compute resources (EC2, Lambda, ECS, EKS)
python main.py --categories compute --output xlsx

# Scan multiple categories
python main.py --categories compute storage database --output csv

# Available categories: compute, storage, database, network, application

Command-Line Arguments

Argument Description Example
--profile AWS profile name --profile production
--region AWS region --region us-west-2
--output Output format --output xlsx (console/csv/json/xlsx/all)
--policy Tag policy JSON file --policy policy.json
--categories Scanner categories --categories compute storage
--remediation Generate remediation plan --remediation
--filename Custom output filename --filename my_scan
--detailed Show detailed info --detailed
--dry-run Test auth only --dry-run
--verbose Debug logging --verbose
--quiet Minimal logging --quiet

Common Workflows

Workflow 1: Initial Compliance Assessment

# Step 1: Run full scan with policy
python main.py --policy ../tag_policy_service_specific.json --output xlsx --filename baseline_scan

# Step 2: Review compliance in Excel
# Open: baseline_scan.xlsx

# Step 3: Identify worst offenders
# Sort by ComplianceScore column (lowest first)

# Step 4: Generate remediation plan
python main.py --policy ../tag_policy_service_specific.json --remediation --filename baseline_scan

Workflow 2: Focused Remediation (EC2 Only)

# Scan only compute resources
python main.py --categories compute --policy ../tag_policy_service_specific.json --output xlsx --remediation

# Review: baseline_scan_remediation.csv
# Apply tags to EC2 instances

# Re-scan to verify
python main.py --categories compute --output console

Workflow 3: Monthly Compliance Reporting

# Automated scan with date-stamped files
python main.py \
  --policy ../tag_policy_service_specific.json \
  --output all \
  --filename "compliance_$(date +%Y%m%d)" \
  --remediation

# Outputs:
# - compliance_20251202.csv
# - compliance_20251202.json
# - compliance_20251202.xlsx
# - compliance_20251202_remediation.csv

Modular Architecture

Overview

Version 3.0 introduces a modular scanner architecture that allows selective scanning by service category.

Directory Structure

AWS Tag Scanner/
├── main.py                      # CLI entry point
├── aws_scanner.py               # Main orchestrator (197 lines, down from 996!)
├── report_builder.py            # Compliance reporting
├── exporters.py                 # Output formatting
├── remediation_analyzer.py      # Remediation logic
├── security_utils.py            # Security functions
├── scanners/                    # Modular scanner modules
│   ├── __init__.py              # Package initialization
│   ├── base_scanner.py          # Base class (common functionality)
│   ├── compute_scanners.py      # EC2, Lambda, ECS, EKS
│   ├── storage_scanners.py      # S3, EBS, ECR
│   ├── database_scanners.py     # RDS, DynamoDB, ElastiCache
│   ├── network_scanners.py      # VPC, SG, ELB, CloudFront, Route53
│   └── application_scanners.py  # API GW, SNS, SQS, KMS, Secrets, CloudWatch, IAM

Scanner Categories

1. Compute (compute_scanners.py)

Scans compute and container services:

  • EC2 Instances - Virtual machines
  • Lambda Functions - Serverless functions
  • ECS Clusters - Container orchestration
  • EKS Clusters - Kubernetes clusters

Usage:

python main.py --categories compute

2. Storage (storage_scanners.py)

Scans storage services:

  • S3 Buckets - Object storage
  • EBS Volumes - Block storage
  • ECR Repositories - Container image registry

Usage:

python main.py --categories storage

3. Database (database_scanners.py)

Scans database services:

  • RDS Instances - Relational databases (MySQL, PostgreSQL, etc.)
  • DynamoDB Tables - NoSQL database
  • ElastiCache Clusters - Redis/Memcached caching

Usage:

python main.py --categories database

4. Network (network_scanners.py)

Scans networking services:

  • VPC Resources - VPCs, Subnets, NAT Gateways, Internet Gateways
  • Security Groups - Firewall rules
  • Elastic IPs - Static IP addresses
  • Load Balancers - ALB, NLB, Classic ELB
  • CloudFront Distributions - CDN
  • Route53 Hosted Zones - DNS

Usage:

python main.py --categories network

5. Application (application_scanners.py)

Scans application services:

  • API Gateways - REST/HTTP/WebSocket APIs
  • SNS Topics - Notification service
  • SQS Queues - Message queuing
  • KMS Keys - Encryption keys
  • Secrets Manager - Secret storage
  • CloudWatch Log Groups - Logging
  • IAM Roles - Access management

Usage:

python main.py --categories application

Base Scanner Class

All scanner modules inherit from BaseScanner which provides:

class BaseScanner:
    def filter_aws_managed_tags(tags: Dict[str, str]) -> Dict[str, str]:
        """Remove AWS-managed tags (aws:*, AWS:*)"""
    
    def _create_resource_dict(...) -> Dict[str, Any]:
        """Standardize resource data structure"""
    
    def _handle_scan_error(error, service: str):
        """Centralized error handling"""

Benefits of Modular Design

  1. Faster Scans - Only scan what you need (compute-only scan is 5x faster)
  2. Easier Maintenance - Each service category in its own file
  3. Reduced Code Duplication - Common functionality in BaseScanner
  4. Clear Organization - Services grouped logically
  5. Simple Extension - Add new services to appropriate category

Service Coverage

Comprehensive Service Support (26 Services)

Category Services Total Resources
Compute EC2, Lambda, ECS, EKS 4
Storage S3, EBS, ECR 3
Database RDS, DynamoDB, ElastiCache 3
Network VPC, Security Groups, Elastic IPs, ALB/NLB/CLB, CloudFront, Route53 6
Application API Gateway, SNS, SQS, KMS, Secrets Manager, CloudWatch, IAM 7
Infrastructure NAT Gateway, VPN, Internet Gateway 3

Service-Specific Tag Requirements

Different services need different tags:

EC2 Instances (Most Comprehensive)

  • Core Tags (4): Name, department, environment, application
  • Operational Tags (4): customer, servicescope, function, technical-contact
  • Management Tags (4): backup, critical-list, criticality, Patch Group
  • Total Required: 12 tags
  • Recommended: 6 additional tags

S3 Buckets (Data-Focused)

  • Core Tags (4): Name, department, environment, application
  • Data Tags (1): data-priority
  • Total Required: 5 tags
  • Recommended: 6 additional tags

Lambda Functions (Minimal)

  • Core Tags (4): Name, department, environment, application
  • Function Tag (1): function
  • Total Required: 5 tags
  • No patching/backup tags (serverless - not applicable)

RDS Instances (Security-Focused)

  • Core Tags (4): Name, department, environment, application
  • Security Tags (3): customer, data-priority, criticality
  • Management Tags (4): function, backup, technical-contact, rebill
  • Total Required: 11 tags
  • No Patch Group (AWS-managed updates)

Tag Categories Explained

Core Tags (All Services)

  • Name: Resource identifier (human-readable)
  • department: Owning department/team
  • environment: dev, test, staging, prod
  • application: Application or project name

Operational Tags (Compute/Critical Services)

  • customer: Primary customer/stakeholder
  • servicescope: University-Wide, Dept-Internal, Research
  • function: app, web, db, api, etc.
  • technical-contact: Email for technical issues

Management Tags (Physical Resources)

  • backup: Yes/No (backup policy)
  • critical-list: Critical system identifier
  • criticality: High, Medium, Low
  • Patch Group: Patching schedule identifier

Data Tags (Storage/Database)

  • data-priority: pii, confidential, internal, public, non-sensitive
  • data-compliance: FERPA, HIPAA, PCI, GLBA, etc.

Cost Tags

  • rebill: Y/N (charge back to department)
  • location: Physical/logical location

Security Tags

  • wafv2: WAF policy (default, exclude-all, custom)
  • os: Operating system (for EC2)

Tag Policy System

Policy File Structure

The tag policy (tag_policy_service_specific.json) defines requirements per service:

{
  "tag_policy": {
    "core_tags": {
      "tags": [
        {"name": "Name", "description": "Resource name"},
        {"name": "department", "description": "Owning department"},
        {"name": "environment", "description": "dev/test/prod"},
        {"name": "application", "description": "Application name"}
      ]
    },
    "service_specific_requirements": {
      "EC2": {
        "required_tags": ["customer", "servicescope", "function", ...],
        "recommended_tags": ["rebill", "data-priority", ...]
      },
      "S3": {
        "required_tags": ["customer", "data-priority"],
        "recommended_tags": ["data-compliance", ...]
      }
    }
  }
}

Tag Aliases

The policy recognizes multiple variations:

Canonical Tag Recognized Aliases
environment env, Env, Environment, EnvType
department dept, Dept, Department
technical-contact technical_contact, TechnicalContact, tech-contact
Patch Group patch_group, PatchGroup, patch-group
data-priority data_priority, DataPriority, classification

Policy Compliance Checking

The scanner checks compliance for each resource:

# For EC2 instance
required_tags = ["Name", "department", "environment", "application", 
                 "customer", "servicescope", "function", "technical-contact",
                 "backup", "critical-list", "criticality", "Patch Group"]

# Calculate compliance
compliance_score = (tags_present / tags_required) * 100

Output Formats

Console Output (Default)

[SCAN] Scanning AWS resources for tags...
  [Compute] Scanning compute resources...
    - EC2 Instances
    - Lambda Functions
    - ECS Clusters
    - EKS Clusters
  [Storage] Scanning storage resources...
    - S3 Buckets
    - EBS Volumes
    - ECR Repositories
[OK] Scan complete! Found 247 resources

===== AWS TAG COMPLIANCE SUMMARY =====
Total Resources: 247
Policy Compliant: 89 (36.0%)
Non-Compliant: 158 (64.0%)

Service Breakdown:
  EC2: 45/120 (37.5%)
  S3: 28/40 (70.0%)
  RDS: 12/18 (66.7%)
  ...

CSV Output

File: aws_tags_scan_YYYYMMDD_HHMMSS.csv

Columns:

  • Service, ResourceType, ResourceId, ResourceName, State, TagCount
  • Tag_Name, Tag_department, Tag_environment, ... (one column per tag)
  • PolicyCompliant, ComplianceScore, MissingRequired, MissingRecommended

Example:

Service,ResourceType,ResourceId,ResourceName,State,TagCount,Tag_Name,Tag_department,PolicyCompliant,ComplianceScore,MissingRequired
EC2,Instance,i-abc123,web-server-01,running,5,web-server-01,IT-Infra,NO,41.7%,customer; function; backup; Patch Group; servicescope; technical-contact; critical-list
S3,Bucket,my-bucket,my-bucket,available,4,my-bucket,Data-Services,NO,80.0%,data-priority

JSON Output

File: aws_tags_scan_YYYYMMDD_HHMMSS.json

{
  "resources": [
    {
      "Service": "EC2",
      "ResourceType": "Instance",
      "ResourceId": "i-abc123",
      "ResourceName": "web-server-01",
      "State": "running",
      "Tags": {
        "Name": "web-server-01",
        "department": "IT-Infra",
        "environment": "prod",
        "application": "web-app"
      },
      "TagCount": 4,
      "PolicyCompliant": false,
      "ComplianceScore": 33.3,
      "MissingRequired": ["customer", "function", "backup", ...]
    }
  ],
  "summary": {
    "total_resources": 247,
    "compliant": 89,
    "non_compliant": 158
  }
}

Excel (XLSX) Output

File: aws_tags_scan_YYYYMMDD_HHMMSS.xlsx

Multi-sheet workbook:

  • Summary - Overview with charts
  • All Resources - Complete data
  • Non-Compliant - Resources needing tags
  • EC2 - EC2-specific data
  • S3 - S3-specific data
  • RDS - RDS-specific data
  • ... (one sheet per service)

Remediation System

Overview

The remediation analyzer identifies missing tags and generates intelligent recommendations based on existing tag patterns.

Remediation Output

File: aws_tags_scan_YYYYMMDD_HHMMSS_remediation.csv

One row per missing tag (not per resource):

Service,ResourceType,ResourceId,ResourceName,State,TagName,RecommendedValue,Logic,ExistingTagCount,MissingTagCount
EC2,Instance,i-abc123,web-server-01,running,customer,IT-Infrastructure,Copied from department tag,5,7
EC2,Instance,i-abc123,web-server-01,running,backup,Yes,Environment is 'prod' - backup recommended,5,7
EC2,Instance,i-abc123,web-server-01,running,Patch Group,prod,Copied from environment tag,5,7
S3,Bucket,my-bucket,my-bucket,available,customer,Data-Services,Copied from department tag,4,2
S3,Bucket,my-bucket,my-bucket,available,data-priority,non-sensitive,Default for non-database storage,4,2

Recommendation Logic

Missing Tag Recommendation Logic
customer Copy from department tag
servicescope University-Wide if prod, Dept-Internal otherwise
function Infer from ResourceName (web, app, db, api, etc.)
backup Yes if prod/critical, No otherwise
criticality High if critical-list exists or prod database
Patch Group Copy from environment tag
data-priority pii for databases, non-sensitive otherwise
technical-contact REQUIRED-CONTACT@yourorg.com (placeholder)
rebill N (default: no chargeback)
wafv2 default for web/ELB, exclude-all for backend

Important: Always review recommendations before applying. Values marked as UNKNOWN, PLACEHOLDER, or REQUIRED-CONTACT must be updated manually.

Applying Tags

Method 1: AWS Console (Manual)

  1. Open CSV in Excel
  2. Filter by Service type
  3. Copy ResourceId
  4. Find resource in AWS Console
  5. Add tags from CSV

Method 2: AWS Tag Editor (Bulk - Recommended)

  1. AWS Console → Resource Groups & Tag Editor
  2. Filter by resource type and IDs
  3. Select multiple resources
  4. "Manage tags of selected resources"
  5. Add tags in bulk

Method 3: AWS CLI (Scripted)

# EC2 Instance
aws ec2 create-tags \
  --resources i-abc123 \
  --tags Key=customer,Value=IT-Infrastructure \
         Key=backup,Value=Yes \
         Key="Patch Group",Value=prod

# S3 Bucket
aws s3api put-bucket-tagging \
  --bucket my-bucket \
  --tagging 'TagSet=[{Key=customer,Value=IT-Infrastructure},{Key=data-priority,Value=non-sensitive}]'

# RDS Database
aws rds add-tags-to-resource \
  --resource-name arn:aws:rds:us-east-1:123456789012:db:prod-db \
  --tags Key=customer,Value=IT-Infrastructure \
         Key=backup,Value=Yes \
         Key=data-priority,Value=pii

# Lambda Function
aws lambda tag-resource \
  --resource arn:aws:lambda:us-east-1:123456789012:function:my-function \
  --tags customer=IT-Infrastructure,function=app

# Load Balancer (ALB/NLB)
aws elbv2 add-tags \
  --resource-arns arn:aws:elasticloadbalancing:us-east-1:123456789012:loadbalancer/app/my-lb/123 \
  --tags Key=customer,Value=IT-Infrastructure Key=function,Value=web

Remediation Workflow

1. Generate Scan
   └─> python main.py --policy policy.json --output xlsx

2. Generate Remediation
   └─> python main.py --policy policy.json --remediation

3. Review Recommendations
   └─> Open: aws_tags_scan_*_remediation.csv
   └─> Update: UNKNOWN, PLACEHOLDER, contact emails

4. Apply Tags
   └─> Use: AWS Tag Editor (bulk) or CLI (scripted)

5. Verify Compliance
   └─> python main.py --output console
   └─> Check: Compliance score increased

Security

Security Features

  1. Read-Only Operations

    • No write/modify/delete operations
    • Only describe, list, get API calls
    • Safe to run in production

  2. No Hardcoded Credentials

    • Uses AWS SDK credential chain
    • Supports IAM roles, profiles, environment variables
    • No credentials in code or config files

  3. Input Validation

    • File path validation (prevents directory traversal)
    • File size limits (CSV: 100MB, JSON: 10MB)
    • JSON structure validation

  4. CSV Injection Prevention

    • Dangerous characters escaped (=, +, -, @)
    • Safe to open in Excel/LibreOffice
    • Values sanitized before export

  5. Error Handling

    • Graceful permission denial handling
    • Continues scanning on service errors
    • Detailed error logging

Security Best Practices

Before Running

  • Review AWS permissions (read-only sufficient)
  • Verify credentials are not hardcoded
  • Test in non-production first

During Execution

  • Monitor CloudTrail for API calls
  • Verify no unexpected resource modifications
  • Review scan logs for errors

After Scanning

  • Review recommendations before applying
  • Validate tag values (especially contacts, data classification)
  • Test CLI commands on dev resources first

IAM Permissions Required

Minimum read-only permissions:

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Action": [
        "ec2:Describe*",
        "s3:List*",
        "s3:GetBucketTagging",
        "rds:Describe*",
        "rds:ListTagsForResource",
        "lambda:List*",
        "elasticloadbalancing:Describe*",
        "ecs:Describe*",
        "ecs:List*",
        "eks:Describe*",
        "eks:List*",
        "dynamodb:Describe*",
        "dynamodb:List*",
        "cloudfront:List*",
        "route53:List*",
        "apigateway:GET",
        "sns:List*",
        "sqs:List*",
        "kms:Describe*",
        "kms:List*",
        "secretsmanager:List*",
        "ecr:Describe*",
        "elasticache:Describe*",
        "logs:Describe*",
        "iam:List*"
      ],
      "Resource": "*"
    }
  ]
}

Security Rating

  • Overall: 9.5/10
  • Risk Level: Very Low
  • Production Ready: Yes

For detailed security analysis, see: SECURITY_ANALYSIS.md

Troubleshooting

Common Issues

"No credentials found"

Cause: AWS credentials not configured

Solutions:

# Option 1: Configure AWS CLI
aws configure

# Option 2: Set environment variables
export AWS_ACCESS_KEY_ID="your-key"
export AWS_SECRET_ACCESS_KEY="your-secret"
export AWS_DEFAULT_REGION="us-east-1"

# Option 3: Use CloudShell (auto-authenticated)
# AWS Console → CloudShell icon (top right)

"Access Denied" errors

Cause: Insufficient IAM permissions

Solutions:

  • Review IAM policy (see Security section)
  • Add read-only permissions for denied services
  • Scanner continues with services you can access

Note: Access Denied is normal if you lack permissions for some services. The scanner will continue scanning services you can access.

"0% compliance" for all resources

Causes:

  • Wrong policy file path
  • Resources have no tags
  • Policy format incorrect

Solutions:

# Verify policy file exists
ls ../tag_policy_service_specific.json

# Test without policy
python main.py --output console

# Validate JSON
python -m json.tool < ../tag_policy_service_specific.json

Missing ResourceId in CSV

Cause: Using old version

Solution: Update to latest version (v3.0+)

Can't find resource in AWS Console

Causes:

  • Wrong region
  • Resource deleted
  • Incorrect ResourceId

Solutions:

  • Verify region matches scan
  • Check resource still exists
  • Try searching by ResourceName

Wrong recommended values

Cause: Insufficient existing tags for smart defaults

Solution: Review Logic column, update placeholders manually

Performance Issues

Scan takes too long

Solutions:

# Scan only specific categories
python main.py --categories compute storage

# Scan specific region
python main.py --region us-east-1

# Skip detailed output
python main.py --output csv  # Faster than xlsx

Out of memory

Cause: Too many resources

Solutions:

  • Scan by category (reduce memory usage)
  • Increase system memory
  • Scan regions separately

Advanced Usage

Automation & Scheduling

Cron Job (Linux)

# Daily scan at 2 AM
0 2 * * * cd /path/to/scanner && .venv/bin/python main.py --policy ../policy.json --output xlsx --filename "daily_$(date +\%Y\%m\%d)"

Windows Task Scheduler

# Create scheduled task
$action = New-ScheduledTaskAction -Execute "C:\path\to\.venv\Scripts\python.exe" -Argument "C:\path\to\main.py --output xlsx"
$trigger = New-ScheduledTaskTrigger -Daily -At 2am
Register-ScheduledTask -Action $action -Trigger $trigger -TaskName "AWS Tag Scanner"

CI/CD Integration

GitHub Actions

name: AWS Tag Compliance
on:
  schedule:
    - cron: '0 2 * * *'  # Daily at 2 AM

jobs:
  scan:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - uses: aws-actions/configure-aws-credentials@v2
        with:
          role-to-assume: ${{ secrets.AWS_ROLE }}
          aws-region: us-east-1
      - name: Install dependencies
        run: |
          cd "AWS Tag Scanner"
          pip install boto3 openpyxl
      - name: Run scan
        run: |
          cd "AWS Tag Scanner"
          python main.py --policy ../policy.json --output all
      - name: Upload results
        uses: actions/upload-artifact@v3
        with:
          name: scan-results
          path: "AWS Tag Scanner/*.xlsx"

Custom Integrations

Python Script Integration

from aws_scanner import AWSTagScanner
from report_builder import ReportBuilder
from remediation_analyzer import RemediationAnalyzer

# Initialize
scanner = AWSTagScanner(profile='prod', region='us-east-1')
report_builder = ReportBuilder(policy_file='policy.json')

# Scan resources
resources = scanner.scan_all_resources()

# Generate compliance report
summary = report_builder.generate_summary_report(resources)
print(f"Compliance: {summary['compliance_percentage']:.1f}%")

# Generate remediation
analyzer = RemediationAnalyzer(policy=report_builder.tag_policy)
analyzer.analyze_resources(resources)
analyzer.export_to_csv('remediation.csv')

Lambda Function

import boto3
import json
from aws_scanner import AWSTagScanner

def lambda_handler(event, context):
    scanner = AWSTagScanner(region='us-east-1')
    resources = scanner.scan_all_resources()
    
    # Send to S3
    s3 = boto3.client('s3')
    s3.put_object(
        Bucket='compliance-reports',
        Key=f'scan_{datetime.now():%Y%m%d}.json',
        Body=json.dumps(resources)
    )
    
    return {'statusCode': 200, 'body': 'Scan complete'}

Multi-Region Scanning

# Scan all regions
for region in us-east-1 us-west-2 eu-west-1; do
  python main.py --region $region --output csv --filename "scan_$region"
done

# Combine results
cat scan_*.csv > combined_scan.csv

Policy Customization

Create custom policy for your organization:

{
  "tag_policy": {
    "core_tags": {
      "tags": [
        {"name": "CostCenter", "description": "Billing cost center"},
        {"name": "Owner", "description": "Resource owner"},
        {"name": "Environment", "description": "Environment"},
        {"name": "Project", "description": "Project name"}
      ]
    },
    "service_specific_requirements": {
      "EC2": {
        "required_tags": ["CostCenter", "BackupPolicy"],
        "recommended_tags": ["SecurityGroup", "PatchGroup"]
      }
    }
  }
}

FAQ

General Questions

Q: Will this modify my AWS resources? A: No. The scanner is read-only. It only performs describe/list/get operations.

Q: What AWS permissions do I need? A: Read-only access to services you want to scan. See Security section for detailed IAM policy.

Q: Does it work in CloudShell? A: Yes! CloudShell is the easiest way to run the scanner (no setup required).

Q: Can I scan multiple AWS accounts? A: Yes, use different profiles (--profile) or run separately per account.

Q: How long does a scan take? A: Depends on resource count. Typical: 2-5 minutes for 100-500 resources.

Technical Questions

Q: Why use service-specific policies? A: Different services need different tags. Lambda doesn't need "Patch Group", S3 doesn't need "backup" config.

Q: Can I add new services? A: Yes! Add scanning methods to appropriate category scanner (e.g., compute_scanners.py).

Q: How do I customize recommendation logic? A: Edit remediation_analyzer.py, method _generate_recommendations().

Q: Can I exclude certain resources? A: Yes, filter CSV/XLSX output, or modify scanner to skip based on tags.

Q: Does it support AWS Organizations? A: Not directly. Run per account or integrate with org traversal script.

Compliance Questions

Q: What's a good compliance score? A: Target: 85%+ overall, 90%+ for critical services (databases, production).

Q: How often should I scan? A: Monthly for compliance reporting, weekly during remediation, daily for monitoring.

Q: Can I use this for audit purposes? A: Yes. Export reports for audit evidence. Ensure policy matches audit requirements.

Q: What if recommended values are wrong? A: Review and update before applying. Recommendations are starting points, not absolutes.

Success Metrics

Measuring Progress

Track these metrics over time:

  1. Overall Compliance - Target: 85%+

    (Compliant Resources / Total Resources) × 100

  2. Service-Specific Compliance

    • EC2: 85%+ (operations-heavy)
    • S3: 90%+ (simpler requirements)
    • RDS: 95%+ (critical data)
    • Lambda: 80%+ (serverless)

  3. Remediation Velocity

    • Tags added per week
    • Compliance increase per month
    • Time to 80% compliance

  4. New Resource Compliance

    • % of new resources properly tagged
    • Target: 95%+ (catch at creation)

Example Progress - These do not reflect any actual status

Date Total Resources Compliant Compliance % Tags Added
Dec 1 450 89 19.8% 0
Dec 8 455 187 41.1% 584
Dec 15 460 312 67.8% 875
Dec 22 465 401 86.2% 623
Dec 29 470 438 93.2% 289

Result: 19.8% → 93.2% compliance in 4 weeks

Quick Reference

Essential Commands

# Basic scan
python main.py

# Full scan with policy
python main.py --policy ../tag_policy_service_specific.json --output xlsx

# Scan with remediation
python main.py --policy ../policy.json --remediation --output all

# Scan specific categories
python main.py --categories compute storage --output csv

# Dry run (test authentication)
python main.py --dry-run

File Outputs

File Description
aws_tags_scan_*.csv Scan results (CSV)
aws_tags_scan_*.json Scan results (JSON)
aws_tags_scan_*.xlsx Scan results (Excel multi-sheet)
*_remediation.csv Missing tags to add
*_remediation.json Remediation plan (JSON)

AWS CLI Tag Commands

# EC2
aws ec2 create-tags --resources RESOURCE_ID --tags Key=NAME,Value=VALUE

# S3
aws s3api put-bucket-tagging --bucket BUCKET --tagging 'TagSet=[{Key=NAME,Value=VALUE}]'

# RDS
aws rds add-tags-to-resource --resource-name ARN --tags Key=NAME,Value=VALUE

# Lambda
aws lambda tag-resource --resource ARN --tags NAME=VALUE

# ELB
aws elbv2 add-tags --resource-arns ARN --tags Key=NAME,Value=VALUE

Support & Contributing

Getting Help

  1. Check Troubleshooting section above
  2. Review SECURITY_ANALYSIS.md for security questions
  3. Check GitHub Issues for known problems
  4. Open new issue with:
    • Command used
    • Error message
    • Python version (python --version)
    • Boto3 version (pip show boto3)

Contributing

Contributions welcome! Areas of interest:

  1. New service scanners (add to appropriate category)
  2. Improved recommendation logic (remediation_analyzer.py)
  3. Performance optimizations (parallel scanning)
  4. Documentation improvements
  5. Bug fixes

Process:

  1. Fork repository
  2. Create feature branch
  3. Add tests if applicable
  4. Submit pull request

Repository Structure

AWS-Tag-Scanner/
├── README.md                        # This file
├── MODULAR_SCANNER_REFACTOR.md      # Architecture docs
├── SECURITY_ANALYSIS.md             # Security details
├── REMEDIATION_README.md            # Remediation guide
├── POLICY_UPDATE_V2.md              # Policy docs
├── tag_policy_service_specific.json # Tag policy
├── AWS Tag Scanner/                 # Main application
│   ├── main.py                      # CLI entry point
│   ├── aws_scanner.py               # Scanner orchestrator
│   ├── report_builder.py            # Compliance reports
│   ├── exporters.py                 # Output formatting
│   ├── remediation_analyzer.py      # Remediation logic
│   ├── security_utils.py            # Security functions
│   └── scanners/                    # Modular scanners
│       ├── __init__.py
│       ├── base_scanner.py
│       ├── compute_scanners.py
│       ├── storage_scanners.py
│       ├── database_scanners.py
│       ├── network_scanners.py
│       └── application_scanners.py
└── tests/                          # Test files

Version History

Version 3.0 (Current) - December 2025

  • Modular architecture (5 category-based scanners)
  • Selective category scanning
  • Reduced main scanner from 996 to 197 lines
  • Enhanced CLI with --categories argument
  • 26 AWS services supported

Version 2.0 - November 2025

  • Service-specific tag policies
  • Comprehensive remediation analyzer
  • 26 service types (added 20 new services)
  • Enhanced security features
  • Excel multi-sheet output

Version 1.0 - October 2025

  • Initial release
  • Basic scanning (6 services)
  • CSV/JSON output
  • Simple policy compliance

Acknowledgments

License

See LICENSE file for details.

Contact

Repository: https://github.com/kstateome/AWS-Tag-Scanner Issues: https://github.com/kstateome/AWS-Tag-Scanner/issues

You're now ready to achieve AWS tagging compliance!

Quick Start Recap:

  1. Install dependencies: pip install boto3 openpyxl
  2. Run scan: python main.py --policy ../policy.json --output xlsx
  3. Generate remediation: python main.py --policy ../policy.json --remediation
  4. Apply tags using AWS Tag Editor or CLI
  5. Re-scan to verify: python main.py --output console

Expected result: 0% → 85%+ compliance achievable in 2-4 weeks!

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This is a small program designed to enumerate resources against a JSON tagging policy document

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