Skip to main content
Glama
annaescalada

AWS Security Group Auditor

by annaescalada

AWS Security Group Auditor

Audits AWS Security Groups for dangerous configurations. Detects publicly exposed critical ports (SSH, RDP, databases) and provides remediation commands.

Features

  • Automated detection of dangerous rules (0.0.0.0/0 on critical ports)

  • Optional AI analysis via Claude

  • Markdown reports with remediation commands

  • MCP server for Claude Desktop integration

  • Risk prioritization (Critical, High, Medium)

Related MCP server: AWS MCP Audit

Detection Rules

  • Port 22 (SSH) open to Internet

  • Port 3389 (RDP) open to Internet

  • Database ports (3306, 5432, 27017) exposed

  • Protocol -1 (all traffic) open to 0.0.0.0/0

  • Administrative and internal services publicly exposed

Requirements

  • Python 3.10+

  • AWS credentials (via AWS CLI or environment variables)

  • Anthropic API key (optional, for AI analysis only)

Installation

# Clone or download repository
cd sg-auditor

# Create virtual environment with Python 3.10+
python3.11 -m venv venv
source venv/bin/activate

# Install dependencies
pip install -r requirements.txt

AWS Configuration

Option 1: AWS CLI (recommended)

aws configure

Option 2: Environment variables

export AWS_ACCESS_KEY_ID="your_key"
export AWS_SECRET_ACCESS_KEY="your_secret"
export AWS_DEFAULT_REGION="us-east-1"

Optional: Claude AI Analysis

Create .env file for AI-powered analysis:

ANTHROPIC_API_KEY=sk-ant-xxx

Get your API key at console.anthropic.com

Usage

CLI

# Audit default region
python audit.py

# Audit specific region
python audit.py --region us-west-2

# Skip AI analysis
python audit.py --no-ai

# Custom output directory
python audit.py --output-dir /path/to/reports

Exit codes: 0 (clean), 1 (high severity), 2 (critical severity)

MCP Server (Claude Desktop Integration)

Configure in ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "security-group-auditor": {
      "command": "/path/to/sg-auditor/venv/bin/python",
      "args": ["/path/to/sg-auditor/src/mcp_server.py"]
    }
  }
}

Restart Claude Desktop. Available tools:

  • scan_security_groups - Scan all Security Groups in a region

  • analyze_specific_group - Analyze specific Security Group by ID

  • get_risk_summary - Get risk information

Python Library

from src.audit_core import run_audit

result = run_audit(region='us-east-1')
print(f"Findings: {result['summary']['total_findings']}")

Architecture

sg-auditor/
├── audit.py                 # CLI entry point
├── requirements.txt         # Python dependencies
├── src/
│   ├── audit_core.py       # Core audit logic (shared)
│   ├── sg_collector.py     # AWS Security Group collector (boto3)
│   ├── rule_analyzer.py    # Dangerous rule detector
│   ├── ai_agent.py         # Optional AI analysis (CLI only)
│   ├── mcp_server.py       # MCP server (Claude Desktop)
│   └── report_generator.py # Markdown report generator
└── reports/                # Generated audit reports

Design:

  • audit_core.py contains shared logic used by both CLI and MCP server

  • ai_agent.py is only used by CLI tool (MCP returns raw findings for Claude to analyze)

  • mcp_server.py exposes tools via Model Context Protocol for AI agents

AWS Permissions

Required IAM permissions (read-only):

{
  "Version": "2012-10-17",
  "Statement": [{
    "Effect": "Allow",
    "Action": [
      "ec2:DescribeSecurityGroups",
      "ec2:DescribeRegions"
    ],
    "Resource": "*"
  }]
}

The auditor never modifies AWS resources.

Advanced Usage

CI/CD Integration

python audit.py --region us-east-1 --no-ai
if [ $? -eq 2 ]; then
    echo "CRITICAL findings - blocking deployment"
    exit 1
fi

Multi-Region Audit

for region in us-east-1 us-west-2 eu-west-1; do
    python audit.py --region $region
done

AWS Organizations

Use assumed roles in src/sg_collector.py:

sts = boto3.client('sts')
assumed_role = sts.assume_role(
    RoleArn='arn:aws:iam::ACCOUNT_ID:role/SecurityAuditor',
    RoleSessionName='SecurityAudit'
)
credentials = assumed_role['Credentials']
self.ec2_client = boto3.client(
    'ec2',
    aws_access_key_id=credentials['AccessKeyId'],
    aws_secret_access_key=credentials['SecretAccessKey'],
    aws_session_token=credentials['SessionToken']
)

Customization

Custom Ports

Edit src/rule_analyzer.py to add custom ports:

CRITICAL_PORTS = {
    22: "SSH",
    3389: "RDP",
    8080: "Custom Application",
}

Cost

Claude AI analysis (optional):

  • 5,000 tokens per audit ($0.10 USD)

  • Use --no-ai flag to skip AI analysis

Resources

License

MIT

F
license - not found
-
quality - not tested
D
maintenance

Maintenance

Maintainers
Response time
Release cycle
Releases (12mo)
Commit activity

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/annaescalada/sg-auditor'

If you have feedback or need assistance with the MCP directory API, please join our Discord server