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Usage Guide

This comprehensive guide covers all aspects of using the Linux Security Audit Project, from basic commands to advanced workflows.

Table of Contents

Command-Line Syntax

Basic Syntax

python3 linux_security_audit.py [OPTIONS]

All Available Options

Option Short Description Default
--modules -m Comma-separated list of modules to run All
--output-format -f Output format (HTML/CSV/JSON/XML/Console) HTML
--output-path -o Path for output file Auto-generated
--list-modules List all available modules and exit
--parallel Execute modules in parallel
--workers Number of parallel workers Auto
--profile Display performance statistics
--log-level Set logging level (DEBUG/INFO/WARNING/ERROR/CRITICAL) INFO
--log-file Custom log file path Auto (logs/)
--json-log Enable JSON-structured log output
--verbose -v Enable verbose console output
--quiet -q Suppress non-essential console output
--remediate Interactively remediate failed checks
--remediate-fail Remediate only FAIL status issues
--remediate-warning Remediate only WARNING status issues
--remediate-info Remediate only INFO status issues
--auto-remediate Automatically remediate without prompting
--remediation-file JSON file with specific issues to remediate

Help and Information

Display help information:

python3 linux_security_audit.py --help

List available modules:

python3 linux_security_audit.py --list-modules

Module Selection

Available Modules

The project includes 8 security framework modules:

Module Full Name Check Count Description
Core Core Security Baseline 153 Industry best practices and OS-specific security guidance
CIS CIS Benchmarks 212 Center for Internet Security benchmark compliance
CISA CISA Guidance 147 Cybersecurity and Infrastructure Security Agency best practices
ENISA ENISA Guidelines 97 European Union Agency for Cybersecurity standards
ISO27001 ISO/IEC 27001 115 International information security management standard
NIST NIST Frameworks 172 NIST 800-53, CSF 2.0, and 800-171 controls
NSA NSA Hardening 144 National Security Agency security configuration guides
STIG DISA STIGs 167 Defense Information Systems Agency Security Technical Implementation Guides

Module Selection Examples

Run All Modules (Default)

sudo python3 linux_security_audit.py
# or explicitly
sudo python3 linux_security_audit.py -m All

Use Case: Comprehensive security assessment
Time: 3-5 minutes
Checks: 1,100+ security checks

Run Single Module

# Core baseline security
sudo python3 linux_security_audit.py -m Core

# CIS Benchmarks only
sudo python3 linux_security_audit.py -m CIS

# NIST frameworks only
sudo python3 linux_security_audit.py -m NIST

Use Case: Focused assessment on specific framework
Time: 20-45 seconds per module
Checks: 97-212 per module

Run Multiple Specific Modules

# Compliance-focused (CIS, NIST, ISO27001)
sudo python3 linux_security_audit.py -m CIS,NIST,ISO27001

# Government/Critical Infrastructure (STIG, NSA, CISA)
sudo python3 linux_security_audit.py -m STIG,NSA,CISA

# Baseline + Compliance (Core, CIS)
sudo python3 linux_security_audit.py -m Core,CIS

Note: Module names are case-insensitive. Use commas with no spaces.

Module Selection Strategy

For Initial Assessment

sudo python3 linux_security_audit.py -m Core,CIS

Start with Core and CIS for fundamental security posture.

For Compliance Audits

# Financial/General: ISO27001, NIST, CIS
sudo python3 linux_security_audit.py -m ISO27001,NIST,CIS

# Government/Defense: STIG, NSA, NIST
sudo python3 linux_security_audit.py -m STIG,NSA,NIST

# European Organizations: ISO27001, ENISA, CIS
sudo python3 linux_security_audit.py -m ISO27001,ENISA,CIS

For Continuous Monitoring

# Lightweight daily checks
sudo python3 linux_security_audit.py -m Core,CISA

# Weekly comprehensive
sudo python3 linux_security_audit.py -m All

Output Formats

HTML (Default)

Interactive browser-based report with rich features.

sudo python3 linux_security_audit.py -f HTML
# or
sudo python3 linux_security_audit.py  # HTML is default

Features:

  • Interactive filtering by status and module
  • Sortable columns (click headers)
  • Full-text search across all fields
  • Dark/Light theme toggle
  • Export selected issues to JSON
  • Inline remediation commands
  • Statistics dashboard

File Naming: Security-Audit-Report-YYYYMMDD-HHMMSS.html

Use Cases:

  • Manual security reviews
  • Management reporting
  • Compliance documentation
  • Interactive issue exploration

Example with Custom Path:

sudo python3 linux_security_audit.py -f HTML -o /var/reports/audit-$(date +%Y%m%d).html

CSV

Comma-separated values for spreadsheet analysis.

sudo python3 linux_security_audit.py -f CSV -o security-audit.csv

Structure:

Module,Category,Status,Message,Details,Remediation,Timestamp
Core,Password Policy,Pass,Password aging is configured,...
Core,SSH Security,Fail,Root login is enabled,...

Use Cases:

  • Excel/Google Sheets analysis
  • Data trending and graphing
  • Custom reporting workflows
  • Historical comparisons

Example for Tracking:

# Monthly security trends
sudo python3 linux_security_audit.py -f CSV -o /var/reports/$(date +%Y%m)-audit.csv

JSON

Structured data format for automation and APIs.

sudo python3 linux_security_audit.py -f JSON -o security-audit.json

Structure:

{
  "execution_info": {
    "hostname": "server01",
    "os_version": "Linux 5.15.0",
    "scan_date": "2025-01-07 14:30:22",
    "duration": "0:03:45",
    "modules_run": ["Core", "CIS", "NIST"],
    "total_checks": 512,
    "pass_count": 387,
    "fail_count": 89,
    "warning_count": 32,
    "info_count": 4,
    "error_count": 0
  },
  "results": [
    {
      "module": "Core",
      "category": "SSH Security",
      "status": "Fail",
      "message": "Root login is enabled",
      "details": "SSH configuration allows direct root login",
      "remediation": "sed -i 's/^PermitRootLogin.*/PermitRootLogin no/' /etc/ssh/sshd_config && systemctl restart sshd",
      "timestamp": "2025-01-07 14:30:25"
    }
  ]
}

Use Cases:

  • SIEM integration
  • Automation workflows
  • API consumption
  • Selective remediation (via --remediation-file)
  • Custom analysis scripts

Example for SIEM:

# Daily feed for SIEM
sudo python3 linux_security_audit.py -f JSON -o /var/siem/feeds/security-$(hostname)-$(date +%Y%m%d).json

XML

Extensible Markup Language for enterprise tools.

sudo python3 linux_security_audit.py -f XML -o security-audit.xml

Structure:

<?xml version="1.0" encoding="UTF-8"?>
<security_audit>
  <execution_info>
    <hostname>server01</hostname>
    <os_version>Linux 5.15.0</os_version>
    <scan_date>2025-01-07 14:30:22</scan_date>
    <total_checks>512</total_checks>
    <pass_count>387</pass_count>
    <fail_count>89</fail_count>
  </execution_info>
  <results>
    <result>
      <module>Core</module>
      <category>SSH Security</category>
      <status>Fail</status>
      <message>Root login is enabled</message>
    </result>
  </results>
</security_audit>

Use Cases:

  • Enterprise security tools (Splunk, QRadar)
  • GRC platforms
  • Configuration management systems
  • Legacy system integration

Example for Enterprise SIEM:

sudo python3 linux_security_audit.py -f XML -o /mnt/nfs/siem-intake/$(hostname)-audit.xml

Console

Direct terminal output without file creation.

sudo python3 linux_security_audit.py -f Console

Features:

  • Color-coded status (Pass=Green, Fail=Red, Warning=Yellow)
  • Real-time display as checks execute
  • Suitable for quick checks and terminal-only environments
  • Can be redirected to text files

Use Cases:

  • Quick security checks
  • SSH sessions without file transfer
  • Logging to text files via redirection
  • Automated scripts with parsed output

Example with Redirection:

# Save console output to text file
sudo python3 linux_security_audit.py -f Console > audit-$(date +%Y%m%d).txt 2>&1

Remediation Options

Understanding Remediation

Remediation allows you to automatically or interactively apply security fixes based on audit findings. All remediation requires root privileges.

Important Safety Notes:

  • Always review remediation commands before applying
  • Test in non-production environments first
  • Have backups of critical configurations
  • Document changes made during remediation
  • Consider maintenance windows for production systems

Interactive Remediation

Review and approve each fix individually with detailed information.

sudo python3 linux_security_audit.py --remediate

Workflow:

  1. Script performs full audit
  2. Presents each remediable issue one at a time
  3. Shows: Module, Category, Status, Message, Details, Remediation Command
  4. Prompts: [y]es, [n]o, [s]kip remaining, [q]uit
  5. Executes approved remediations
  6. Displays results for each action

Example Interaction:

====================================================================================================
Issue 1 of 156
====================================================================================================
Module:       Core
Category:     SSH Security
Status:       Fail
Message:      Root login is enabled
Details:      SSH configuration allows direct root login (security risk)

Remediation Command:
  sed -i 's/^PermitRootLogin.*/PermitRootLogin no/' /etc/ssh/sshd_config && systemctl restart sshd

Apply this remediation? [y]es, [n]o, [s]kip remaining, [q]uit: y

[+] Executing remediation...
[+] Remediation successful

Continue? Press Enter...

Use Cases:

  • First-time remediations
  • Learning remediation commands
  • Selective manual approval
  • High-security environments requiring human review

Status-Filtered Remediation

Remediate only issues with specific status levels.

Remediate Only FAIL Status

Critical security issues only:

sudo python3 linux_security_audit.py --remediate-fail

Use Cases:

  • Focus on critical vulnerabilities
  • Quick security wins
  • Pre-production hardening
  • Compliance requirement fixes

Remediate Only WARNING Status

Best practice violations:

sudo python3 linux_security_audit.py --remediate-warning

Use Cases:

  • Post-critical remediation
  • Configuration optimization
  • Security posture improvement
  • Non-urgent hardening

Remediate Only INFO Status

Informational recommendations:

sudo python3 linux_security_audit.py --remediate-info

Use Cases:

  • Optional security enhancements
  • Future-proofing configurations
  • Documentation and awareness

Automated Remediation

Automatically apply fixes without prompting for each issue.

sudo python3 linux_security_audit.py --auto-remediate

Workflow:

  1. Script performs full audit
  2. Identifies all remediable issues
  3. Displays summary of actions to be taken
  4. Prompts for final confirmation
  5. Executes all remediations automatically
  6. Displays summary of results

Example:

====================================================================================================
AUTOMATED REMEDIATION SUMMARY
====================================================================================================
Total Issues:       156
FAIL:               89 issues
WARNING:            52 issues
INFO:               15 issues

This will automatically execute 156 remediation commands.

[!] WARNING: This is an automated process. Ensure you understand the impact.
[!] Consider backing up critical configurations before proceeding.

Proceed with automated remediation? [yes/no]: yes

[*] Executing remediations...
[+] 1/156: Core - SSH Security: Root login disabled
[+] 2/156: Core - Firewall: UFW enabled and configured
[+] 3/156: CIS - Password Policy: Password aging configured
...
[+] 156/156: NIST - Audit Logging: Auditd configuration updated

====================================================================================================
REMEDIATION COMPLETE
====================================================================================================
Successful:    145 (93%)
Failed:         11 (7%)
Duration:      0:02:15
====================================================================================================

Use Cases:

  • Pre-configured environments
  • Automated deployment pipelines
  • Bulk system hardening
  • Emergency security responses

Safety: Includes final confirmation prompt before executing.

Combining Filters with Auto-Remediation

Focus automated remediation on specific status levels:

# Auto-fix only critical FAIL issues
sudo python3 linux_security_audit.py --remediate-fail --auto-remediate

# Auto-fix only WARNING best practices
sudo python3 linux_security_audit.py --remediate-warning --auto-remediate

Use Cases:

  • Staged remediation approach (FAIL first, then WARNING, then INFO)
  • Risk-based prioritization
  • Minimizing system changes

Selective Remediation (From JSON Export)

The most precise remediation method - fix only specific issues selected from the HTML report.

Workflow:

  1. Run Initial Audit:
sudo python3 linux_security_audit.py

  1. Review HTML Report:

    • Open the generated HTML report in browser
    • Review each finding
    • Use checkboxes to select specific issues to remediate
    • Click "Export Selected" button

  2. Save JSON File:

    • Browser downloads file: Selected-Report-YYYYMMDD-HHMMSS.json
    • Contains only your selected issues

  3. Run Selective Remediation:

sudo python3 linux_security_audit.py --auto-remediate --remediation-file Selected-Report-20250107-143022.json

Example JSON Structure (exported selection):

{
  "execution_info": {
    "hostname": "server01",
    "scan_date": "2025-01-07 14:30:22"
  },
  "results": [
    {
      "module": "Core",
      "category": "SSH Security",
      "status": "Fail",
      "message": "Root login is enabled",
      "remediation": "sed -i 's/^PermitRootLogin.*/PermitRootLogin no/' /etc/ssh/sshd_config && systemctl restart sshd"
    }
  ]
}

Use Cases:

  • Surgical precision in remediation
  • Change management requirements
  • Testing specific fixes
  • Phased remediation approach
  • Multiple administrators dividing work

Benefits:

  • Complete control over what gets fixed
  • Visual review of each issue before selection
  • Documentation of intentional changes
  • Repeatable remediation sets

Advanced Usage Patterns

Pattern 1: Baseline and Trend Analysis

Establish security baseline and track changes over time.

# Initial baseline
sudo python3 linux_security_audit.py -f JSON -o /var/security/baseline.json

# Weekly audits
sudo python3 linux_security_audit.py -f JSON -o /var/security/audit-$(date +%Y%m%d).json

# Compare results
# Use custom scripts or tools to diff JSON files

Pattern 2: Pre/Post Remediation Comparison

Document security improvements.

# Before remediation
sudo python3 linux_security_audit.py -o audit-before.html

# Apply fixes
sudo python3 linux_security_audit.py --remediate-fail --auto-remediate

# After remediation
sudo python3 linux_security_audit.py -o audit-after.html

# Compare statistics in both reports

Pattern 3: Multi-System Auditing

Audit multiple systems centrally.

# On each system (via SSH or automation)
ssh user@server1 "sudo python3 /opt/security-audit/linux_security_audit.py -f JSON -o /tmp/audit.json"
scp user@server1:/tmp/audit.json ./server1-audit-$(date +%Y%m%d).json

# Repeat for all systems, then consolidate results

Pattern 4: Compliance-Specific Audits

Focus on specific compliance requirements.

# PCI-DSS focus
sudo python3 linux_security_audit.py -m CIS,NIST,Core -o pci-audit-$(date +%Y%m%d).html

# HIPAA focus
sudo python3 linux_security_audit.py -m NIST,ISO27001,Core -o hipaa-audit-$(date +%Y%m%d).html

# FedRAMP focus
sudo python3 linux_security_audit.py -m NIST,STIG,NSA -o fedramp-audit-$(date +%Y%m%d).html

Pattern 5: Scheduled Automated Audits

Set up regular security monitoring.

Cron Example (/etc/cron.d/security-audit):

# Daily audit at 2 AM
0 2 * * * root /usr/bin/python3 /opt/security-audit/linux_security_audit.py -f JSON -o /var/log/security/audit-$(date +\%Y\%m\%d).json >> /var/log/security/audit.log 2>&1

# Weekly comprehensive HTML report on Sundays at 3 AM
0 3 * * 0 root /usr/bin/python3 /opt/security-audit/linux_security_audit.py -o /var/reports/weekly-audit-$(date +\%Y\%m\%d).html >> /var/log/security/audit.log 2>&1

Systemd Timer Example:

Service file (/etc/systemd/system/security-audit.service):

[Unit]
Description=Linux Security Audit
After=network.target

[Service]
Type=oneshot
ExecStart=/usr/bin/python3 /opt/security-audit/linux_security_audit.py -f JSON -o /var/log/security/audit-$(date +%%Y%%m%%d).json
StandardOutput=journal
StandardError=journal

Timer file (/etc/systemd/system/security-audit.timer):

[Unit]
Description=Daily Security Audit Timer
Requires=security-audit.service

[Timer]
OnCalendar=daily
OnCalendar=02:00
Persistent=true

[Install]
WantedBy=timers.target

Enable timer:

sudo systemctl daemon-reload
sudo systemctl enable security-audit.timer
sudo systemctl start security-audit.timer

Pattern 6: Development to Production Pipeline

Integrate into CI/CD pipelines.

# In deployment script
#!/bin/bash

# Deploy application
deploy_application.sh

# Run security audit
sudo python3 /opt/security-audit/linux_security_audit.py -m Core,CIS -f JSON -o /tmp/post-deploy-audit.json

# Parse results
FAIL_COUNT=$(jq '.execution_info.fail_count' /tmp/post-deploy-audit.json)

# Fail pipeline if critical issues found
if [ "$FAIL_COUNT" -gt 10 ]; then
    echo "Security audit failed with $FAIL_COUNT critical issues"
    exit 1
fi

echo "Security audit passed with $FAIL_COUNT issues (acceptable threshold)"

Pattern 7: Emergency Security Response

Rapid assessment during security incidents.

# Quick critical systems check
sudo python3 linux_security_audit.py -m Core,NSA,CISA -f Console | tee emergency-audit-$(date +%Y%m%d-%H%M%S).txt

# Immediate remediation of critical issues
sudo python3 linux_security_audit.py -m Core,NSA --remediate-fail --auto-remediate

Integration Scenarios

SIEM Integration (Splunk, QRadar)

# Generate XML for SIEM ingestion
sudo python3 linux_security_audit.py -f XML -o /var/siem-feeds/security-audit-$(hostname)-$(date +%Y%m%d).xml

# Or JSON for modern SIEMs
sudo python3 linux_security_audit.py -f JSON -o /var/siem-feeds/security-audit-$(hostname)-$(date +%Y%m%d).json

Configuration Management (Ansible)

Ansible Playbook Example:

---
- name: Run Linux Security Audit
  hosts: all
  become: yes
  tasks:
    - name: Copy audit script
      copy:
        src: /path/to/linux_security_audit.py
        dest: /tmp/linux_security_audit.py
        mode: '0755'

    - name: Copy security modules
      copy:
        src: "{{ item }}"
        dest: /tmp/
      with_fileglob:
        - /path/to/module_*.py

    - name: Run security audit
      command: python3 /tmp/linux_security_audit.py -f JSON -o /tmp/audit.json
      register: audit_result

    - name: Fetch audit results
      fetch:
        src: /tmp/audit.json
        dest: ./audit-results/{{ inventory_hostname }}-audit.json
        flat: yes

Ticketing System Integration

# Generate audit and parse failures
sudo python3 linux_security_audit.py -f JSON -o /tmp/audit.json

# Create tickets for each FAIL status issue
python3 - <<EOF
import json
import requests

with open('/tmp/audit.json') as f:
    data = json.load(f)

for result in data['results']:
    if result['status'] == 'Fail':
        ticket = {
            'title': f"{result['module']} - {result['category']}: {result['message']}",
            'description': result['details'],
            'priority': 'High',
            'remediation': result['remediation']
        }
        # Post to ticketing API
        requests.post('https://ticketing.example.com/api/tickets', json=ticket)
EOF

GRC Platform Integration

# Generate compliance-focused reports
sudo python3 linux_security_audit.py -m CIS,NIST,ISO27001 -f CSV -o compliance-$(date +%Y%m%d).csv

# Upload to GRC platform via API or file transfer
curl -X POST -F "file=@compliance-$(date +%Y%m%d).csv" https://grc-platform.example.com/api/upload

Best Practices

Before Running Audits

  1. Test in Non-Production First: Always test on development/staging systems before production
  2. Schedule Appropriately: Run during maintenance windows or low-usage periods
  3. Communicate: Inform relevant teams before running audits
  4. Backup Configurations: Back up critical config files before remediation
  5. Review Modules: Select appropriate modules for your environment and compliance needs

During Execution

  1. Monitor Progress: Watch for errors or unexpected behavior
  2. Review Results: Don't blindly accept all findings - validate in your context
  3. Document Changes: Keep logs of all remediations applied
  4. Test After Remediation: Verify system functionality after applying fixes
  5. Staged Approach: Fix critical issues first, then warnings, then informational

Report Management

  1. Consistent Naming: Use consistent filename conventions
  2. Centralized Storage: Store reports in a central, backed-up location
  3. Access Controls: Protect reports (contain security information)
  4. Retention Policy: Define how long to keep audit reports
  5. Regular Reviews: Schedule periodic review of audit trends

Remediation Safety

  1. Read First: Always read remediation commands before executing
  2. Understand Impact: Know what the remediation will change
  3. Test Individually: Test critical remediations one at a time
  4. Have Rollback Plan: Know how to undo changes if needed
  5. Document Everything: Keep detailed logs of what was changed and why

Continuous Improvement

  1. Trend Analysis: Track metrics over time to measure improvement
  2. Adjust Baselines: Update expectations as security posture improves
  3. Learn Patterns: Understand recurring issues and address root causes
  4. Automate Where Safe: Automate known-safe remediations over time
  5. Share Knowledge: Document lessons learned and share with team

Common Usage Patterns Summary

Scenario Command Frequency Output
Initial Security Baseline sudo python3 linux_security_audit.py -m Core,CIS Once HTML
Daily Monitoring sudo python3 linux_security_audit.py -f JSON Daily (cron) JSON
Weekly Compliance sudo python3 linux_security_audit.py -m CIS,NIST,ISO27001 Weekly HTML
Pre-Deployment Check sudo python3 linux_security_audit.py -m Core,NSA Per-deployment JSON/Console
Emergency Assessment sudo python3 linux_security_audit.py -m Core,NSA -f Console As-needed Console
SIEM Feed sudo python3 linux_security_audit.py -f XML Daily XML
Change Management sudo python3 linux_security_audit.py -o before.html + remediate + -o after.html Per-change HTML

Getting More Help

v3.0 Pipeline Flags

The v3.0 release adds nine new CLI flags that activate enhanced pipeline phases without changing existing behaviour. All v3 flags are optional; running without them produces the same output as v2.0.

--baseline PATH

Compare the current audit against a previously saved baseline JSON file. Produces a drift report classifying each finding as new failure, resolved, regression, improvement, etc.

# Generate the baseline
sudo python3 linux_security_audit.py -f JSON -o baseline-202604.json

# Later, compare
sudo python3 linux_security_audit.py --baseline baseline-202604.json

--rollback-path PATH

Generate a bash rollback script during remediation. Captures pre-modification state for sysctl, file content/permissions, services, and kernel modules. Run the generated script to undo all changes.

sudo python3 linux_security_audit.py --remediate-fail --rollback-path /var/lib/audit/rollback.sh

--remediation-bundle NAME

Apply a named remediation bundle. Bundles group related fixes so you can apply a coherent set with one command. Run --list-bundles to see all available bundles.

sudo python3 linux_security_audit.py --remediation-bundle HardenSSH --auto-remediate

--asset-criticality 1-10

Set the asset criticality for risk priority scoring. Higher values mean a finding on this system contributes more to the priority score. Default is 5.

# High-value production system
sudo python3 linux_security_audit.py --asset-criticality 9 --show-risk-priority

# Isolated build agent
sudo python3 linux_security_audit.py --asset-criticality 3 --show-risk-priority

--show-risk-priority

Display risk priority scores (1-100) for each Fail/Warning finding, ranked highest first. Combines severity, exploitability, exposure, and asset criticality.

--show-correlations

Display cross-framework control correlations for each result. Shows how a single finding maps to identifiers in CIS, NIST, STIG, ISO 27001, NSA, CISA, ENISA, PCI DSS, HIPAA, etc.

--validate-results

Run strict result validation. Reports any defects in module output (missing severity, malformed cross-references, control characters in messages).

--list-bundles

List all available remediation bundles with their descriptions, included topics, prerequisites, and impact profiles. Exits without running an audit.

python3 linux_security_audit.py --list-bundles

--threshold N

Set the compliance score pass/fail threshold. Default is 70.0. Three scoring methods are computed: simple (pass percentage), weighted (severity-weighted), and severity-adjusted (weight × status credit).

sudo python3 linux_security_audit.py --threshold 85

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Linux Security Audit Project · Version 2.0 · MIT License

Repository · Releases · Issues · Pull Requests

Changelog · Contributing · Security Policy · License

Frameworks: Core · CIS · CISA · ENISA · ISO 27001 · NIST · NSA · STIG

Coverage: 8 Modules · 1,207 Automated Security Checks · 5 Native Output Formats · Zero External Dependencies

This documentation reflects Linux Security Audit Project v2.0 released 2026-03-02. For older versions, see the release tags.

Linux Security Audit

Version 2.0 · 8 modules · 1,207 checks

🚀 Getting Started

📚 Reference

🏗️ Architecture

🛠️ Operations

📦 Release Information

🔍 Quick Reference

Frameworks Covered

Core · CIS · CISA · ENISA · ISO 27001 · NIST · NSA · STIG

Output Formats

HTML · JSON · CSV · XML · Console

Status Values

Pass · Fail · Warning · Info · Error

Severity Levels

Critical · High · Medium · Low · Informational

🔗 External Links

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