System-Wide Military Audit and Inspection Guide
Overview
The System-Wide Military Audit and Inspection system provides comprehensive automated auditing capabilities for the entire Epstein Files Hub infrastructure. This system performs thorough inspections of all components, generates detailed reports, and provides actionable recommendations for system maintenance and improvement.
Table of Contents
- Introduction
- Audit Capabilities
- Quick Start
- Usage Guide
- Report Formats
- Status Levels
- Automation
- Integration
- Best Practices
- Troubleshooting
Introduction
Purpose
The audit system is designed to:
- Monitor all infrastructure components continuously
- Detect issues early before they become critical
- Report findings in military-style formatted reports
- Recommend corrective actions
- Track system health over time
- Ensure compliance with security and quality standards
Key Features
- ✅ 9 Comprehensive Audit Sections
- ✅ Multiple Report Formats (Markdown, JSON, Text)
- ✅ Automated Scheduling (Daily/Weekly)
- ✅ GitHub Actions Integration
- ✅ Issue Creation for critical findings
- ✅ Historical Tracking via logs
- ✅ Zero External Dependencies (uses Python stdlib)
- ✅ Military-Grade Formatting for professional reports
Audit Capabilities
1. Infrastructure Audit
Validates core infrastructure components:
- Directory Structure
- 12 critical directories verified
- Existence and write permissions checked
- Missing directories flagged
- Configuration Files
- 7 essential configuration files
- Readability verification
- Missing files reported
- Python Environment
- Version compatibility (3.8+)
- Package availability
- Installation verification
- Git Repository
- Status checking
- Uncommitted changes detection
- Repository health
2. Agent Infrastructure Audit
Monitors all AI agents:
- Agent Directory Verification
- 26+ agent directories checked
- Documentation completeness
- Operational status
- Agent Types Monitored
- indexing-bot
- image-analysis-bot
- verification-bot
- search-bot
- summarization-bot
- pdf-analysis-bot
- cross-reference-bot
- entity-extraction-bot
- timeline-bot
- fact-checking-bot
- audit-bot (self-monitoring)
- Infrastructure Documentation
- AGENT_INFRASTRUCTURE.md presence
- Bot usage guides
- Development documentation
3. Data Integrity Audit
Validates data storage:
- Data Directories
- data/
- data/public_files/
- data/processed/
- data/wikipedia/
- Metrics Tracked
- File counts
- Storage size (MB/GB)
- Directory accessibility
- Data completeness
4. Documentation Audit
Ensures documentation completeness:
- Required Documents
- README.md - Project overview
- CONTRIBUTING.md - Contribution guidelines
- SETUP_GUIDE.md - Setup instructions
- docs/Glossary.md - Terminology
- docs/CharacterDirectory.md - Character index
- docs/Timeline.md - Event timeline
- docs/Bot-Usage-Guide.md - Bot documentation
- Quality Checks
- File existence
- Minimum size requirements
- Content validation
5. Security Audit
Security compliance verification:
- Environment Protection
- .env file detection (should NOT exist in repo)
- .env.example template verification
- Environment variable security
- Git Security
- .gitignore configuration
- Sensitive file protection
- Secret management verification
- Sensitive Files Detection
- *.key files
- *.pem certificates
- *.p12 keystores
- Password/secret files
6. Workflow Audit
GitHub Actions verification:
- Workflow Files
- .github/workflows/*.yml
- Configuration validity
- Scheduling verification
- Key Workflows
- agent-monitoring.yml
- verify-setup.yml
- deploy-pages.yml
- system-audit.yml (self)
7. Scripts Audit
Python scripts validation:
- Script Directory
- scripts/*.py files
- Executable permissions
- Size and integrity
- Critical Scripts
- fetch-public-files.py
- fetch-wikipedia-data.py
- generate-search-index.py
- process-pdfs.py
- safe-source-expander.py
- system-audit.py (self)
8. Web Interface Audit
Web assets verification:
- Files Checked
- HTML pages
- JavaScript files
- CSS stylesheets
- Images and assets
- Metrics
- File counts
- Directory structure
- Asset accessibility
9. Resource Utilization Audit
Resource monitoring:
- Repository Size
- Total files
- Total size (MB/GB)
- Growth tracking
- Log Directory
- Size monitoring
- Cleanup recommendations
- Warning thresholds
- Cache Directory
- Cache size
- Optimization suggestions
- Space management
Quick Start
Command Line
# Run basic audit with markdown report
make system-audit
# Run audit with all report formats
make system-audit-all
# Run military-style audit (alias)
make military-audit
# Run audit quietly (no console output)
make system-audit-quiet
# Direct Python execution
python scripts/system-audit.py
# With custom options
python scripts/system-audit.py --format all --output-dir logs
GitHub Actions
Trigger manually:
- Go to Actions tab
- Select System-Wide Audit and Inspection
- Click Run workflow
- Choose options and run
Usage Guide
Basic Execution
# Standard audit
python scripts/system-audit.py
# Options:
# --output-dir DIR Where to save reports (default: logs)
# --format FORMAT Report format: markdown, json, text, all
# --quiet Suppress console output
Output Examples
Console Output
================================================================================
SYSTEM-WIDE MILITARY AUDIT AND INSPECTION
================================================================================
Audit ID: AUDIT-20260104180000
Timestamp: 2026-01-04 18:00:00 UTC
================================================================================
[1/9] INFRASTRUCTURE AUDIT
--------------------------------------------------------------------------------
Status: OPERATIONAL
Issues Found: 0
[2/9] AGENT INFRASTRUCTURE AUDIT
--------------------------------------------------------------------------------
Status: OPERATIONAL
Agents Operational: 10/10
[3/9] DATA INTEGRITY AUDIT
--------------------------------------------------------------------------------
Status: OPERATIONAL
Data Directories: 4/4
...
================================================================================
AUDIT COMPLETE
================================================================================
Audit ID: AUDIT-20260104180000
Overall Status: OPERATIONAL
Issues Found: 0
Recommendations: 3
================================================================================
Report Files
After execution, find reports in logs/:
logs/
├── system_audit_20260104_180000.md # Markdown report
├── system_audit_20260104_180000.json # JSON data
└── system_audit_20260104_180000.txt # Plain text report
Markdown Report
Professional formatted report with:
- Executive summary
- Section-by-section findings
- Issues and recommendations
- Audit certification footer
Use case: GitHub Issues, documentation, sharing
JSON Report
Machine-readable structured data:
{
"audit_id": "AUDIT-20260104180000",
"timestamp": "2026-01-04T18:00:00Z",
"overall_status": "OPERATIONAL",
"sections": {...},
"summary": {...}
}
Use case: Automation, dashboards, monitoring systems
Text Report
Plain text formatted for:
- Email distribution
- Terminal viewing
- Legacy systems
Use case: Email alerts, simple viewing
Status Levels
OPERATIONAL ✅
- Meaning: All systems functioning normally
- Action: None required - routine monitoring
- Color Code: Green
- Exit Code: 0
WARNING ⚠️
- Meaning: Minor issues detected
- Action: Review recommendations
- Color Code: Yellow
- Exit Code: 0
DEGRADED 🔶
- Meaning: Significant issues affecting functionality
- Action: Immediate attention needed
- Color Code: Orange
- Exit Code: 1
- Triggers: GitHub Issue creation
CRITICAL 🚨
- Meaning: Severe issues compromising system
- Action: Emergency response required
- Color Code: Red
- Exit Code: 2
- Triggers: GitHub Issue with priority labels
Automation
Daily Audits
Automatically run every day at 6:00 AM UTC:
schedule:
- cron: '0 6 * * *' # Daily
Actions:
- Run full system audit
- Generate all report formats
- Commit reports to repository
- Create issues for DEGRADED/CRITICAL status
Weekly Deep Audits
Every Sunday at 6:00 AM UTC:
schedule:
- cron: '0 6 * * 0' # Weekly on Sunday
Additional checks:
- Git activity analysis
- Repository statistics
- Disk usage trends
- Performance metrics
Output:
- Comprehensive weekly summary issue
- Historical trend analysis
- Capacity planning recommendations
Manual Triggers
Run on-demand via GitHub Actions:
- Navigate to Actions tab
- Select workflow
- Click “Run workflow”
- Choose audit type:
- standard - Regular audit
- deep - Extended analysis
- security-only - Security focus
Integration
Makefile
# Already integrated commands
make system-audit # Standard audit
make system-audit-all # All formats
make military-audit # Alias
make audit-report # Alias
Python API
from scripts.system_audit import SystemAuditor
# Create instance
auditor = SystemAuditor()
# Run audit
results = auditor.run_full_audit()
# Get status
overall_status = results['overall_status']
total_issues = results['summary']['total_issues']
# Generate report
markdown_report = auditor.generate_report('markdown')
json_report = auditor.generate_report('json')
# Save reports
auditor.save_report(output_dir='logs', format_type='all')
CI/CD Pipeline
Integrate into existing workflows:
- name: Run System Audit
run: python scripts/system-audit.py --format json
- name: Check Audit Status
run: |
STATUS=$(python -c "import json; print(json.load(open('logs/system_audit_latest.json'))['overall_status'])")
if [ "$STATUS" = "CRITICAL" ]; then
exit 1
fi
Best Practices
Regular Monitoring
- Review daily audit reports - Check GitHub for issues created
- Track trends - Monitor recurring recommendations
- Address issues promptly - Fix DEGRADED status items quickly
- Plan capacity - Use weekly reports for planning
Issue Management
- Critical Issues - Address immediately (same day)
- Degraded Status - Fix within 48 hours
- Warnings - Review weekly
- Recommendations - Implement during maintenance windows
Report Retention
- Daily reports: 90 days
- Weekly reports: 1 year
- Critical incidents: Indefinite
Threshold Management
Adjust as system grows:
# In system-audit.py
REPO_SIZE_WARNING = 50 # GB
LOGS_SIZE_WARNING = 1000 # MB
CACHE_SIZE_WARNING = 5000 # MB
Troubleshooting
Permission Errors
# Fix permissions
chmod -R u+w logs/
chmod +x scripts/system-audit.py
Module Import Errors
# Ensure Python path is correct
export PYTHONPATH="${PYTHONPATH}:$(pwd)"
# Or use absolute imports
python -m scripts.system-audit
Git Errors
# Ensure git is configured
git config user.name "Your Name"
git config user.email "your@email.com"
Large Repository Size
# Clean cache and logs
make clean
# Or specific cleanup
rm -rf cache/*
rm -rf logs/system_audit_*.{md,json,txt}
Audit Takes Too Long
# Use quiet mode
python scripts/system-audit.py --quiet
# Or run specific sections (modify script)
Advanced Usage
Custom Audit Sections
Add new sections by extending SystemAuditor:
def _audit_custom_section(self):
section = {
"status": "OPERATIONAL",
"checks": {},
"issues": [],
"recommendations": []
}
# Your checks here
self.audit_results["sections"]["custom"] = section
Threshold Customization
# Create custom auditor
class CustomAuditor(SystemAuditor):
REPO_SIZE_THRESHOLD = 100 # GB
LOGS_SIZE_THRESHOLD = 2000 # MB
Integration with Monitoring Systems
Export metrics:
# Generate JSON for monitoring
python scripts/system-audit.py --format json --quiet
# Parse and send to monitoring
python scripts/send-to-monitoring.py logs/system_audit_latest.json
Support
For issues or questions:
- GitHub Issues: Use label
audit or audit-bot
- Documentation: Check related docs above
- Logs: Review
logs/system_audit_*.{md,json,txt}
Changelog
Version 1.0.0 (2026-01-04)
- ✅ Initial release
- ✅ 9 comprehensive audit sections
- ✅ Multiple report formats
- ✅ GitHub Actions integration
- ✅ Automated daily/weekly audits
- ✅ Issue creation for critical status
Version: 1.0.0
Last Updated: 2026-01-04
Maintainer: System Audit Bot
Status: ✅ Production Ready