Analysis_Tools

CPE Caching System Documentation

Overview

The CPE Caching System dramatically reduces processing time for large CVE dataset analysis by storing NVD /cpes/ API responses locally and reusing them across multiple CVE records.

Benefits

Configuration

The cache system is configured in config.json:

"cache": {
    "enabled": true,           // Enable/disable caching
    "directory": "cache",      // Cache directory name
    "max_age_hours": 12,       // Hours before cache entries expire (12 hours)
    "max_size_mb": 500,        // Maximum cache size (future use)
    "compression": false,      // Enable gzip compression for cache files
    "validation_on_startup": true,  // Validate cache on startup
    "auto_cleanup": true       // Automatically clean expired entries
}

Cache Refresh Strategy

The cache uses an aggressive 12-hour refresh strategy to ensure data freshness:

How It Works

  1. Cache Check: Before making an NVD API call, the system checks if the CPE string already exists in the local cache
  2. Cache Hit: If found and not expired, the cached response is used immediately
  3. Cache Miss: If not found, the API call is made and the response is cached for future use
  4. Cache Storage: Cache data is stored in cache/ directory in the project root

Cache Files

Cache Entry Structure

Each cache entry contains:

{
  "cpe:2.3:a:microsoft:windows": {
    "query_response": { /* Full NVD API response */ },
    "last_queried": "2025-06-21T10:30:00Z",
    "query_count": 15,
    "total_results": 245,
    "cache_version": "1.0"
  }
}

Performance Monitoring

The system provides detailed cache performance logging:

Example log output:

[INFO] Cache session performance: 1,847 hits, 423 misses, 81.4% hit rate, 423 new entries
[INFO] Cache lifetime performance: 78.5% hit rate, 15,234 API calls saved

Usage

The caching system is automatically integrated into the existing workflow. No changes to existing commands or usage patterns are required.

Bulk Processing

When processing large datasets, the cache will automatically:

  1. Load existing cache data at startup
  2. Check cache before each API call
  3. Store new responses for future use
  4. Log performance statistics
  5. Save updated cache data when complete

Single CVE Processing

Even single CVE processing benefits from the cache by:

Cache Management

Automatic Refresh (12-Hour Strategy)

Performance Impact

Manual Cache Operations

# Disable caching temporarily
config['cache']['enabled'] = False

# Clear cache completely
cache.clear()

# Force cache save
cache.flush()

Cache Statistics

stats = cache.get_stats()
print(f"Total entries: {stats['total_entries']}")
print(f"Hit rate: {stats['lifetime_hit_rate']}%")
print(f"API calls saved: {stats['api_calls_saved']}")

Performance Optimization

The cache system has been heavily optimized for production use:

Ultra-Fast JSON Operations

Benchmark Results

Operation Entries Time Performance
Save Cache 10,000 0.02s 500,000 entries/sec
Load Cache 10,000 0.07s 140,000 entries/sec
Cache Lookup 1,000 0.005s 200,000 lookups/sec
Add Entry 10,000 0.07s 140,000 entries/sec

Real-World Impact

Best Practices

  1. Keep cache enabled for all bulk processing operations
  2. Monitor cache hit rates - consistently low rates may indicate data quality issues
  3. Periodic cache cleanup - let expired entries be removed automatically
  4. Backup important caches for large operational datasets
  5. Review cache size periodically to ensure it doesn’t grow excessively

Troubleshooting

Cache Not Loading

Low Hit Rates

Performance Issues

Future Enhancements

Potential future improvements include: