SWE Pattern Analysis
8 Years of Data Integrity Incidents (2018-2025)
Incident Timeline
Track the evolution of data integrity failures over time
Key Insights
- Peak incident year: 2019 with 10 incidents
- Average new pattern discovery rate: 4.6 per year
- Most recent trend: Stabilizing incident rate
Pattern Distribution
Most frequently observed schema weaknesses
Top 10 SWE Patterns
Cantorian Magnitude Distribution
Most Common Patterns
Industry Impact Analysis
Schema weaknesses by industry sector
Industry-Specific Patterns
Healthcare
14 incidents, 10 unique patterns
- Data protection gaps
- vendor security failures
Financial Services
8 incidents, 8 unique patterns
- Legacy system brittleness
- monolithic architectures
E-commerce/SaaS
8 incidents, 6 unique patterns
- Scaling limitations
- cache dependencies
Government
7 incidents, 3 unique patterns
- Spreadsheet abuse
- legacy mainframes
Emerging Trends & Predictions
New patterns and evolving threat landscape
🔥 Hot Patterns
Rapidly increasing in frequency
🌅 Emerging Threats
New patterns discovered recently
📉 Declining Patterns
Becoming less common (better understood)
Pattern Evolution
How schema weaknesses have evolved over time
Understanding the Evolution
Explore Further
Dive deeper into the data with our specialized analysis tools
📅 Incident Timeline
Browse all 57 incidents chronologically with filters and ethical context
→🔍 Pattern Explorer
Interactive network graph showing pattern relationships and evolution
→🏢 Industry Deep Dives
Sector-specific vulnerabilities and compliance considerations
→🛠️ Developer Toolkit
Detection queries, cost calculator, and architecture decision helper
→