Layer 7 DDoS Mitigation: Application-Layer Attack Protection
AI-powered protection against HTTP floods, bot attacks, and application-layer threats.
Surgical mitigation in <30 seconds with <0.01% false positives.
Sophisticated DDoS protection targeting application-layer attacks (HTTP/HTTPS floods, DNS attacks, Slowloris, etc.). AI-powered detection identifies malicious traffic patterns while allowing legitimate users through.
Our Layer 7 mitigation is part of our comprehensive DDoS protection services, protecting web applications, APIs, and DNS infrastructure from even the most advanced application-layer attacks.
Built for web applications, SaaS platforms, and API providers who face intelligent attackers. Surgical mitigation blocks bots and malicious scripts while maintaining user experience for legitimate traffic.
Technical Specifications
| Protection Layers | HTTP/HTTPS, DNS, SIP, custom protocols |
| Detection Time | <10 seconds (AI-powered) |
| Mitigation Time | <30 seconds from detection |
| Capacity | Up to 10 Tbps (network-wide) |
| False Positive Rate | <0.01% (AI learning) |
| Legitimate Traffic Impact | Minimal (<5ms latency) |
| Attack Types | HTTP floods, Slowloris, DNS amplification, API abuse |
| Bot Detection | Advanced fingerprinting + behavioral analysis |
| CAPTCHA | Optional challenge for suspicious requests |
| Rate Limiting | Per-IP, per-endpoint, custom rules |
| Geographic Blocking | By country, region, or ASN |
| Custom Rules | API for custom mitigation policies |
| Logging | Full attack logs + legitimate traffic stats |
| Uptime SLA | 99.999% |
Attack Types Protected
HTTP/HTTPS Floods
Volumetric attacks targeting web servers. We block millions of requests while allowing legitimate traffic through.
Slowloris/Slow POST
Low-bandwidth attacks that exhaust server connections. Detected via behavioral analysis.
DNS Amplification
Reflection attacks using DNS resolvers. Mitigated at scrubbing centers before reaching your infrastructure.
Application-Specific Attacks
WordPress login brute force, API endpoint abuse, form submission floods. Custom rules per application.
Bot Attacks
Credential stuffing, web scraping, inventory hoarding. Advanced bot fingerprinting and behavioral detection.
Key Features
AI-Powered Detection
Machine learning identifies attack patterns in real-time. Learns normal traffic baselines automatically.
Surgical Mitigation
Block only malicious traffic. Legitimate users experience normal performance (<5ms added latency).
Sub-Minute Response
Detection in <10 seconds, mitigation active within 30 seconds. No manual intervention required.
CAPTCHA Challenges
Optional CAPTCHA for suspicious traffic. Verify humans vs bots without blocking completely.
Custom Rate Limiting
Per-IP, per-endpoint, or custom rules. Protect specific API endpoints or login pages.
Detailed Analytics
Real-time attack dashboards. Historical data for forensic analysis.
How It Works
Step 1: Traffic Analysis
All traffic flows through our scrubbing centers. AI analyzes request patterns, headers, behavior.
Step 2: Threat Detection
Machine learning identifies anomalies: unusual request rates, malformed headers, bot signatures.
Step 3: Classification
Traffic classified as: legitimate, suspicious, or malicious. Suspicious traffic may receive CAPTCHA.
Step 4: Mitigation
Malicious traffic blocked at scrubbing center. Legitimate traffic forwarded to your origin with <5ms latency.
Step 5: Continuous Learning
AI adapts to new attack patterns. False positive rate decreases over time.
Use Cases
E-Commerce Platforms
Protect checkout flows from bot attacks. Prevent inventory hoarding during sales.
SaaS Applications
Defend login pages from credential stuffing. Protect APIs from abuse.
Financial Services
High-security applications requiring zero downtime. Regulatory compliance with DDoS protection.
Gaming Platforms
Protect game servers and authentication from targeted attacks. Low-latency mitigation.
Media/Streaming
Protect content delivery during high-traffic events. Ensure smooth streaming under attack.
Detection Methods
Behavioral Analysis
Request frequency, session duration, mouse movements, keyboard patterns.
Fingerprinting
Browser fingerprints, TLS fingerprints, HTTP/2 fingerprints. Identify bots vs real browsers.
Geographic Patterns
Unusual traffic sources, concentration from specific ASNs or countries.
Header Analysis
Missing headers, unusual User-Agents, malformed requests.
Rate Patterns
Requests per second per IP, burst patterns, distributed vs single-source attacks.
Why Virtuasys Layer 7?
Layer 7 vs Layer 3-4
| Feature | Layer 3-4 Protection | Layer 7 Mitigation |
|---|---|---|
| Attack Types | Volumetric (UDP, SYN) | Application (HTTP, DNS) |
| Detection | Volume-based | Behavior-based |
| Latency Impact | <1ms | <5ms |
| False Positives | Very low | Low (<0.01%) |
| Customization | Limited | Extensive (custom rules) |
| Use Case | Network infrastructure | Web apps, APIs |
Recommendation: Use both for complete protection.
FAQ
Common questions about application layer attack protection