Transform vulnerability data into production-ready, industry-specific signatures using the most competent, cost-effective, and reliable AI models
Discover the intelligence behind the system
Intelligently determines which signature type to generate based on vulnerability characteristics and learned patterns
Security teams face a critical challenge...
Manual signature creation takes hours or days
Requires deep knowledge of attack patterns
High false positive rates impact operations
Quality varies across different analysts
Difficulty keeping pace with new vulnerabilities
Expertise lost when team members leave
Every hour without protection is a window for attackers
AI-powered generation combined with persistent pattern recognition and accumulated expertise
The system doesn't just use AI - it builds and retains its own expertise
Curated security expertise, attack pattern libraries, signature generation best practices, and protocol specifications
47+ learned patterns from real-world use, success/failure analysis, false positive prevention strategies
User feedback integration, quality improvement patterns, context-aware recommendations, personalized approaches
Knowledge retained across all sessions, pattern reuse and refinement, cumulative expertise building
Upload TrendMicro XML, TSL ID, or CVE ID
Gathers data from 30+ sources
Evaluates data sufficiency using learned quality patterns
Determines IPS/IDP suitability using historical patterns
Loads ONLY relevant knowledge base files
Quality scoring using learned criteria
Natural language feedback collection
New patterns added to graph memory
What makes this system intelligent
System improves by 12% every 6 months through accumulated learning
Specialized protection for your sector's unique threats
See how the system handles industry-specific threats
CVE-2024-8765 - Critical Severity
Payment gateway SQL injection vulnerability detected
Retrieved 8 SQL injection patterns from memory
Financial sector threat intelligence gathered
PCI-DSS compliance patterns applied
Quality: 92% (financial sector threshold: 85%)
Payment gateway attack patterns validated
IPS-suitable (application-layer attack)
12 similar financial sector signatures reviewed
Applied: SQL injection pattern #4, Financial sector false positive prevention
Quality: 94/100
Validated against PCI-DSS requirements
alert tcp any any -> any 443 (
msg:"SQL Injection - Payment Gateway - CVE-2024-8765";
flow:to_server,established;
content:"POST"; http_method;
content:"payment"; http_uri; nocase;
pcre:"/(\%27)|(\')|(\-\-)|(\%23)|(#)/i";
sid:1000765; rev:1;
)2 financial sector patterns applied • 12 similar signatures consulted • PCI-DSS compliant • 96% pattern effectiveness
CVE-2024-9123 - High Severity
Medical imaging protocol vulnerability detected
Retrieved 5 DICOM-specific patterns from memory
Healthcare sector threat intelligence gathered
HIPAA compliance patterns applied
Quality: 88% (healthcare threshold: 80%)
Medical device attack patterns validated
IDP-suitable (protocol-level attack)
8 similar healthcare signatures reviewed
Applied: DICOM protocol pattern #2, Healthcare false positive prevention
Quality: 91/100
Validated against HIPAA security requirements
alert tcp any any -> any 104 (
msg:"DICOM Protocol Exploit - CVE-2024-9123";
flow:to_server,established;
content:"|00 00 00 00|"; offset:0; depth:4;
content:"|00 00 00 01|"; distance:4; within:4;
byte_test:4,>,1000,8,relative;
sid:1009123; rev:1;
)2 healthcare patterns applied • 8 similar signatures consulted • HIPAA compliant • 91% pattern effectiveness
CVE-2024-7456 - Critical Severity
Industrial control system vulnerability detected
Retrieved 7 ICS/SCADA patterns from memory
Critical infrastructure threat intelligence gathered
NERC CIP compliance patterns applied
Quality: 95% (infrastructure threshold: 90%)
SCADA attack patterns validated
IDP-suitable (industrial protocol attack)
10 similar infrastructure signatures reviewed
Applied: Modbus TCP pattern #3, Infrastructure false positive prevention
Quality: 96/100
Validated against NERC CIP requirements
alert tcp any any -> any 502 (
msg:"Modbus TCP Unauthorized Write - CVE-2024-7456";
flow:to_server,established;
content:"|00 00 00 00 00 06|"; offset:0; depth:6;
byte_test:1,=,16,7,relative; # Function code 16
byte_test:2,>,100,8,relative; # Excessive register count
sid:1007456; rev:1;
)3 infrastructure patterns applied • 10 similar signatures consulted • NERC CIP compliant • 96% pattern effectiveness
CVE-2024-6789 - High Severity
E-commerce price manipulation vulnerability detected
Retrieved 9 e-commerce attack patterns from memory
Retail sector threat intelligence gathered
PCI-DSS compliance patterns applied
Quality: 87% (retail threshold: 80%)
Shopping cart attack patterns validated
IPS-suitable (application-layer attack)
11 similar retail signatures reviewed
Applied: Price manipulation pattern #5, Retail false positive prevention
Quality: 93/100
Validated against PCI-DSS requirements
alert tcp any any -> any 443 (
msg:"Shopping Cart Price Manipulation - CVE-2024-6789";
flow:to_server,established;
content:"POST"; http_method;
content:"cart"; http_uri; nocase;
content:"price"; http_client_body; nocase;
pcre:"/price[\"']?\s*:\s*-?\d+\.\d{3,}/i";
sid:1006789; rev:1;
)2 retail patterns applied • 11 similar signatures consulted • PCI-DSS compliant • 93% pattern effectiveness
We don't just collect data - we extract actionable signature intelligence
Start with 47+ learned patterns. Add your own expertise. Watch the system get smarter with every signature.