Research-driven security
We're not just building tools—we're advancing the field. Our detection models are developed through rigorous research and benchmark-driven evaluation.
Publications
Our research papers, technical reports, and datasets.
Multi-Channel Phishing Detection Using Transformer-Based Models
Our approach to unified detection across email, chat, and URL vectors using modern transformer architectures.
Behavioral Anomaly Detection in Enterprise Communication
Methods for identifying compromised accounts and targeted attacks through behavioral analysis.
Benchmark Suite for Phishing Detection Evaluation
A standardized benchmark for comparing phishing detection systems across multiple channels.
Publications will be linked here as they become available.
How we evaluate
Our commitment to rigorous, reproducible evaluation.
Benchmark-driven development
Every model improvement is measured against standardized benchmarks. We track precision, recall, and false positive rates across diverse test sets.
Real-world validation
Lab performance is just the start. We validate models against real-world attack patterns from industry partnerships and threat intelligence.
Continuous evaluation
Phishing evolves constantly. Our models are continuously evaluated against emerging threats and re-trained as needed.
Reproducible research
We're committed to sharing our methodology so the security community can build on our work and verify our claims.