Building the Future of Device Intelligence
Lightning Research was born from academic research at one of the world's leading security conferences. We turned groundbreaking cross-browser fingerprinting science into a production platform that protects businesses from fraud, bots, and account abuse.
The Technology
How we identify devices across browsers without cookies.
Browser
90+ signals collected
GPU Timing
DRAWNAPART analysis
Audio
AudioContext extraction
Hashing
Stable hash generation
Similarity engine
Weighted heuristic matching
Device ID
Persistent identifier
Unlike cookie-based tracking, our fingerprinting uses hardware-level signals — GPU rendering patterns (DRAWNAPART-inspired timing analysis with 10K+ vertex workloads), audio processing characteristics, and canvas rasterization — that remain consistent regardless of browser, incognito mode, or VPN. A research-backed heuristic engine scores similarity across sessions with configurable weights; automated signal drift detection and stability benchmarking help accuracy degrade gracefully as browsers evolve. Pattern-based script detection (inspired by the DeepFPD taxonomy) classifies third-party fingerprinting attempts without relying on deep learning in the browser.
SOC 2 Type II (in progress) · GDPR-ready · High availability architecture — contact us for compliance documentation.
Our Values
The principles that guide everything we build.
Privacy First
Security without surveillance. Our fingerprinting is privacy-compliant by design — no PII, no cookies, fully auditable.
Research Driven
Built on peer-reviewed NDSS'17 research. Every signal and model is backed by published science.
Accuracy Obsessed
We continuously measure and improve cross-browser identification through automated drift detection and stability benchmarking.
Developer Focused
Clean APIs, comprehensive docs, TypeScript-first SDK. Tools that developers love to work with.
Team
The people behind Lightning Research.
Abhinav
Founder & CEO
Security researcher and full-stack engineer. Led the original NDSS research on cross-browser fingerprinting.
Our Journey
Research Published
Cross-browser fingerprinting paper presented at NDSS — the foundation of our technology. First to demonstrate GPU-based identification across browsers.
Platform Launch
First production release with a research-backed heuristic matching engine, real-time analytics, and the JavaScript SDK.
Enterprise Ready
Enterprise-grade security practices, on-premise deployment options, dedicated support, and custom SLA terms in contract.
Scale & Hardening
Multi-region deployment, enterprise security hardening, and on-premise deployment options for regulated industries.
Intelligence Leap
Shipped configurable similarity scoring, pattern-based script detection (DeepFPD-inspired taxonomy), calibration tooling for weights, automated signal drift monitoring, and DRAWNAPART-inspired GPU timing analysis.
Open Research
Built on published, peer-reviewed science.
(Cross-)Browser Fingerprinting via OS and Hardware Level Features
NDSS 2017 — Network and Distributed Systems Security Symposium
The foundational paper that proved cross-browser fingerprinting is possible by leveraging OS and hardware-level features — specifically GPU rendering tasks that produce identical outputs regardless of which browser is used. Our platform implements and extends this research with production-grade heuristic matching and real-time scoring.
NDSS 2017 ProceedingsReady to get started?
Whether you're looking to integrate our platform or learn more about our technology, we'd love to hear from you.